Baseline 18F-FDG PET/CT quantitative parameters as prognostic factors in esophageal squamous cell cancer | Revista Española de Medicina Nuclear e Imagen Molecular (English Edition)

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Martínez, J.R. Infante, J. Quirós, J.I. Rayo, J. Serrano, M. Moreno, P. Jiménez, A. Cobo, A. Baena" "autores" => array:9 [ 0 => array:4 [ "nombre" => "A." "apellidos" => "Martínez" "email" => array:1 [ 0 => "andres.martineze@salud-juntaex.es" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "*" "identificador" => "cor0005" ] ] ] 1 => array:3 [ "nombre" => "J.R." "apellidos" => "Infante" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 2 => array:3 [ "nombre" => "J." "apellidos" => "Quirós" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "b" "identificador" => "aff0010" ] ] ] 3 => array:3 [ "nombre" => "J.I." "apellidos" => "Rayo" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 4 => array:3 [ "nombre" => "J." 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Comparison of CSS according to the TLG value." ] ] ] "textoCompleto" => "IntroductionEsophageal cancer is the ninth most frequent diagnosis in the world and represents the sixth cause of death by a neoplastic process<a class="elsevierStyleCrossRef" href="#bib0005">1</a>. Squamous cell carcinoma (SCC) is the most frequent histological type, overall in Asian countries and Southern Africa, although in the last four decades the incidence of adenocarcinoma has increased in Europe and North America<a class="elsevierStyleCrossRef" href="#bib0010">2</a>.SCC is an aggressive tumor with an unfavorable prognosis, with most patients being asymptomatic until reaching an advanced stage<a class="elsevierStyleCrossRef" href="#bib0015">3</a>. Treatment includes the use of chemotherapy plus radiotherapy (CRT) followed by surgery, the generally recommended therapeutic modality<a class="elsevierStyleCrossRef" href="#bib0020">4</a>. Nonetheless, more than one third of patients present remission after neoadjuvant treatment, considering this therapy as possibly definitive, obviating the need for surgery. On the other hand, in the absence of adequate response to CRT, patients are exposed to secondary effects while surgical treatment is delayed<a class="elsevierStyleCrossRef" href="#bib0025">5</a>.In this context, the application of non invasive diagnostic methods able to determine prognostic factors to the diagnosis are gaining significant importance. The prediction of possible responder and non responder patients allows individualization of treatment, reducing costs<a class="elsevierStyleCrossRef" href="#bib0025">5</a>. Computerized tomography (CT) is useful to define tumor size and the extension of the process to adjacent structures, but it is fundamentally based on morphological changes. In turn, transesophageal ultrasonography is limited to evaluating the depth of tumor invasion and identifying locoregional adenopathies<a class="elsevierStyleCrossRef" href="#bib0030">6</a>.In addition to adequately determining distant involvement, which is frequent in esophageal cancer, fluorodeoxyglucose positron emission tomography /CT (18F-FDG PET/CT) allows evaluation of response to neoadjuvant treatment. Likewise, it is useful for planning radiotherapyand defining the tumor volume to irradiate, thereby limiting involvement of the lung or heart<a class="elsevierStyleCrossRef" href="#bib0035">7</a>. Different authors have evaluated quantitative parameters of PET as well as the maximum standard uptake value (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) with different and even contradictory results<a class="elsevierStyleCrossRef" href="#bib0040">8</a>. A smaller number of publications have focused on assessing the utility of these parameters as predictors of response to treatment and the survival of patients with SCC<a class="elsevierStyleCrossRef" href="#bib0045">9</a>.Taking this into acount, the objective of this study was to determine the utility of quantitative 18F-FDG PET/CT parameters as prognostic factors of response to neoadjuvant treatment, progression-free survival (PFS) and cancer-specific survival (CSS) in patients in our setting diagnosed with esophageal SCC.Material and methodsPatientsWe performed a retrospective study evaluating patients referred to our department with a diagnosis of esophageal cancer from January 2011 to December 2016. The collection of data on the evolution of the patients finalized in October 2020, allowing a minimum follow-up of 4 years in cases in which death did not take place.The inclusion criteria were: a minimum age of 18 years, histology compatible with SCC, 18F-FDG PET/CT with the diagnosis and examination prior to treatment inclusing physical examination, laboratory analysis and radiological study by CT. The exclusion criteria were a previous history of neoplasia, the presence of a second synchronous tumor, cause of death other than esophageal cancer and the impossibility of performing follow-up.Clinical tumor, node, metastasis (cTNM) staging was performed using the classification described in the 8th edition of the American Joint Committe on Cancer, AJCC-TNM (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>)<a class="elsevierStyleCrossRef" href="#bib0050">10</a>.<elsevierMultimedia ident="tbl0005"></elsevierMultimedia>PET/CT studyThe metabolic study was carried out in a hybrid Discovery ST4 system (General Electric, Milwaukee, USA.) within 7 weeks prior to treatment. Before injection of the radiopharmaceutical, all the patients had been fasting for at least 4 h with adequate hydratation and glucemia level <10 mMol/l. An 18F-FDG dose of 3.5–4.5 MBq/kg was injected. After an interval of 60 min images were obtained with the arms above the head. For the CT study neither oral nor intravenous contrast was used. The CT acquisition parameters were 110 keV, modulation with a maximum amperage of 80 mA and slice thickness of 3.75 mm. Three dimensional (3D) PET images were then acquired at 2 min per bed, with a matrix of 128 × 128 and iterative reconstruction.An Advantage Volume Share 4, GE Healthcare workstation was used for image processing, quantifying the metabolic parameters, SUVmax, SUVmean, MTV and TLG (product between SUVmean and MTV). These latter two parameters were calculated with a 3D isocontour threshold based on a SUVmax of 2.5, one the most commonly used in the bibliography consulted (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>).<elsevierMultimedia ident="fig0005"></elsevierMultimedia>In the case of involvement outside the primary tumor, the MTV and TLG of each of the lesions found in the metabolic study were determined (primary lesion, adenopathy and/or distant involvement), summing all the values found. In this way, both parameters represent the whole of the neoplastic involvement. The SUVmax and SUVmean defined for each patient was the maximum value quantified independently of their localization (in or outside the esophagus).Likewsie, the SUVmax and SUVmean of the liver was calculated to determine the corresponding lesion/liver ratios (tumoral SUVmax/liver SUVmax, expressed as ratio-A, and tumoral SUVmean/liver SUVmean, expressed as ratio-B). Spherical volumes of interest with a diameter of 3 cm at the level of hepatic segment VII were drawn similar to what is recommended in the PERCIST evaluation.Evaluation of the images and their processing were carried out by two experienced nuclear medicine physicians.Neoadjuvant treatmentAll the patients received CRT or chemotherapy. The schedule used in the CRT group was that of the CROSS protocol, consisting in the, application of a conformal 3D ALE radiotherapy technique with photons of 6−18 MV, 41 Gy/1.8 Gy in 23 daily sessions, together with the concomitant administration of weekly carboplatin and paclitaxel.The regimen used in the exclusive chemotherapy group was continuous infusion of cisplatin and 5-FU o 5-fluorouracil.Evaluation of response to treatmentBetween one and two months after the finalization of treatment, response to treatment was evaluated by 18F-FDG CT or PET/CT. The RECIST criteria were used in the radiological study and the PERCIST criteria in the metabolic study<a class="elsevierStyleCrossRef" href="#bib0055">11</a>. Response to treatment was considered when this was complete, and no response was considered when it was partial, stable disease or in the presence of progression.Evaluation of response to treatment was carried out jointly by an experienced nuclear medicine physician and a radiologist.Follow-upThe patients were evaluated every 3−6 months during the first two years of follow-up, every 6 months after the third year and annually after the fifth year. Each case underwent clinical examinations, blood analyses including the carcinoembryonic antigen (CEA) tumoral marker and radiological studies (CT with contrast). In addition, every 6 months during the first two years the patients underwent endoscopy. In some cases, an 18F-FDG PET/CT was requested on suspicion of recurrence-progression.Statistical analysisThe statistical analyses were performed with the SPSS® (IBM, New York, USA) version 19 statistical package. The time of evolution was quantified beginning from the first day of treatment. CSS was defined as the interval between the initiation of treatment and the date of death due to the neoplasia, while PFS was defined as the time interval between the initiation of treatment and the appearance of recurrence or progression.Comparison between the responders and non responders was done by the Mann-Whitney U test in the case of quantitative variables and the chi-square test for categorical variables.The most appropriate cut-off value and the area under the curve (AUC) of the metabolic parameters showing statistical significance was determined using the receiver operating characteristic curve (ROC) and application of the Youden index. The Kaplan-Meier method was used to estimate the survival curves and the Log-rank test was used to determine statistical differences among curves. A P value <0.05 was considered statisticallly signifiant.ResultsPatients, follow-up and metabolic parametersOf a total of 114 patients diagnosed with esophageal cancer referred to our department during the study period, 38 with a histological study of SCC were selected. Of this group, 2 were excluded due to death not related to cancer, 4 for presenting premature death without being able to evaluate the response to treatment and 2 for incomplete follow-up. Thus, a total of 30 patients were finally included in the study.<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a> shows the characteristics of the patients studied, the tumoral lesions and the treatments administered. Almost all the patients were men, with a mean age of 63 years. The mean tumor size was 56.4 mm; the most frequent localization was the middle third of the esophagus and the most frequent stages were II and IVB. Most of the patients underwent CRT, while 7 received chemotherapy alone and 1 received only radiotherapy.<elsevierMultimedia ident="tbl0010"></elsevierMultimedia>In regard to response to treatment, this was diagnosed by PET/CT in 11 cases and by CT in 9. Thirteen patients presented complete response. There were no significant differences on comparing the types of response with the diagostic method used (chi-square test, p = 0.08). Neither were there differences in PFS and CSS between patients classified according to the method of evaluation of response (Kaplan-Meier, p = 0.304 and p = 0.212, respectively).The mean follow-up time of the study group was 22.4 months, with 25 deaths and 22 recurrences-progressions (8 local, 4 local and lymph nodes, 4 lymph nodes, 1 regional and distant lymph nodes, 4 distant and 1 local and distant). The rates of CSS at one and 5 years were 47 and 17%, and 34 and 18%, respectively for PFS.<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a> shows the values found for the different metabolic parameters.