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"documento" => "simple-article" "crossmark" => 1 "subdocumento" => "crp" "cita" => "Med Clin. 2020;154:66-7" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "en" => array:10 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Scientific letter</span>" "titulo" => "Effectiveness of outpatient treatment with intravenous iron in selected primary care patients" "tienePdf" => "en" "tieneTextoCompleto" => "en" "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "66" "paginaFinal" => "67" ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Efectividad del tratamiento ambulatorio con hierro intravenoso en pacientes seleccionados de atención primaria" ] ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Laura Rivilla Marugán, Teófilo Lorente Aznar, José Antonio García-Erce" "autores" => array:3 [ 0 => array:2 [ "nombre" => "Laura" "apellidos" => "Rivilla Marugán" ] 1 => array:2 [ "nombre" => "Teófilo" "apellidos" => "Lorente Aznar" ] 2 => array:2 [ "nombre" => "José Antonio" "apellidos" => "García-Erce" ] ] ] ] ] "idiomaDefecto" => "en" "Traduccion" => array:1 [ "es" => array:9 [ "pii" => "S0025775318305979" "doi" => "10.1016/j.medcli.2018.10.004" "estado" => "S300" "subdocumento" => "" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "idiomaDefecto" => "es" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0025775318305979?idApp=UINPBA00004N" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2387020619305297?idApp=UINPBA00004N" "url" => "/23870206/0000015400000002/v2_202001231012/S2387020619305297/v2_202001231012/en/main.assets" ] "itemAnterior" => array:19 [ "pii" => "S2387020619305479" "issn" => "23870206" "doi" => "10.1016/j.medcle.2019.04.032" "estado" => "S300" "fechaPublicacion" => "2020-01-24" "aid" => "4860" "copyright" => "Elsevier España, S.L.U." "documento" => "article" "crossmark" => 1 "subdocumento" => "sco" "cita" => "Med Clin. 2020;154:59-60" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "en" => array:10 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Editorial article</span>" "titulo" => "Automated blood pressure measurement in consultation" "tienePdf" => "en" "tieneTextoCompleto" => "en" "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "59" "paginaFinal" => "60" ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Medicion automatizada de presión arterial en consulta" ] ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Nicolás Roberto Robles, Juan Francisco Sánchez Muñoz-Torrero" "autores" => array:2 [ 0 => array:2 [ "nombre" => "Nicolás Roberto" "apellidos" => "Robles" ] 1 => array:2 [ "nombre" => "Juan Francisco" "apellidos" => "Sánchez Muñoz-Torrero" ] ] ] ] ] "idiomaDefecto" => "en" "Traduccion" => array:1 [ "es" => array:9 [ "pii" => "S0025775319303033" "doi" => "10.1016/j.medcli.2019.04.009" "estado" => "S300" "subdocumento" => "" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "idiomaDefecto" => "es" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0025775319303033?idApp=UINPBA00004N" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2387020619305479?idApp=UINPBA00004N" "url" => "/23870206/0000015400000002/v2_202001231012/S2387020619305479/v2_202001231012/en/main.assets" ] "en" => array:21 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Review</span>" "titulo" => "Whole body FDG-PET/CT for the assessment of bone marrow infiltration in patients with newly diagnosed lymphoma" "tieneTextoCompleto" => true "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "61" "paginaFinal" => "65" ] ] "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "Wang Xiao-Xue, Huang Xinyue, Zhang Lijun" "autores" => array:3 [ 0 => array:3 [ "nombre" => "Wang" "apellidos" => "Xiao-Xue" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">1</span>" "identificador" => "fn0005" ] ] ] 1 => array:3 [ "nombre" => "Huang" "apellidos" => "Xinyue" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">1</span>" "identificador" => "fn0005" ] ] ] 2 => array:4 [ "nombre" => "Zhang" "apellidos" => "Lijun" "email" => array:1 [ 0 => "lzhang202003@163.com" ] "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">*</span>" "identificador" => "cor0005" ] ] ] ] "afiliaciones" => array:1 [ 0 => array:2 [ "entidad" => "Department of Hematology, the First Hospital, China Medical University, Shenyang 110001, China" "identificador" => "aff0005" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "FDG-PET/TC de cuerpo entero para evaluar la infiltración de la médula ósea en pacientes con linfoma de nuevo diagnóstico" ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Lymphoma is a common malignant tumor origin from the lymphatic hematopoietic system. It is usually accompanied by bone marrow infiltration thus affecting the Ann Arbor staging. Therefore, the evaluation of lymphoma bone marrow infiltration is particularly important. Bone marrow biopsy is the most direct method of detecting lymphoma infiltration, but it is an invasive procedure which is accompanied by several complications such as pain and hemorrhage.<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">1</span></a> On the other hand, PET–CT is a non-invasive examination that can comprehensively evaluate the state of bone marrow with extremely high sensitivity in detecting bone marrow infiltration of lymphoma.<a class="elsevierStyleCrossRefs" href="#bib0230"><span class="elsevierStyleSup">2–4</span></a> Therefore, many clinical institutions put forward the idea of replacing bone marrow biopsy with PET–CT as the first choice in the diagnosing of lymphoma bone marrow infiltration.</p><p id="par0010" class="elsevierStylePara elsevierViewall">Meanwhile, many other researchers share different opinions. Relevant research indicates that PET–CT cannot replace bone biopsy in the diagnosing of bone marrow infiltration in DLBCL and FL,<a class="elsevierStyleCrossRef" href="#bib0245"><span class="elsevierStyleSup">5</span></a> and the accuracy of PET–CT in detecting bone marrow infiltration is dissatisfactory.<a class="elsevierStyleCrossRefs" href="#bib0250"><span class="elsevierStyleSup">6,7</span></a> Some researchers came to the conclusion that the clinical significance of diffuse infiltration of bone marrow in PET–CT remains uncertain because the high uptake focus of FDG in PET–CT cannot represent the bone marrow infiltration very well.<a class="elsevierStyleCrossRefs" href="#bib0260"><span class="elsevierStyleSup">8,9</span></a> It is not objective to do a comparison between whole body PET–CT and one sample point bone marrow biopsy.<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">10</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">At this moment, there is no clear international guideline between the indications of PET–CT and bone marrow biopsy. The aim of this research is to discuss the significance of PET–CT in detecting lymphoma bone marrow infiltration and clinical staging.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Data and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Inclusion criteria and exclusion criteria of patients</span><p id="par0020" class="elsevierStylePara elsevierViewall">Inclusion criteria includes: specific histological type; accepted PET–CT and bone marrow biopsy before treatment; the interval between PET–CT and bone marrow biopsy is less than 2 weeks; detailed and believable clinical information.</p><p id="par0025" class="elsevierStylePara elsevierViewall">Exclusion criteria includes: undefined histological type; accepted PET–CT and bone marrow biopsy after treatment; the interval between PET–CT and bone marrow biopsy is more than 2 weeks; missing or suspicious clinical information.</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Data collection</span><p id="par0030" class="elsevierStylePara elsevierViewall">Collected clinical information includes name, age, sex, pathological type, specific PET–CT description, bone marrow biopsy report, serum LDH level, etc. Patients were categorized based on the Ann Arbor Staging Criteria. Patients are then scored based on the IPI index.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Methods</span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">PET–CT image collection and analysis</span><p id="par0035" class="elsevierStylePara elsevierViewall">Patients were imaged with equipment MCT31067. After a 4-h fasting period, patients were intravenous injected with imaging agent and rested for 1<span class="elsevierStyleHsp" style=""></span>h before CT was performed. After attenuation correction and iterative reconstruction, multifaceted and multi-piece PET imaging was performed and fused with CT images. Grayscale was used to compare the imaging agent uptake level of liver and bone marrow. If a high-uptake focus in bone marrow was observed and the uptake level of the focus was higher than liver (or the mean SUV of bone marrow was higher than 2.7), the patient was defined abnormal bone marrow glucose metabolism. If no high-uptake focus in bone marrow was observed and the mean uptake level of bone marrow was lower than liver (or lower than 1.7), the patient was defined normal bone marrow glucose metabolism. We acquired the SUVmax of the bone marrow focuses in patients with abnormal bone glucose metabolism.</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Bone marrow biopsy and pathological analysis</span><p id="par0040" class="elsevierStylePara elsevierViewall">Unilateral iliac crest biopsies were performed before treatment. BMB specimens were evaluated morphologically by hematopathologists. Immunohistochemistry of the bone marrow were carried out to determine the immunophenotype of the lymphoma and to quantify marrow involvement.</p></span></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Statistical analysis</span><p id="par0045" class="elsevierStylePara elsevierViewall">We used SPSS 19.0 to analyze continuous variables with non-parametric tests and grouping variables with Chi-square test or Fisher's exact test.</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">General data</span><p id="par0050" class="elsevierStylePara elsevierViewall">Our research included 153 patients who were diagnosed with lymphoma in the First Affiliated Hospital of China Medical University between September 2016 and October 2017. The basic information of the patients can be found in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>.</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Consistency analysis of bone marrow biopsy and PET–CT</span><p id="par0055" class="elsevierStylePara elsevierViewall">Among the 153 patients, 42 patients were reported bone marrow infiltration by PET–CT (27.5%), 35 patients were reported bone marrow infiltration by bone marrow biopsy (22.9%). Setting bone marrow biopsy as golden standard, the sensitivity, specificity and accuracy of PET–CT in detecting bone marrow infiltration are 54.3%, 80.5% and 74.5% respectively (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>).