<elsevierMultimedia ident="tbl0015"></elsevierMultimedia>Comparison between groups<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a> shows the results of the comparison between the responders and non responders in relation to different parameters. There were no significant differences in patient age, tumor localization, type of treatment administered, SUVmax, SUVmean, ratio-A or ratio-B. However, there were statistically significant differences with respect to tumor stage and size as well as MTV and TLG.<elsevierMultimedia ident="tbl0020"></elsevierMultimedia>Analysis of survival<a class="elsevierStyleCrossRef" href="#tbl0025">Table 5</a> shows the results of the ROC curve analysis and Youden index for the three last quantitative parameters, with adequate AUCs, very significant P values, greater sensitivity for TLG with a cut-off of 200.4 and greater specificity for the MTV with a cut-off of 63.6 cm3. Application of the analysis to the SUVmax and SUVmean showed non significant P values (p = 0.884 and p = 0.439, respectively).<elsevierMultimedia ident="tbl0025"></elsevierMultimedia>The Kaplan-Meier survival analysis showed significantly different PFS and CSS curves for the three parameters with values in relation to tumor size of p = 0.044 and p = 0.009 with respect to the MTV of p = 0.000 in both cases (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>) and for TLG of p = 0.024 and p = 0.007, respectively (<a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>). Likewise, significant differences were found in both survivals when comparing the curves of responders and non responders (p = 0.000).<elsevierMultimedia ident="fig0010"></elsevierMultimedia><elsevierMultimedia ident="fig0015"></elsevierMultimedia>DiscussionCancer of the esophagus is the third in frequency among malignant gastrointestinal tumors and the ninth globally. This neoplasia has a high incidence in Asia, especially in what is known as the esophageal cancer belt, a geographical area that goes from the north of Iran to the north of China in which around 80% of the tumors are SCC<a class="elsevierStyleCrossRefs" href="#bib0005">1,12</a>.The main risk factor of SCC is the increase in tobacco and alcohol consumption, the ingestion of red meat and consumption of very hot beverages. Genetic factors have also been described<a class="elsevierStyleCrossRefs" href="#bib0005">1,13</a>. It is an aggressive tumor with advanced stages at diagnosis and early recurrences even after surgical resection. The 5-year survival rate is from 16 to 32%<a class="elsevierStyleCrossRef" href="#bib0070">14</a>, similar to the range found in our group of patients.Chemotherapy or CRT followed by surgery is the standard treatment for SCC. Controlled and randomized studies have found a greater survival among patients treated with this therapeutic plan compared to the use of surgerywithout previous neoadjuvant therapy<a class="elsevierStyleCrossRef" href="#bib0020">4</a>. However, a similar survival has been described on comparing definitive CRT with response to treatment with neoadjuvant CRT followed by surgery, suggesting that definitive CRT may be a first line of treament in the case of locally advanced esophageal cancer<a class="elsevierStyleCrossRef" href="#bib0005">1</a>. In this sense, it is known that esophagectomy is associated with a high morbidity, a reduction in quality of life and mortality greater than 7% during the first months after surgery. On the other hand, patients without response to CRT may present toxicity to treatment without receiving any benefits from the treatment, local treatment failure rates above 50% having been reported<a class="elsevierStyleCrossRefs" href="#bib0005">1,5</a>.Taking all of this into account, the determination of prognostic factors at diagnosis that can predict response to treatment would allow individualizing the treatment administered and reduce costs. The metabolic parameters of PET have been evaluated as predictors in different tumors such as the lung or lymphoma<a class="elsevierStyleCrossRef" href="#bib0075">15</a>. Following the study by Fukunaga et al.<a class="elsevierStyleCrossRef" href="#bib0080">16</a> in 1998, an increasing number of publications have focused on the utility of these parameters in esophageal cancer, with diverse and sometimes contradictory results.In our case, the statistical study showed that the MTV and TLG were prognostic factors for not only the evaluation of response to treatment but also for survival, while neither the SUVmax nor the SUVmean were found to be prognostic. These results agree with those of other authors. Chen et al.<a class="elsevierStyleCrossRef" href="#bib0085">17</a> described the MTV with a cut-off value of 40 cm3 as a predictive factor of PFS and overall survival (OS) in 90 patients with irresectable SCC, finding no significant correlation with the SUVmax. This value was similar to that found in our study, although in their case it was calculated in only the primary tumor. Similar results were described by Li et al.<a class="elsevierStyleCrossRef" href="#bib0090">18</a> in 86 patients with SCC, considering the MTV and the TLG of the primary tumor and of the regional adenopathies but not the SUVmax as prognostic variables. In this previous study, the cut-off values used for the two metabolic parameters were 15.6 cm3 and 183.5, respectively. Likewise, the study by Chang et al.<a class="elsevierStyleCrossRef" href="#bib0095">19</a>, which included 44 patients with locally advanced cancer of the esophagus, reported that the MTV with a cut-off of 8.93 cm3 was a potent prognostic predictor, while the SUVmax and SUVmean did not present statistically significant values. Nonetheless, thse parameters were only determined in the primary tumor in contrast to our studyin which lymph node and distant involvement were also added. Along the same line, Liu et al.<a class="elsevierStyleCrossRef" href="#bib0100">20</a> demonstrated that the MTV with a cut-off of 16.08 cm3 acted as a prognostic factor in a study including 58 patients with SCC, without significant results for the SUV. These authors calculated the metabolic parameters in the primary tumor and the adjacent lymph nodes, excluding patients with distant metastasis. In a recent publication, Domachevsky et al.<a class="elsevierStyleCrossRef" href="#bib0045">9</a> studied 61 patients with locally advanced esophageal cancer and demonstrated that the MTV calculated based on the primary tumor and the largest adenopathy in the basal PET/CT were correlated with response to neoadjuvant treatment.The utility of volumetric parameters has been widely evaluated in other cancers. In the study of Jiménez-Ballvé et al.<a class="elsevierStyleCrossRef" href="#bib0105">21</a> including 40 patients with locally advanced breast cancer it was observed that both the MTV and the TLG were predictors of recurrence-free survival. The cut-off values calculated in the primary tumor in this study were 19.3 cm3 and 74.4, respectively.In contrast, for other authors such as Miyata et al.<a class="elsevierStyleCrossRef" href="#bib0110">22</a> and Fathinul Fikri et al.<a class="elsevierStyleCrossRef" href="#bib0115">23</a>, the pretreatment SUVmax was an independent prognostic indicater of OS, although in both studies neither the MTV nor the TLG were determined. Elimova et al.<a class="elsevierStyleCrossRef" href="#bib0120">24</a> considered that neither the SUVmax nor the TLG could predict response to teatment, with the latter parameter showing a significant association with OS. In this study the MTV was also not determined.These discrepancies of results among studies may be due to differences in the numbers of events occuring in the groups of patients (deaths, progressions) or to different inclusion criteria and evaluation. Likewise, variability among institutions in relation to the maximum glucemia level accepted, the length of fasting and the uptake of the radiopharmaceutical as well as the reconstruction methods used should be taken into account<a class="elsevierStyleCrossRef" href="#bib0125">25</a>.In the case of the SUV, it has been considered that the variability of results is due to numerous factors that can influence this parameter. It is dependent of the time of uptake, glucemia, body weight, injection technique, the calibration of the camera, the method of reonstruction used, the size of the matrix and the partial volume effect<a class="elsevierStyleCrossRef" href="#bib0130">26</a>. On the other hand, when using this parameter the significant heterogeneity of tumor uptake of the radiopharmaceutical should be taken into account and that some lesions may be constituted by neoplastic or non neoplastic components and that, essentially express the greatest intratumoral metabolic activity but not its whole metabolic activity<a class="elsevierStyleCrossRef" href="#bib0025">5</a>.In regard to the other two metabolic parameters, the development of new software work stations for processing PET/CT images has facilitated their calculation, allowing evaluation of their predictive capacity. The number of publications related to this subject suggest that these parameters are being implemented in daily clinical practice. The MTV provides metabolic and anatomical information since it reflects the volume of tumoral cells showing abnormal glucose metabolism. The TLG has been proposed as the most accurate parameters due to the fact that it considers both the SUVmean and the MTV. Elevated TLG values correspond to greater tumoral tissue glycolysis, implying cellular hypoxia<a class="elsevierStyleCrossRef" href="#bib0095">19</a>.Considering all of the above, the determination of the MTV and TLG in the PET/CT at diagnosis allows individualized treatment planning of the tumor by classifying the patients by their probability of belongiong to the group of responders or non responders. Likewise, it allows predicting the posterior evolution and the probability of patient survial since, similar to our study, previous studies have described better clinical outcomes in patients in complete response following CRT<a class="elsevierStyleCrossRef" href="#bib0135">27</a>. Patients diagnosed with SCC usually present impaired nutritional balance, with weight loss, anemia and low tolerance to invasive studies and, thus, adjustment of the treatment is of special importance<a class="elsevierStyleCrossRef" href="#bib0140">28</a>.Our study describes tumoral size and stage as predictors of response to treatment, correlating size with PFS and CSS. These findings agree with the literature which describes a direct relationsip between tumor size and local infiltraton and the presence of lymphatic involvement, conditioning the stage and the prognosis of the patient<a class="elsevierStyleCrossRef" href="#bib0145">29</a>.In addition to 18F-FDG, other PET radiopharmaceuticals have been used in esophageal cancer such as l-[3-18F]-α-methyltyrosine, for which an increase in the specificity of lymph staging has been described<a class="elsevierStyleCrossRef" href="#bib0150">30</a>. Our department only has experience with 18F-FDG.Our study has some limitations which must be considered. The group of patients was not very large compared to other previous studies. Obviously, since the study was retrospective, the diagnostic method used to evaluate response to treatment could not be controlled, and this may have led to bias in the results. Nonetheless, the statistical study did not show differences on comparing the results between PET/CT and CT. Neither were there any differences for PFS and CSS between the two groups. However, this possible bias would not compromise the results related to the survival analysis derived from the metabolic parameters determined at diagnosis.In conclusion, the MTV and TLG metabolic parameters of the 18F-FDG PET/CT study as well as tumor size have shown to be prognostic