</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Correlation analysis of bone marrow biopsy and PET–CT in various pathological types of lymphoma</span><p id="par0060" class="elsevierStylePara elsevierViewall">Setting bone marrow biopsy as golden standard, we analyzed the sensitivity, specificity and accuracy of PET–CT in detecting bone marrow infiltration of different pathological types of lymphoma. The sensitivity of PET–CT is 0%, specificity and accuracy are both 46.7% in HL patients due to no bone marrow infiltration detection by bone marrow biopsy. In aggressive B-cell lymphoma (DLBCL, HG-BL) and MZL, PET–CT results of bone marrow infiltration showed high accuracy of 88.1% and 83.3% respectively. In other pathological types, PET–CT showed lower consistency with bone marrow biopsy. The median value of SUVmax in the patients detected bone marrow infiltration by BMB was significant higher than patients with BMB negative results among subgroups of aggressive B-cell lymphoma, MZL and T-NHL (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>). Detailed information for each histological subgroups can be found in supplementary Table 1.</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia></span></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Discussion</span><p id="par0065" class="elsevierStylePara elsevierViewall">Bone marrow biopsy and PET–CT are two kinds of common examinations in detecting bone marrow infiltration of lymphoma. The former is an invasive examination which has high true positive rate (sensitivity) and false negative rate (rate of missed diagnosis). The latter is a noninvasive examination which has high true negative rate (specificity) and false positive rate (misdiagnosis rate). Consequently, the clinical value of bone marrow biopsy and PET–CT needed to be reevaluated.</p><p id="par0070" class="elsevierStylePara elsevierViewall">Lymphoma is a common malignant proliferative disease in which bone marrow infiltration may alters Ann Arbor staging of patients, and thus affects the prognosis of the disease. Therefore, the evaluation of lymphoma bone marrow infiltration is particularly important.<a class="elsevierStyleCrossRefs" href="#bib0235"><span class="elsevierStyleSup">3,4,11</span></a> In our research, twenty patients from the Ann Arbor stage directed by PET–CT differ from the Ann Arbor stage directed by bone marrow biopsy. Among them, 13 patients were upgraded by PET–CT and 7 patients were downgraded. Except for the 8 patients with HL, the change of stage did not affect the clinical treatment of other types of lymphoma which is similar to related literature reports. Also, as expected, The SUVmax value of bone marrow in PET–CT showed significant correlation with bone marrow infiltration among patients with aggressive B-cell lymphoma and T-NHL (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05), which may be associated with a highly aggressive nature of the disease.<a class="elsevierStyleCrossRefs" href="#bib0280"><span class="elsevierStyleSup">12,13</span></a></p><p id="par0075" class="elsevierStylePara elsevierViewall">There are several recent research that have discussed the clinical status of PET–CT in detecting bone marrow infiltration of lymphoma with different pathological types, however, no unified conclusion has been drawn to guide the clinic so far.</p><p id="par0080" class="elsevierStylePara elsevierViewall">For patients with HL, most investigators put forward that PET–CT is very precise in detecting bone marrow infiltration thus may replace bone marrow biopsy as the preferred examination.<a class="elsevierStyleCrossRefs" href="#bib0290"><span class="elsevierStyleSup">14,15</span></a> As for HL, Ujjani et al. reported that PET–CT detected over 90% bone marrow infiltration including the ones escaped from bone marrow biopsy.<a class="elsevierStyleCrossRefs" href="#bib0300"><span class="elsevierStyleSup">16–18</span></a> Subocz et al. believed that PET–CT is the most valuable imagological examination in lymphoma, and may even replace bone marrow biopsy now and then.<a class="elsevierStyleCrossRef" href="#bib0315"><span class="elsevierStyleSup">19</span></a> Chen-Liang et al. recommended PET–CT as the first choice examination in detecting bone marrow infiltration of HL as well.<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">11</span></a> However, our research does not include HL which has positive bone marrow biopsy result due to rare bone marrow infiltration in early HL. Among all the 15 patients with HL, 8 had positive PET–CT results about bone marrow infiltration, thus the sensitivity of PET–CT bone marrow infiltration detection of HL is 0% and the specificity and accuracy are both 46.7%. Based on our data, it is not appropriate to take PET positivity as an unequivocal sign of BM involvement in HL, since treatment options may be changed in some of the patients in this event. Sometimes, PET–CT may be too sensitive and detect small degrees of BMI that are clinically irrelevant. It is questionable to pursue high sensitivity blindly.</p><p id="par0085" class="elsevierStylePara elsevierViewall">Some guidelines indicated that PET–CT is now recommended as the gold standard for staging DLBCL patients. Thus, biopsy is no longer required when a PET/CT scan demonstrates bone or marrow involvement indicating advanced-stage disease but is appropriate in case of negative PET–CT results.<a class="elsevierStyleCrossRef" href="#bib0320"><span class="elsevierStyleSup">20</span></a> Teagle and El Karak et al. revealed that as for DLBCL, the sensitivity and specificity of PET–CT are higher than bone marrow biopsy.<a class="elsevierStyleCrossRefs" href="#bib0300"><span class="elsevierStyleSup">16,21,22</span></a> However, low-volume involvement (<10–20%) and discordant lymphoma may be missed by PET/CT imaging.<a class="elsevierStyleCrossRef" href="#bib0335"><span class="elsevierStyleSup">23</span></a> Our study showed that the sensitivity, specificity and accuracy of PET–CT in detecting bone marrow infiltration of DLBCL were 80%, 90.0% and 88.1% respectively. As for HG-BL, Chen-Liang et al. recommended to check PET–CT first. Bone marrow biopsy is necessary only in cases where PET–CT showed no bone marrow infiltration.<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">11</span></a> The consistency of bone marrow biopsy and PET–CT is relatively convincing thus it was concluded that PET–CT can be used as a first line examination in detecting bone marrow infiltration of DLBCL and HG-BL.</p><p id="par0090" class="elsevierStylePara elsevierViewall">As for FL, PET–CT seems to be less precise in detecting bone marrow infiltration thus cannot replace bone marrow biopsy as the golden standard in clinic. According to study conducted by Gallamini et al., PET–CT can stage and evaluate the prognosis of FL precisely.<a class="elsevierStyleCrossRef" href="#bib0340"><span class="elsevierStyleSup">24</span></a> However, Ujjani and Teagle reported that the sensitivity and specificity of PET–CT in detecting bone marrow infiltration of FL are unsatisfactory.<a class="elsevierStyleCrossRefs" href="#bib0300"><span class="elsevierStyleSup">16,21</span></a> The sensitivity, specificity and accuracy of PET–CT in detecting bone marrow infiltration of FL in our research were 37.5%, 87.5% and 70.8%. The consistency of bone marrow biopsy and PET–CT is not ideal, so we believe PET–CT have less value in detecting bone marrow infiltration of FL.</p><p id="par0095" class="elsevierStylePara elsevierViewall">A recent study conducted by Koh et al.<a class="elsevierStyleCrossRef" href="#bib0345"><span class="elsevierStyleSup">25</span></a> analyzed 109 (63 PTCL and 46 NKTCL) patients. Biopsy revealed BM involvement in 35.8% of cases. Sensitivity and specificity of PET for diagnosing positive BM biopsy were 61.5% and 75.7% respectively. Despite fair correlation with BM biopsy result, PET may not replace BM biopsy in PTCL and NKTCL. However, the BM finding on PET is an independent prognostic factor, suggesting additional biological implication of PET findings. Abe et al.<a class="elsevierStyleCrossRef" href="#bib0350"><span class="elsevierStyleSup">26</span></a> revealed that PET/CT exhibited a higher sensitivity for BM involvement than BMB. Furthermore, BM assessment using PET/CT identified patients at high risk of disease progression and mortality. Shao puts forward that PET–CT is of vital importance in AITL.<a class="elsevierStyleCrossRef" href="#bib0355"><span class="elsevierStyleSup">27</span></a> The sensitivity, specificity and accuracy of PET–CT in detecting bone marrow infiltration of AITL and ALCL in our research were relatively high. Due to the fact that there was only 1 patient with bone marrow infiltration for each pathological type, we cannot draw any convincing conclusion for ALCL and AITL from our research.</p><p id="par0100" class="elsevierStylePara elsevierViewall">There is no report discussing the correlation between bone marrow biopsy and PET–CT in MCL, MALT, and MZL for the time being.</p><p id="par0105" class="elsevierStylePara elsevierViewall">Still, our research had certain limitations. First of all, our sample was not large enough so that our conclusion may not represent the total population. Secondly, the pathological types included in our research were not comprehensive enough; the distribution among each type was not well-proportioned. As a consequence, we cannot draw conclusions for each type of lymphoma. Thirdly, our sample was collected only from our own hospital, thus our conclusion has regional limitation. Lastly, this retrospective study omitted the blind method in clinical information such as PET–CT and B symptom. As a result, the information bias may affect the results of our research.</p><p id="par0110" class="elsevierStylePara elsevierViewall">PET–CT has many other functions besides diagnosing and staging of lymphoma. PET–CT can distinguish invasive lymphoma from noninvasive lymphoma.<a class="elsevierStyleCrossRefs" href="#bib0280"><span class="elsevierStyleSup">12,13,28</span></a> PET–CT is also an important evidence for differential diagnosis in many diseases.<a class="elsevierStyleCrossRefs" href="#bib0365"><span class="elsevierStyleSup">29–33</span></a> Furthermore, PET–CT can detect lymphoma infiltration in different locations.<a class="elsevierStyleCrossRefs" href="#bib0390"><span class="elsevierStyleSup">34–41</span></a></p><p id="par0115" class="elsevierStylePara elsevierViewall">In addition, a delayed PET–CT may have high clinical value.<a class="elsevierStyleCrossRefs" href="#bib0430"><span class="elsevierStyleSup">42,43</span></a> Recent studies on PET-MRI stated that the combination of PET–CT with MRI resulted in a reduction of radiation from CT, thus giving it a promising future development.<a class="elsevierStyleCrossRef" href="#bib0440"><span class="elsevierStyleSup">44</span></a> More future researches with larger sample size are needed to determine if delayed PET–CT is better than the standard PET–CT and whether PET-MRI can replace PET–CT in the evaluation of bone marrow condition without radiation.</p></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Conclusion</span><p id="par0120" class="elsevierStylePara elsevierViewall">PET–CT may be sometime useful in the diagnosis of bone marrow infiltration in lymphoma. At some point it may show influence on Ann Arbor staging of lymphoma even lead to changes of clinical treatment. However, the clinical significance of PET in the diagnosis of bone marrow infiltration remains uncertain in certain pathological types. So, PET–CT cannot replace bone marrow biopsy completely.