factors for response to neoadjuvant treatment, PFS and CSS in patients diagnosed with SCC in our setting. Neither the SUVmax nor the SUVmean were predictors for any of the evaluation criteria. These results may be useful to personalize patient treatment, although a larger number of cases should be analyzed to confirm these findings.FundingNone.Conflict of interestsNone." "textoCompletoSecciones" => array:1 [ "secciones" => array:11 [ 0 => array:3 [ "identificador" => "xres1709427" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Aim" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Material and methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusion" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1512006" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1709426" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Material y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusión" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1512007" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Material and methods" "secciones" => array:6 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Patients" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "PET/CT study" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Neoadjuvant treatment" ] 3 => array:2 [ "identificador" => "sec0030" "titulo" => "Evaluation of response to treatment" ] 4 => array:2 [ "identificador" => "sec0035" "titulo" => "Follow-up" ] 5 => array:2 [ "identificador" => "sec0040" "titulo" => "Statistical analysis" ] ] ] 6 => array:3 [ "identificador" => "sec0045" "titulo" => "Results" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0050" "titulo" => "Patients, follow-up and metabolic parameters" ] 1 => array:2 [ "identificador" => "sec0055" "titulo" => "Comparison between groups" ] 2 => array:2 [ "identificador" => "sec0060" "titulo" => "Analysis of survival" ] ] ] 7 => array:2 [ "identificador" => "sec0065" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0070" "titulo" => "Funding" ] 9 => array:2 [ "identificador" => "sec0075" "titulo" => "Conflict of interests" ] 10 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2021-01-14" "fechaAceptado" => "2021-03-18" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1512006" "palabras" => array:6 [ 0 => "PET/CT" 1 => "Esophageal cancer" 2 => "Squamous cell cancer" 3 => "SUV" 4 => "MTV" 5 => "TLG" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1512007" "palabras" => array:6 [ 0 => "PET/TC" 1 => "Cáncer de esófago" 2 => "Carcinoma de células escamosas" 3 => "SUV" 4 => "MTV" 5 => "TLG" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "AimTo determine the utility of [18F]FDG PET/CT quantitative parameters as prognostic factors for the response to neoadjuvant treatment, progression-free survival (PFS) and cancer-specific survival (CSS) in patients with esophageal squamous cell carcinoma (SCC). Material and methodsThirty patients (29 men) diagnosed with SCC were retrospectively evaluated over a 6-year interval. Metabolic parameters were determined: maximum SUV (SUVmax), mean SUV (SUVmed), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) from baseline PET/CT study. After treatment with chemotherapy and/or radiotherapy, response to treatment and patient survival were assessed. The comparison of parameters between groups of responders and non-responders was carried out using a Mann-Whitney U test ROC curves and the Kaplan-Meier method were used for analysis of prognostic factors and survival curves. ResultsThe average follow-up was 22.4 months, with 22 recurrence-progressions and 25 deaths. Significant differences were demonstrated between responders and non-responders with respect to tumor size, MTV and TLG. Survival analysis found significant differences for SCE and CSS depending on these three parameters. ConclusionMetabolic parameters MTV and TLG, and tumor size were prognostic factors for neoadjuvant treatment response, PFS, and CSS in patients diagnosed with SCC. Neither SUVmax nor SUVmed were predictive for any of the evaluation criteria. Results could help to personalize patient treatment." "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Aim" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Material and methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusion" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "ObjetivoDeterminar la utilidad de los parámetros cuantitativos de la PET/TC con [18F]FDG como factores pronósticos para la respuesta al tratamiento neoadyuvante, la supervivencia libre de progresión (SLP) y la supervivencia cáncer específica (SCE) en pacientes con carcinoma de células escamosas de esófago (CCE). Material y métodosSe valoraron retrospectivamente 30 pacientes (29 hombres) diagnosticados de CCE durante un intervalo de 6 años. Se determinaron los parámetros metabólicos SUV máximo (SUVmax), SUV medio (SUVmed), volumen metabólico tumoral (MTV) y glicolisis tumoral total (TLG) del estudio PET/TC al diagnóstico. Tras tratamiento con quimioterapia y/o radioterapia, se valoró la respuesta al tratamiento y la supervivencia de los pacientes. La comparación de parámetros entre grupos de respondedores y no respondedores se realizó mediante la prueba U de Mann-Whitney. Las curvas ROC y el método de Kaplan-Meier se utilizaron para el análisis de factores pronósticos y curvas de supervivencia. ResultadosEl seguimiento medio fue de 22,4 meses, produciéndose 22 recurrencias-progresiones y 25 exitus. Se demostraron diferencias significativas entre respondedores y no respondedores con respecto al tamaño tumoral, el MTV y la TLG. El análisis de supervivencia halló diferencias significativas para SCE y SLP dependiendo de estos tres parámetros. ConclusiónLos parámetros metabólicos MTV y TLG, así como el tamaño tumoral, fueron factores pronósticos para la respuesta al tratamiento neoadyuvante, la SLP y la SCE en pacientes diagnosticados de CCE. Ni el SUVmax ni el SUVmed fueron predictores para ninguno de los criterios de evaluación. Los resultados permitirían personalizar el tratamiento de los pacientes." "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Material y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusión" ] ] ] ] "NotaPie" => array:1 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "Please cite this article as: Martínez A, Infante JR, Quirós J, Rayo JI, Serrano J, Moreno M, et al. Parámetros cuantitativos de la PET/TC basal con 18F-FDG como factores pronósticos en el carcinoma de células escamosas de esófago. Rev Esp Med Nucl Imagen Mol. 2022;41:164–170." ] ] "multimedia" => array:8 [ 0 => array:8 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 2007 "Ancho" => 2917 "Tamanyo" => 480108 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0005" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "18F-FDG PET/CT: fusion image in axial, sagittal and coronal axes showing isocontour based on a SUVmax of 2.5. The study is of a 41-year-old male diagnosed with squamous cell carcinoma of the upper esophagus with left laterocervical lymph node involvement (stage IVB). The values of the metabolic parameters were SUVmax of 21.1, SUVmean of 7.3, MTV of 27.6 cm3 and TLG of 183.2. The patient present complete response to treatment, evaluated by PET/CT study. During follow-up (49 months) there were no tumoral recurrences, and the patient remains asymptomatic to date." ] ] 1 => array:8 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1184 "Ancho" => 1507 "Tamanyo" => 88162 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0010" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "Kaplan-Meier curves. Comparison of PFS according to the MTV value." ] ] 2 => array:8 [ "identificador" => "fig0015" "etiqueta" => "Figure 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 1102 "Ancho" => 1507 "Tamanyo" => 83392 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0015" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "Kaplan-Meier curves. Comparison of CSS according to the TLG value." ] ] 3 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0020" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">T category</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Tx \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">The tumor cannot be evaluated</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">T0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">No evidence of the primary tumor</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Tis \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">High grade dysplasia defined as malignant cells confined to the epithelium by the basal membrane</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">T1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">The tumor invades the lamina propia, the muscularis mucosae or submucosa</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">T1a \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">The tumor invades the lamina propia or the muscularis mucosae</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">T1b \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">The tumor invades the submucosa</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">T2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">The tumor invades the muscular propia</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">T3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">The tumor invades the adventicia</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">T4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">The tumor invades neighboring structures</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">T4a \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">The tumor invades the pleura, the pericardium, the azygous vein, the diaphragm or the peritoneum</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">T4b \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">The tumor invades other structures such as the aorta, the vertebrae or the airway</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">N category</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Nx \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">The regional lymph nodes cannot be evaluated</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">N0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">No metastasis in the regional lymph nodes</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">N1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Metastasis in 1−2 regional lymph nodes</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">N2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Metastasis in 3−6 regional lymph nodes</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">N3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Metastasis in 7 or more regional lymph nodes</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">M category</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">M0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">No distant metastasis</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">M1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Distant metastasis</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Clinical stage(cTNM)</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Tis \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">N0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">M0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">T1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">N0−1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">M0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">I \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">T2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">N0−1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">M0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">II \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">T3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">N0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">M0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">II \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">T3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">N1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">M0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">III \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">T1−3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">N2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">M0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">III \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">T4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">N0−2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">M0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">IVA \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Any T \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">N3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">M0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">IVA \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Any T \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Any N \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">M1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">IVB \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2903127.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Eighth edition of the AJCC-TNM classification." ] ] 4 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0025" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Patients</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Sex, n (%)</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Man \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">29 (96.7) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Woman \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (3.3) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Age (year), mean (range) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">63 (41−81) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Recurrence/progression \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">22 (73.3) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Muerte \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">25 (83.3) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Tumor</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Size (mm), mean (range) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">56.4 (21−110) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Localization, n (%)</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Superior \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9 (30) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Middle \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14 (46.7) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Inferior \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (23.3) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Stage, n (%)</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">II \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (33.3) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">III \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (23.3) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">IVA \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (10.1) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">IVB \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (33.3) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Type of treatment n (%)</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Chemotherapy \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (23.3) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Radiotherapy \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (3.3) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Chemoratiotherapy \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">22 (73.3) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Response to treatment n (%)</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Complete \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">13 (43.3) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Stable disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 .16.7) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Partial \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (16.7) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Progression \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (23.3) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2903124.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Characteristics of the patients, tumoral lesions and treatments administered." ] ] 5 => array:8 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0030" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "SEM: standard error of the mean.MTV in cubic cm." "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Mean ± SEM \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Range \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">SUVmax \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17.5 ± 1.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.3−31.0 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">SUVmed \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.8 ± 0.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.0−13.8 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">MTV \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">83.6 ± 13.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.9−243.1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">TLG \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">529.5 ± 93.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11.5−1966.9 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Ratio-A \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5.7 ± 0.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.2−10.2 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Ratio-B \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.5 ± 0.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.9−5.8 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2903129.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Metabolic parameters." ] ] 6 => array:8 [ "identificador" => "tbl0020" "etiqueta" => "Table 4" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0035" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "Tumor size in mm." "tablatextoimagen" => array:2 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">Responders \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">Non responders \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">n \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">n \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Localization \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.297 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Superior \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Middle \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Inferior \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Stage \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.019 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">II \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">III \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">IVA \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">IVB \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Type of treatment \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.117 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Chemotherapy \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Radiotherapy \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Chemoradiotherapy \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2903126.png" ] ] 1 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Mean \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Mean \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Age \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">64.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">61.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.385 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Tumor size \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">SUVmax \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.902 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">SUVmed \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.457 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">MTV \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">45.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">112.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.006 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">TLG \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">319.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">690.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.005 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Ratio-A \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.805 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Ratio-B \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.170 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2903125.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Comparison of different parameters between responder and non responder patients." ] ] 7 => array:8 [ "identificador" => "tbl0025" "etiqueta" => "Table 5" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0040" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "AUC: area under the curve; Sp: specificity S: sensitivity.Tumor size in mm.MTV in cubic cm." "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Parameter \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Cut-off \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">AUC (95%CI) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">S (%) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Sp (%) \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Tumor size \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">42 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.837 (0.692−0.983) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.002 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">88 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">70 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">MTV \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">63.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.792 (0.628−0.956) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.007 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">65 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">85 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">TLG \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">200.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.796 (0.625−0.968) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.006 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">94 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">62 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2903128.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Cut-off point in receiver operating characteristic curves and their significance." ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:30 [ 0 => array:3 [ "identificador" => "bib0005" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Oesophageal cancer" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:4 [ 0 => "J. 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Baseline 18F-FDG PET/CT quantitative parameters as prognostic factors in esophageal squamous cell cancer

Parámetros cuantitativos de la PET/TC basal con 18F-FDG como factores pronósticos en el carcinoma de células escamosas de esófago

A. Martíneza,

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andres.martineze@salud-juntaex.es

Corresponding author.