</p></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Conflict of interest</span><p id="par0125" class="elsevierStylePara elsevierViewall">The authors declare no conflicts of interest.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:12 [ 0 => array:3 [ "identificador" => "xres1290168" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusion" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1191969" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1290167" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Antecedentes" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusión" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1191970" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Data and methods" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Inclusion criteria and exclusion criteria of patients" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Data collection" ] 2 => array:3 [ "identificador" => "sec0025" "titulo" => "Methods" "secciones" => array:2 [ 0 => array:2 [ "identificador" => "sec0030" "titulo" => "PET–CT image collection and analysis" ] 1 => array:2 [ "identificador" => "sec0035" "titulo" => "Bone marrow biopsy and pathological analysis" ] ] ] 3 => array:2 [ "identificador" => "sec0040" "titulo" => "Statistical analysis" ] ] ] 6 => array:3 [ "identificador" => "sec0045" "titulo" => "Results" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0050" "titulo" => "General data" ] 1 => array:2 [ "identificador" => "sec0055" "titulo" => "Consistency analysis of bone marrow biopsy and PET–CT" ] 2 => array:2 [ "identificador" => "sec0060" "titulo" => "Correlation analysis of bone marrow biopsy and PET–CT in various pathological types of lymphoma" ] ] ] 7 => array:2 [ "identificador" => "sec0065" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0070" "titulo" => "Conclusion" ] 9 => array:2 [ "identificador" => "sec0075" "titulo" => "Conflict of interest" ] 10 => array:2 [ "identificador" => "xack443575" "titulo" => "Acknowledgement" ] 11 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2018-12-16" "fechaAceptado" => "2019-07-18" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1191969" "palabras" => array:5 [ 0 => "Lymphoma" 1 => "PET–CT" 2 => "SUVmax" 3 => "Bone marrow infiltration" 4 => "Ann Arbor stage" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1191970" "palabras" => array:5 [ 0 => "Linfoma" 1 => "PET/TC" 2 => "SUVmáx" 3 => "Infiltración de la médula ósea" 4 => "Estadificación de Ann Arbor" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Background</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Positron emission tomography–computed tomography (PET–CT) and bone marrow biopsy are currently the common clinical examination of lymphoma infiltration. The aim of this research is to evaluate the value of PET–CT in diagnosis of bone marrow infiltration, clinical staging and pathological typing of lymphoma.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">153 cases were analyzed retrospectively to compare the consistency of PET–CT and bone marrow biopsy. We analyzed the sensitivity, accuracy and specificity of PET–CT in different clinical pathology of lymphoma.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">The PET–CT sensitivity in detecting bone marrow infiltration is 54.3% with a specificity of 80.5% and accuracy of 74.5%. In aggressive B-cell lymphoma (DLBCL, HG-BL) and MZL, PET–CT results of bone marrow infiltration showed high accuracy of 88.1% and 83.3% respectively. The median value of SUVmax in the patients detected to have bone marrow infiltration by BMB was significantly higher than patients with BMB negative results among subgroups of aggressive B-cell lymphoma, MZL and T-NHL (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>.05).</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusion</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">PET–CT is significant in detecting bone marrow infiltration in certain pathological types of lymphoma. However pathological inconsistencies still exist between bone marrow biopsy and PET–CT, thus PET–CT cannot completely replace biopsy.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusion" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Antecedentes</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">La tomografía computarizada por emisión de positrones (PET/TC) y la biopsia de médula ósea (BMB) son actualmente los exámenes clínicos comunes para valorar la infiltración linfomatosa. El objetivo de este estudio es evaluar el valor de la PET/TC en el diagnóstico de la infiltración de la médula ósea, la estadificación clínica y la tipificación patológica del linfoma.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Métodos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Se analizaron retrospectivamente 153 casos para comparar la consistencia de la PET/TC y la BMB. Analizamos la sensibilidad, la fiabilidad y la especificidad de la PET/TC en las diferentes enfermedades clínicas del linfoma.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">La sensibilidad de la PET/TC para detectar infiltración de la médula ósea es del 54,3%, con una especificidad del 80,5% y una precisión del 74,5%. En los casos de linfoma agresivo de células B (DLBCL, HG-BL) y MZL, los resultados de la PET/TC para la infiltración de la médula ósea reflejaron una alta precisión del 88,1 y 83,3%, respectivamente. El valor medio SUVmáx en los pacientes en los que se detectó infiltración de la médula ósea mediante BMB fue significativamente superior al de los pacientes con resultados negativos de BMB entre los subgrupos de linfoma agresivo de células B, MZL y T-NHL (p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0,05).