, J.R. Infantea, J. Quirósb, J.I. Rayoa, J. Serranoa, M. Morenoa, P. Jiméneza, A. Coboa, A. Baenaa

a Servicio de Medicina Nuclear, Hospital Universitario de Badajoz, Badajoz, Spain

b Servicio de Oncología Radioterápica, Hospital Universitario de Badajoz, Badajoz, Spain

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The collection of data on the evolution of the patients finalized in October 2020&#44; allowing a minimum follow-up of 4 years in cases in which death did not take place&#46;</p><p id="par0035" class="elsevierStylePara elsevierViewall">The inclusion criteria were&#58; a minimum age of 18 years&#44; histology compatible with SCC&#44; <span class="elsevierStyleSup">18</span>F-FDG PET&#47;CT with the diagnosis and examination prior to treatment inclusing physical examination&#44; laboratory analysis and radiological study by CT&#46; The exclusion criteria were a previous history of neoplasia&#44; the presence of a second synchronous tumor&#44; cause of death other than esophageal cancer and the impossibility of performing follow-up&#46;</p><p id="par0040" class="elsevierStylePara elsevierViewall">Clinical tumor&#44; node&#44; metastasis &#40;cTNM&#41; staging was performed using the classification described in the 8th edition of the American Joint Committe on Cancer&#44; AJCC-TNM &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">10</span></a>&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">PET&#47;CT study</span><p id="par0045" class="elsevierStylePara elsevierViewall">The metabolic study was carried out in a hybrid Discovery ST4 system &#40;General Electric&#44; Milwaukee&#44; USA&#46;&#41; within 7 weeks prior to treatment&#46; Before injection of the radiopharmaceutical&#44; all the patients had been fasting for at least 4&#8239;h with adequate hydratation and glucemia level &#60;10&#8239;mMol&#47;l&#46; An <span class="elsevierStyleSup">18</span>F-FDG dose of 3&#46;5&#8211;4&#46;5&#8239;MBq&#47;kg was injected&#46; After an interval of 60&#8239;min images were obtained with the arms above the head&#46; For the CT study neither oral nor intravenous contrast was used&#46; The CT acquisition parameters were 110&#8239;keV&#44; modulation with a maximum amperage of 80&#8239;mA and slice thickness of 3&#46;75&#8239;mm&#46; Three dimensional &#40;3D&#41; PET images were then acquired at 2&#8239;min per bed&#44; with a matrix of 128&#8239;&#215;&#8239;128 and iterative reconstruction&#46;</p><p id="par0050" class="elsevierStylePara elsevierViewall">An Advantage Volume Share 4&#44; GE Healthcare workstation was used for image processing&#44; quantifying the metabolic parameters&#44; SUVmax&#44; SUVmean&#44; MTV and TLG &#40;product between SUVmean and MTV&#41;&#46; These latter two parameters were calculated with a 3D isocontour threshold based on a SUVmax of 2&#46;5&#44; one the most commonly used in the bibliography consulted &#40;<a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>&#41;&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0055" class="elsevierStylePara elsevierViewall">In the case of involvement outside the primary tumor&#44; the MTV and TLG of each of the lesions found in the metabolic study were determined &#40;primary lesion&#44; adenopathy and&#47;or distant involvement&#41;&#44; summing all the values found&#46; In this way&#44; both parameters represent the whole of the neoplastic involvement&#46; The SUVmax and SUVmean defined for each patient was the maximum value quantified independently of their localization &#40;in or outside the esophagus&#41;&#46;</p><p id="par0060" class="elsevierStylePara elsevierViewall">Likewsie&#44; the SUVmax and SUVmean of the liver was calculated to determine the corresponding lesion&#47;liver ratios &#40;tumoral SUVmax&#47;liver SUVmax&#44; expressed as ratio-A&#44; and tumoral SUVmean&#47;liver SUVmean&#44; expressed as ratio-B&#41;&#46; Spherical volumes of interest with a diameter of 3&#8239;cm at the level of hepatic segment VII were drawn similar to what is recommended in the PERCIST evaluation&#46;</p><p id="par0065" class="elsevierStylePara elsevierViewall">Evaluation of the images and their processing were carried out by two experienced nuclear medicine physicians&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Neoadjuvant treatment</span><p id="par0070" class="elsevierStylePara elsevierViewall">All the patients received CRT or chemotherapy&#46; The schedule used in the CRT group was that of the CROSS protocol&#44; consisting in the&#44; application of a conformal 3D ALE radiotherapy technique with photons of 6&#8722;18&#8239;MV&#44; 41&#8239;Gy&#47;1&#46;8&#8239;Gy in 23 daily sessions&#44; together with the concomitant administration of weekly carboplatin and paclitaxel&#46;</p><p id="par0075" class="elsevierStylePara elsevierViewall">The regimen used in the exclusive chemotherapy group was continuous infusion of cisplatin and 5-FU o 5-fluorouracil&#46;</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Evaluation of response to treatment</span><p id="par0080" class="elsevierStylePara elsevierViewall">Between one and two months after the finalization of treatment&#44; response to treatment was evaluated by <span class="elsevierStyleSup">18</span>F-FDG CT or PET&#47;CT&#46; The RECIST criteria were used in the radiological study and the PERCIST criteria in the metabolic study<a class="elsevierStyleCrossRef" href="#bib0055"><span class="elsevierStyleSup">11</span></a>&#46; Response to treatment was considered when this was complete&#44; and no response was considered when it was partial&#44; stable disease or in the presence of progression&#46;</p><p id="par0085" class="elsevierStylePara elsevierViewall">Evaluation of response to treatment was carried out jointly by an experienced nuclear medicine physician and a radiologist&#46;</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Follow-up</span><p id="par0090" class="elsevierStylePara elsevierViewall">The patients were evaluated every 3&#8722;6 months during the first two years of follow-up&#44; every 6 months after the third year and annually after the fifth year&#46; Each case underwent clinical examinations&#44; blood analyses including the carcinoembryonic antigen &#40;CEA&#41; tumoral marker and radiological studies &#40;CT with contrast&#41;&#46; In addition&#44; every 6 months during the first two years the patients underwent endoscopy&#46; In some cases&#44; an <span class="elsevierStyleSup">18</span>F-FDG PET&#47;CT was requested on suspicion of recurrence-progression&#46;</p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Statistical analysis</span><p id="par0095" class="elsevierStylePara elsevierViewall">The statistical analyses were performed with the SPSS&#174; &#40;IBM&#44; New York&#44; USA&#41; version 19 statistical package&#46; The time of evolution was quantified beginning from the first day of treatment&#46; CSS was defined as the interval between the initiation of treatment and the date of death due to the neoplasia&#44; while PFS was defined as the time interval between the initiation of treatment and the appearance of recurrence or progression&#46;</p><p id="par0100" class="elsevierStylePara elsevierViewall">Comparison between the responders and non responders was done by the Mann-Whitney <span class="elsevierStyleItalic">U</span> test in the case of quantitative variables and the chi-square test for categorical variables&#46;</p><p id="par0105" class="elsevierStylePara elsevierViewall">The most appropriate cut-off value and the area under the curve &#40;AUC&#41; of the metabolic parameters showing statistical significance was determined using the receiver operating characteristic curve &#40;ROC&#41; and application of the Youden index&#46; The Kaplan-Meier method was used to estimate the survival curves and the Log-rank test was used to determine statistical differences among curves&#46; A <span class="elsevierStyleItalic">P</span> value &#60;0&#46;05 was considered statisticallly signifiant&#46;</p></span></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Results</span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Patients&#44; follow-up and metabolic parameters</span><p id="par0110" class="elsevierStylePara elsevierViewall">Of a total of 114 patients diagnosed with esophageal cancer referred to our department during the study period&#44; 38 with a histological study of SCC were selected&#46; Of this group&#44; 2 were excluded due to death not related to cancer&#44; 4 for presenting premature death without being able to evaluate the response to treatment and 2 for incomplete follow-up&#46; Thus&#44; a total of 30 patients were finally included in the study&#46;</p><p id="par0115" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a> shows the characteristics of the patients studied&#44; the tumoral lesions and the treatments administered&#46; Almost all the patients were men&#44; with a mean age of 63 years&#46; The mean tumor size was 56&#46;4&#8239;mm&#59; the most frequent localization was the middle third of the esophagus and the most frequent stages were II and IVB&#46; Most of the patients underwent CRT&#44; while 7 received chemotherapy alone and 1 received only radiotherapy&#46;</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0120" class="elsevierStylePara elsevierViewall">In regard to response to treatment&#44; this was diagnosed by PET&#47;CT in 11 cases and by CT in 9&#46; Thirteen patients presented complete response&#46; There were no significant differences on comparing the types of response with the diagostic method used &#40;chi-square test&#44; <span class="elsevierStyleItalic">p</span>&#8239;&#61;&#8239;0&#46;08&#41;&#46; Neither were there differences in PFS and CSS between patients classified according to the method of evaluation of response &#40;Kaplan-Meier&#44; <span class="elsevierStyleItalic">p</span>&#8239;&#61;&#8239;0&#46;304 and <span class="elsevierStyleItalic">p</span>&#8239;&#61;&#8239;0&#46;212&#44; respectively&#41;&#46;</p><p id="par0125" class="elsevierStylePara elsevierViewall">The mean follow-up time of the study group was 22&#46;4&#8239;months&#44; with 25 deaths and 22 recurrences-progressions &#40;8 local&#44; 4 local and lymph nodes&#44; 4 lymph nodes&#44; 1 regional and distant lymph nodes&#44; 4 distant and 1 local and distant&#41;&#46; The rates of CSS at one and 5 years were 47 and 17&#37;&#44; and 34 and 18&#37;&#44; respectively for PFS&#46;</p><p id="par0130" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a> shows the values found for the different metabolic parameters&#46;</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Comparison between groups</span><p id="par0135" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a> shows the results of the comparison between the responders and non responders in relation to different parameters&#46; There were no significant differences in patient age&#44; tumor localization&#44; type of treatment administered&#44; SUVmax&#44; SUVmean&#44; ratio-A or ratio-B&#46; However&#44; there were statistically significant differences with respect to tumor stage and size as well as MTV and TLG&#46;</p><elsevierMultimedia ident="tbl0020"></elsevierMultimedia></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Analysis of survival</span><p id="par0140" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0025">Table 5</a> shows the results of the ROC curve analysis and Youden index for the three last quantitative parameters&#44; with adequate AUCs&#44; very significant <span class="elsevierStyleItalic">P</span> values&#44; greater sensitivity for TLG with a