</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusión</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">La PET/TC es significativa a la hora de detectar infiltración de la médula ósea en ciertos tipos patológicos de linfoma. Sin embargo, siguen existiendo inconsistencias patológicas entre la biopsia de médula ósea y la PET/TC, aunque esta técnica no puede sustituir por completo a la biopsia.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Antecedentes" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusión" ] ] ] ] "NotaPie" => array:1 [ 0 => array:3 [ "etiqueta" => "1" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Contribute equally to this work, both are considered as the first author.</p>" "identificador" => "fn0005" ] ] "apendice" => array:1 [ 0 => array:1 [ "seccion" => array:1 [ 0 => array:4 [ "apendice" => "<p id="par0140" class="elsevierStylePara elsevierViewall">The following are the supplementary data to this article:<elsevierMultimedia ident="upi0005"></elsevierMultimedia></p>" "etiqueta" => "Appendix A" "titulo" => "Supplementary data" "identificador" => "sec0085" ] ] ] ] "multimedia" => array:4 [ 0 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "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=""><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">Characteristics \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"><span class="elsevierStyleItalic">N</span> (%) \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"><span class="elsevierStyleItalic">Median age (year) [range]</span> \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">52 [19–78] \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" 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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Sex</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>Male \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">73 (47.7%) \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"><span class="elsevierStyleHsp" style=""></span>Female \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">80 (52.3%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" 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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Subtypes</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>Hodgkin's lymphoma \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">15 (9.8%) \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"><span class="elsevierStyleHsp" style=""></span>Diffuse large B cell lymphoma \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">55 (35.9%) \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"><span class="elsevierStyleHsp" style=""></span>High grade B-cell lymphoma \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 (2.6%) \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>Follicular lymphoma \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">24 (15.7%) \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"><span class="elsevierStyleHsp" style=""></span>Mantle cell lymphoma \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 (5.9%) \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"><span class="elsevierStyleHsp" style=""></span>Mucosa associated lymphoid tissue lymphoma \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 (4.6%) \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>Marginal zone lymphoma \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 (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"><span class="elsevierStyleHsp" style=""></span>Peripheral T cell lymphoma \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">15 (9.8%) \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"><span class="elsevierStyleHsp" style=""></span>NK/T cell lymphoma \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 (3.9%) \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"><span class="elsevierStyleHsp" style=""></span>Anaplastic large cell lymphoma \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 (4.6%) \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>Angioimmunoblastic T cell lymphoma \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 (3.9%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" 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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Performance score</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>0–1 \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">102 (66.7%) \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"><span class="elsevierStyleHsp" style=""></span>2–4 \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">51 (33.3%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" 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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Ann Arbor staging</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>I–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">68 (44.4%) \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>III–IV \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 (55.6%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" 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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">International Prognostic Index</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>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">87 (56.9%) \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"><span class="elsevierStyleHsp" style=""></span>3–5 \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">66 (43.1%) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2209545.