cut-off of 200&#46;4 and greater specificity for the MTV with a cut-off of 63&#46;6&#8239;cm<span class="elsevierStyleSup">3</span>&#46; Application of the analysis to the SUVmax and SUVmean showed non significant <span class="elsevierStyleItalic">P</span> values &#40;<span class="elsevierStyleItalic">p</span>&#8239;&#61;&#8239;0&#46;884 and <span class="elsevierStyleItalic">p</span>&#8239;&#61;&#8239;0&#46;439&#44; respectively&#41;&#46;</p><elsevierMultimedia ident="tbl0025"></elsevierMultimedia><p id="par0145" class="elsevierStylePara elsevierViewall">The Kaplan-Meier survival analysis showed significantly different PFS and CSS curves for the three parameters with values in relation to tumor size of <span class="elsevierStyleItalic">p</span>&#8239;&#61;&#8239;0&#46;044 and p&#8239;&#61;&#8239;0&#46;009 with respect to the MTV of <span class="elsevierStyleItalic">p</span>&#8239;&#61;&#8239;0&#46;000 in both cases &#40;<a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>&#41; and for TLG of p&#8239;&#61;&#8239;0&#46;024 and <span class="elsevierStyleItalic">p</span>&#8239;&#61;&#8239;0&#46;007&#44; respectively &#40;<a class="elsevierStyleCrossRef" href="#fig0015">Fig&#46; 3</a>&#41;&#46; Likewise&#44; significant differences were found in both survivals when comparing the curves of responders and non responders &#40;<span class="elsevierStyleItalic">p</span>&#8239;&#61;&#8239;0&#46;000&#41;&#46;</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia><elsevierMultimedia ident="fig0015"></elsevierMultimedia></span></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Discussion</span><p id="par0150" class="elsevierStylePara elsevierViewall">Cancer of the esophagus is the third in frequency among malignant gastrointestinal tumors and the ninth globally&#46; This neoplasia has a high incidence in Asia&#44; especially in what is known as the esophageal cancer belt&#44; a geographical area that goes from the north of Iran to the north of China in which around 80&#37; of the tumors are SCC<a class="elsevierStyleCrossRefs" href="#bib0005"><span class="elsevierStyleSup">1&#44;12</span></a>&#46;</p><p id="par0155" class="elsevierStylePara elsevierViewall">The main risk factor of SCC is the increase in tobacco and alcohol consumption&#44; the ingestion of red meat and consumption of very hot beverages&#46; Genetic factors have also been described<a class="elsevierStyleCrossRefs" href="#bib0005"><span class="elsevierStyleSup">1&#44;13</span></a>&#46; It is an aggressive tumor with advanced stages at diagnosis and early recurrences even after surgical resection&#46; The 5-year survival rate is from 16 to 32&#37;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a>&#44; similar to the range found in our group of patients&#46;</p><p id="par0160" class="elsevierStylePara elsevierViewall">Chemotherapy or CRT followed by surgery is the standard treatment for SCC&#46; Controlled and randomized studies have found a greater survival among patients treated with this therapeutic plan compared to the use of surgerywithout previous neoadjuvant therapy<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">4</span></a>&#46; However&#44; a similar survival has been described on comparing definitive CRT with response to treatment with neoadjuvant CRT followed by surgery&#44; suggesting that definitive CRT may be a first line of treament in the case of locally advanced esophageal cancer<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a>&#46; In this sense&#44; it is known that esophagectomy is associated with a high morbidity&#44; a reduction in quality of life and mortality greater than 7&#37; during the first months after surgery&#46; On the other hand&#44; patients without response to CRT may present toxicity to treatment without receiving any benefits from the treatment&#44; local treatment failure rates above 50&#37; having been reported<a class="elsevierStyleCrossRefs" href="#bib0005"><span class="elsevierStyleSup">1&#44;5</span></a>&#46;</p><p id="par0165" class="elsevierStylePara elsevierViewall">Taking all of this into account&#44; the determination of prognostic factors at diagnosis that can predict response to treatment would allow individualizing the treatment administered and reduce costs&#46; The metabolic parameters of PET have been evaluated as predictors in different tumors such as the lung or lymphoma<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a>&#46; Following the study by Fukunaga et al&#46;<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">16</span></a> in 1998&#44; an increasing number of publications have focused on the utility of these parameters in esophageal cancer&#44; with diverse and sometimes contradictory results&#46;</p><p id="par0170" class="elsevierStylePara elsevierViewall">In our case&#44; the statistical study showed that the MTV and TLG were prognostic factors for not only the evaluation of response to treatment but also for survival&#44; while neither the SUVmax nor the SUVmean were found to be prognostic&#46; These results agree with those of other authors&#46; Chen et al&#46;<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a> described the MTV with a cut-off value of 40&#8239;cm<span class="elsevierStyleSup">3</span> as a predictive factor of PFS and overall survival &#40;OS&#41; in 90 patients with irresectable SCC&#44; finding no significant correlation with the SUVmax&#46; This value was similar to that found in our study&#44; although in their case it was calculated in only the primary tumor&#46; Similar results were described by Li et al&#46;<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> in 86 patients with SCC&#44; considering the MTV and the TLG of the primary tumor and of the regional adenopathies but not the SUVmax as prognostic variables&#46; In this previous study&#44; the cut-off values used for the two metabolic parameters were 15&#46;6&#8239;cm<span class="elsevierStyleSup">3</span> and 183&#46;5&#44; respectively&#46; Likewise&#44; the study by Chang et al&#46;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a>&#44; which included 44 patients with locally advanced cancer of the esophagus&#44; reported that the MTV with a cut-off of 8&#46;93&#8239;cm<span class="elsevierStyleSup">3</span> was a potent prognostic predictor&#44; while the SUVmax and SUVmean did not present statistically significant values&#46; Nonetheless&#44; thse parameters were only determined in the primary tumor in contrast to our studyin which lymph node and distant involvement were also added&#46; Along the same line&#44; Liu et al&#46;<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">20</span></a> demonstrated that the MTV with a cut-off of 16&#46;08&#8239;cm<span class="elsevierStyleSup">3</span> acted as a prognostic factor in a study including 58 patients with SCC&#44; without significant results for the SUV&#46; These authors calculated the metabolic parameters in the primary tumor and the adjacent lymph nodes&#44; excluding patients with distant metastasis&#46; In a recent publication&#44; Domachevsky et al&#46;<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">9</span></a> studied 61 patients with locally advanced esophageal cancer and demonstrated that the MTV calculated based on the primary tumor and the largest adenopathy in the basal PET&#47;CT were correlated with response to neoadjuvant treatment&#46;</p><p id="par0175" class="elsevierStylePara elsevierViewall">The utility of volumetric parameters has been widely evaluated in other cancers&#46; In the study of Jim&#233;nez-Ballv&#233; et al&#46;<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">21</span></a> including 40 patients with locally advanced breast cancer it was observed that both the MTV and the TLG were predictors of recurrence-free survival&#46; The cut-off values calculated in the primary tumor in this study were 19&#46;3&#8239;cm<span class="elsevierStyleSup">3</span> and 74&#46;4&#44; respectively&#46;</p><p id="par0180" class="elsevierStylePara elsevierViewall">In contrast&#44; for other authors such as Miyata et al&#46;<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">22</span></a> and Fathinul Fikri et al&#46;<a class="elsevierStyleCrossRef" href="#bib0115"><span class="elsevierStyleSup">23</span></a>&#44; the pretreatment SUVmax was an independent prognostic indicater of OS&#44; although in both studies neither the MTV nor the TLG were determined&#46; Elimova et al&#46;<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">24</span></a> considered that neither the SUVmax nor the TLG could predict response to teatment&#44; with the latter parameter showing a significant association with OS&#46; In this study the MTV was also not determined&#46;</p><p id="par0185" class="elsevierStylePara elsevierViewall">These discrepancies of results among studies may be due to differences in the numbers of events occuring in the groups of patients &#40;deaths&#44; progressions&#41; or to different inclusion criteria and evaluation&#46; Likewise&#44; variability among institutions in relation to the maximum glucemia level accepted&#44; the length of fasting and the uptake of the radiopharmaceutical as well as the reconstruction methods used should be taken into account<a class="elsevierStyleCrossRef" href="#bib0125"><span class="elsevierStyleSup">25</span></a>&#46;</p><p id="par0190" class="elsevierStylePara elsevierViewall">In the case of the SUV&#44; it has been considered that the variability of results is due to numerous factors that can influence this parameter&#46; It is dependent of the time of uptake&#44; glucemia&#44; body weight&#44; injection technique&#44; the calibration of the camera&#44; the method of reonstruction used&#44; the size of the matrix and the partial volume effect<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">26</span></a>&#46; On the other hand&#44; when using this parameter the significant heterogeneity of tumor uptake of the radiopharmaceutical should be taken into account and that some lesions may be constituted by neoplastic or non neoplastic components and that&#44; essentially express the greatest intratumoral metabolic activity but not its whole metabolic activity<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a>&#46;</p><p id="par0195" class="elsevierStylePara elsevierViewall">In regard to the other two metabolic parameters&#44; the development of new software work stations for processing PET&#47;CT images has facilitated their calculation&#44; allowing evaluation of their predictive capacity&#46; The number of publications related to this subject suggest that these parameters are being implemented in daily clinical practice&#46; The MTV provides metabolic and anatomical information since it reflects the volume of tumoral cells showing abnormal glucose metabolism&#46; The TLG has been proposed as the most accurate parameters due to the fact that it considers both the SUVmean and the MTV&#46; Elevated TLG values correspond to greater tumoral tissue glycolysis&#44; implying cellular hypoxia<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a>&#46;</p><p id="par0200" class="elsevierStylePara elsevierViewall">Considering all of the above&#44; the determination of the MTV and TLG in the PET&#47;CT at diagnosis allows individualized treatment planning of the tumor by classifying the patients by their probability of belongiong to the group of responders or non responders&#46; Likewise&#44; it allows predicting the posterior evolution and the probability of patient survial since&#44; similar to our study&#44; previous studies have described better clinical outcomes in patients in complete response following CRT<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">27</span></a>&#46; Patients diagnosed with SCC usually present impaired nutritional balance&#44; with weight loss&#44; anemia and low tolerance to invasive studies and&#44; thus&#44; adjustment of the treatment is of special importance<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">28</span></a>&#46;</p><p id="par0205" class="elsevierStylePara elsevierViewall">Our study describes tumoral size and stage as predictors of response to treatment&#44; correlating size with PFS and CSS&#46; These findings agree with the literature which describes a direct relationsip between tumor size and local infiltraton and the presence of lymphatic involvement&#44; conditioning the stage and the prognosis of the patient<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">29</span></a>&#46;</p><p id="par0210" class="elsevierStylePara elsevierViewall">In addition to <span class="elsevierStyleSup">18</span>F-FDG&#44; other PET radiopharmaceuticals have been used in esophageal cancer such as <span class="elsevierStyleSmallCaps">l</span>-&#91;3-<span class="elsevierStyleSup">18</span>F&#93;-&#945;-methyltyrosine&#44; for which an increase in the specificity of lymph staging has been described<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">30</span></a>&#46; Our department only has experience with <span class="elsevierStyleSup">18</span>F-FDG&#46;</p><p id="par0215" class="elsevierStylePara elsevierViewall">Our study has some limitations which must be considered&#46; The group of patients was not very large compared to other previous studies&#46; Obviously&#44; since the study was retrospective&#44; the diagnostic method used to evaluate response to treatment could not be controlled&#44; and this may have led to bias in the results&#46; Nonetheless&#44; the statistical study did not show differences on comparing the results between PET&#47;CT and CT&#46; Neither were there any differences for PFS and CSS between the two groups&#46; However&#44; this possible bias would not compromise the results related to the survival analysis derived from the metabolic parameters determined at diagnosis&#46;</p><p id="par0220" class="elsevierStylePara elsevierViewall">In conclusion&#44; the MTV and TLG metabolic parameters of the <span class="elsevierStyleSup">18</span>F-FDG PET&#47;CT study as well as tumor size have shown to be prognostic factors for response to neoadjuvant treatment&#44; PFS and CSS in patients diagnosed with SCC in our setting&#46; Neither the SUVmax nor the SUVmean were predictors for any of the evaluation criteria&#46; These results may be useful to personalize patient treatment&#44; although a larger number of cases should be analyzed to confirm these findings&#46;</p></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Funding</span><p id="par0225" class="elsevierStylePara elsevierViewall">None&#46;</p></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Conflict of interests</span><p id="par0230" class="elsevierStylePara elsevierViewall">None&#46;</p></span></span>"
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              "identificador" => "sec0060"
              "titulo" => "Analysis of survival"
            ]
          ]
        ]
        7 => array:2 [
          "identificador" => "sec0065"
          "titulo" => "Discussion"
        ]
        8 => array:2 [
          "identificador" => "sec0070"
          "titulo" => "Funding"
        ]
        9 => array:2 [
          "identificador" => "sec0075"
          "titulo" => "Conflict of interests"
        ]
        10 => array:1 [
          "titulo" => "References"
        ]
      ]
    ]
    "pdfFichero" => "main.pdf"
    "tienePdf" => true
    "fechaRecibido" => "2021-01-14"
    "fechaAceptado" => "2021-03-18"
    "PalabrasClave" => array:2 [
      "en" => array:1 [
        0 => array:4 [
          "clase" => "keyword"
          "titulo" => "Keywords"
          "identificador" => "xpalclavsec1512006"
          "palabras" => array:6 [
            0 => "PET&#47;CT"
            1 => "Esophageal cancer"
            2 => "Squamous cell cancer"
            3 => "SUV"
            4 => "MTV"
            5 => "TLG"
          ]
        ]
      ]
      "es" => array:1 [
        0 => array:4 [
          "clase" => "keyword"
          "titulo" => "Palabras clave"
          "identificador" => "xpalclavsec1512007"
          "palabras" => array:6 [
            0 => "PET&#47;TC"
            1 => "C&#225;ncer de es&#243;fago"
            2 => "Carcinoma de c&#233;lulas escamosas"
            3 => "SUV"
            4 => "MTV"
            5 => "TLG"
          ]
        ]
      ]
    ]
    "tieneResumen" => true
    "resumen" => array:2 [
      "en" => array:3 [
        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Aim</span><p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">To determine the utility of &#91;<span class="elsevierStyleSup">18</span>F&#93;FDG PET&#47;CT quantitative parameters as prognostic factors for the response to neoadjuvant treatment&#44; progression-free survival &#40;PFS&#41; and cancer-specific survival &#40;CSS&#41; in patients with esophageal squamous cell carcinoma &#40;SCC&#41;&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Material and methods</span><p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">Thirty patients &#40;29 men&#41; diagnosed with SCC were retrospectively evaluated over a 6-year interval&#46; Metabolic parameters were determined&#58; maximum SUV &#40;SUVmax&#41;&#44; mean SUV &#40;SUVmed&#41;&#44; metabolic tumor volume &#40;MTV&#41; and total lesion glycolysis &#40;TLG&#41; from baseline PET&#47;CT study&#46; After treatment with chemotherapy and&#47;or radiotherapy&#44; response to treatment and patient survival were assessed&#46; The comparison of parameters between groups of responders and non-responders was carried out using a Mann-Whitney <span class="elsevierStyleItalic">U</span> test ROC curves and the Kaplan-Meier method were used for analysis of prognostic factors and survival curves&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">The average follow-up was 22&#46;4 months&#44; with 22 recurrence-progressions and 25 deaths&#46; Significant differences were demonstrated between responders and non-responders with respect to tumor size&#44; MTV and TLG&#46; Survival analysis found significant differences for SCE and CSS depending on these three parameters&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusion</span><p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">Metabolic parameters MTV and TLG&#44; and tumor size were prognostic factors for neoadjuvant treatment response&#44; PFS&#44; and CSS in patients diagnosed with SCC&#46; Neither SUVmax nor SUVmed were predictive for any of the evaluation criteria&#46; Results could help to personalize patient treatment&#46;</p></span>"
        "secciones" => array:4 [
          0 => array:2 [
            "identificador" => "abst0005"
            "titulo" => "Aim"
          ]
          1 => array:2 [
            "identificador" => "abst0010"
            "titulo" => "Material and methods"
          ]
          2 => array:2 [
            "identificador" => "abst0015"
            "titulo" => "Results"
          ]
          3 => array:2 [
            "identificador" => "abst0020"
            "titulo" => "Conclusion"
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      ]
      "es" => array:3 [
        "titulo" => "Resumen"
        "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Objetivo</span><p id="spar0095" class="elsevierStyleSimplePara elsevierViewall">Determinar la utilidad de los par&#225;metros cuantitativos de la PET&#47;TC con &#91;<span class="elsevierStyleSup">18</span>F&#93;FDG como factores pron&#243;sticos para la respuesta al tratamiento neoadyuvante&#44; la supervivencia libre de progresi&#243;n &#40;SLP&#41; y la supervivencia c&#225;ncer espec&#237;fica &#40;SCE&#41; en pacientes con carcinoma de c&#233;lulas escamosas de es&#243;fago &#40;CCE&#41;&#46;</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Material y m&#233;todos</span><p id="spar0100" class="elsevierStyleSimplePara elsevierViewall">Se valoraron retrospectivamente 30 pacientes &#40;29 hombres&#41; diagnosticados de CCE durante un intervalo de 6 a&#241;os&#46; Se determinaron los par&#225;metros metab&#243;licos SUV m&#225;ximo &#40;SUVmax&#41;&#44; SUV medio &#40;SUVmed&#41;&#44; volumen metab&#243;lico tumoral &#40;MTV&#41; y glicolisis tumoral total &#40;TLG&#41; del estudio PET&#47;TC al diagn&#243;stico&#46; Tras tratamiento con quimioterapia y&#47;o radioterapia&#44; se valor&#243; la respuesta al tratamiento y la supervivencia de los pacientes&#46; La comparaci&#243;n de par&#225;metros entre grupos de respondedores y no respondedores se realiz&#243; mediante la prueba U de Mann-Whitney&#46; Las curvas ROC y el m&#233;todo de Kaplan-Meier se utilizaron para el an&#225;lisis de factores pron&#243;sticos y curvas de supervivencia&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0105" class="elsevierStyleSimplePara elsevierViewall">El seguimiento medio fue de 22&#44;4 meses&#44; produci&#233;ndose 22 recurrencias-progresiones y 25 exitus&#46; Se demostraron diferencias significativas entre respondedores y no respondedores con respecto al tama&#241;o tumoral&#44; el MTV y la TLG&#46; El an&#225;lisis de supervivencia hall&#243; diferencias significativas para SCE y SLP dependiendo de estos tres par&#225;metros&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusi&#243;n</span><p id="spar0110" class="elsevierStyleSimplePara elsevierViewall">Los par&#225;metros metab&#243;licos MTV y TLG&#44; as&#237; como el tama&#241;o tumoral&#44; fueron factores pron&#243;sticos para la respuesta al tratamiento neoadyuvante&#44; la SLP y la SCE en pacientes diagnosticados de CCE&#46; Ni el SUVmax ni el SUVmed fueron predictores para ninguno de los criterios de evaluaci&#243;n&#46; Los resultados permitir&#237;an personalizar el tratamiento de los pacientes&#46;</p></span>"
        "secciones" => array:4 [
          0 => array:2 [
            "identificador" => "abst0025"
            "titulo" => "Objetivo"
          ]
          1 => array:2 [
            "identificador" => "abst0030"
            "titulo" => "Material y m&#233;todos"
          ]
          2 => array:2 [
            "identificador" => "abst0035"
            "titulo" => "Resultados"
          ]
          3 => array:2 [
            "identificador" => "abst0040"
            "titulo" => "Conclusi&#243;n"
          ]
        ]
      ]
    ]
    "NotaPie" => array:1 [
      0 => array:2 [
        "etiqueta" => "&#9734;"
        "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Please cite this article as&#58; Mart&#237;nez A&#44; Infante JR&#44; Quir&#243;s J&#44; Rayo JI&#44; Serrano J&#44; Moreno M&#44; et al&#46; Par&#225;metros cuantitativos de la PET&#47;TC basal con <span class="elsevierStyleSup">18</span>F-FDG como factores pron&#243;sticos en el carcinoma de c&#233;lulas escamosas de es&#243;fago&#46; Rev Esp Med Nucl Imagen Mol&#46; 2022&#59;41&#58;164&#8211;170&#46;</p>"
      ]
    ]
    "multimedia" => array:8 [
      0 => array:8 [
        "identificador" => "fig0005"
        "etiqueta" => "Figure 1"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "figura" => array:1 [
          0 => array:4 [
            "imagen" => "gr1.jpeg"
            "Alto" => 2007
            "Ancho" => 2917
            "Tamanyo" => 480108
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        ]
        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "at0005"
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          ]
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        "descripcion" => array:1 [
          "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleSup">18</span>F-FDG PET&#47;CT&#58; fusion image in axial&#44; sagittal and coronal axes showing isocontour based on a SUVmax of 2&#46;5&#46; The study is of a 41-year-old male diagnosed with squamous cell carcinoma of the upper esophagus with left laterocervical lymph node involvement &#40;stage IVB&#41;&#46; The values of the metabolic parameters were SUVmax of 21&#46;1&#44; SUVmean of 7&#46;3&#44; MTV of 27&#46;6&#8239;cm<span class="elsevierStyleSup">3</span> and TLG of 183&#46;2&#46; The patient present complete response to treatment&#44; evaluated by PET&#47;CT study&#46; During follow-up &#40;49 months&#41; there were no tumoral recurrences&#44; and the patient remains asymptomatic to date&#46;</p>"
        ]
      ]
      1 => array:8 [
        "identificador" => "fig0010"
        "etiqueta" => "Figure 2"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "figura" => array:1 [
          0 => array:4 [
            "imagen" => "gr2.jpeg"
            "Alto" => 1184
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        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "at0010"
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          ]
        ]
        "descripcion" => array:1 [
          "en" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Kaplan-Meier curves&#46; Comparison of PFS according to the MTV value&#46;</p>"
        ]
      ]
      2 => array:8 [
        "identificador" => "fig0015"
        "etiqueta" => "Figure 3"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "figura" => array:1 [
          0 => array:4 [
            "imagen" => "gr3.jpeg"
            "Alto" => 1102
            "Ancho" => 1507
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        ]
        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "at0015"
            "detalle" => "Figure "
            "rol" => "short"
          ]
        ]
        "descripcion" => array:1 [
          "en" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Kaplan-Meier curves&#46; Comparison of CSS according to the TLG value&#46;</p>"
        ]
      ]
      3 => array:8 [
        "identificador" => "tbl0005"
        "etiqueta" => "Table 1"
        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "at0020"
            "detalle" => "Table "
            "rol" => "short"
          ]
        ]
        "tabla" => array:1 [
          "tablatextoimagen" => array:1 [
            0 => array:2 [
              "tabla" => array:1 [
                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " colspan="4" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">T category</span></td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Tx&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">The tumor cannot be evaluated</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>T0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">No evidence of the primary tumor</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Tis&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">High grade dysplasia defined as malignant cells confined to the epithelium by the basal membrane</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>T1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">The tumor invades the lamina propia&#44; the muscularis mucosae or submucosa</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>T1a&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">The tumor invades the lamina propia or the muscularis mucosae</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>T1b&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">The tumor invades the submucosa</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>T2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">The tumor invades the muscular propia</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>T3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">The tumor invades the adventicia</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>T4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">The tumor invades neighboring structures</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>T4a&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">The tumor invades the pleura&#44; the pericardium&#44; the azygous vein&#44; the diaphragm or the peritoneum</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>T4b&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">The tumor invades other structures such as the aorta&#44; the vertebrae or the airway</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " colspan="4" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " colspan="4" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">N category</span></td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Nx&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">The regional lymph nodes cannot be evaluated</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>N0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">No metastasis in the regional lymph nodes</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>N1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Metastasis in 1&#8722;2 regional lymph nodes</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>N2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Metastasis in 3&#8722;6 regional lymph nodes</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>N3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="3" align="left" valign="\n
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                  \t\t\t\t">Metastasis in 7 or more regional lymph nodes</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">No distant metastasis</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t  " colspan="3" align="left" valign="\n
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                  \t\t\t\t">Distant metastasis</td></tr><tr title="table-row"><td class="td-with-role" title="\n
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                  \t\t\t\t"><span class="elsevierStyleItalic">Clinical stage&#40;cTNM&#41;</span></td></tr><tr title="table-row"><td class="td-with-role" title="\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">N0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>T1&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">N0&#8722;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">I&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>T2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">N0&#8722;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">II&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>T3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">N0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">II&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>T3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">N1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">III&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>T1&#8722;3&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">N2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">III&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>T4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">N0&#8722;2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">IVA&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Any T&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">N3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">IVA&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Any T&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Any N&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">M1&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
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                  """
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                  \t\t\t\t">29 &#40;96&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Age &#40;year&#41;&#44; mean &#40;range&#41;</span>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Localization&#44; n &#40;&#37;&#41;</span></td></tr><tr title="table-row"><td class="td-with-role" title="\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Superior&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Inferior&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">7 &#40;23&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Stage&#44; n &#40;&#37;&#41;</span></td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">10 &#40;33&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>III&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">7 &#40;23&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">3 &#40;10&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>IVB&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">10 &#40;33&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleBold">Type of treatment n &#40;&#37;&#41;</span></td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t"><span class="elsevierStyleItalic"><span class="elsevierStyleHsp" style=""></span>Chemotherapy</span>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">1 &#40;3&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic"><span class="elsevierStyleHsp" style=""></span>Chemoratiotherapy</span>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">22 &#40;73&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">13 &#40;43&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">5 &#40;16&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;297&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Superior&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Middle&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">7&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Inferior&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>IVB&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Chemotherapy&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Radiotherapy&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Chemoradiotherapy&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
              "imagenFichero" => array:1 [
                0 => "xTab2903126.png"
              ]
            ]
            1 => array:2 [
              "tabla" => array:1 [
                0 => """
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                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Mean&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
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                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Tumor size&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t">SUVmax&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">SUVmed&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">0&#46;457&nbsp;\t\t\t\t\t\t\n
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                          "etal" => false
                          "autores" => array:4 [
                            0 => "J&#46; Lagergren"
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                      "titulo" => "Global incidence of oesophageal cancer by histological subtype in 2012"
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                            0 => "M&#46; Arnold"
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Article information

ISSN: 22538089
Original language: English

DOI:10.1016/j.remnie.2021.07.006

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