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Patient characteristics.</p>" ] ] 1 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at2" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">BMB<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>bone marrow biopsy, PET–CT<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>positron emission tomography/computed tomography.</p>" "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-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">PET–CT \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 " colspan="2" align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">BMB</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">Total \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="" 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">Positive \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">Negative \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="" 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></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">Positive \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">23 \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="char" 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></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">Negative \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">95 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">111 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " 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 " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Total \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">35 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">118 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">153 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2209547.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Consistency analysis of bone marrow biopsy and PET–CT.</p>" ] ] 2 => array:8 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at3" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">BMB<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>bone marrow biopsy, HL<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>Hodgkin's lymphoma, FL<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>follicular lymphoma, MCL<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>mantle cell lymphoma, MZL<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>marginal zone lymphoma, T-NHL<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>T cell non-Hodgkin's lymphoma.</p>" "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">Pathological subtype \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">PET–CT positive \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">PET–CT negative \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">Sensitivity \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">Specificity \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">Accuracy \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">Median and range of SUVmax \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"><span class="elsevierStyleItalic">p</span> \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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="8" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">HL (N</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">=</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">15)</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>BMB positive \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="char" 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="char" 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 " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0%</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">46.7%</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">46.7%</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" 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 " rowspan="2" align="char" 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 " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>BMB negative \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="char" 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="char" 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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.9 (0–4.7) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="8" 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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="8" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Aggressive B-cell lymphoma (N</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">=</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">59)</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>BMB positive \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="char" 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="char" 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 " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">80%</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">90.0%</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">88.1%</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.4 (1.2–18.9) \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 " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0.05</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>BMB negative \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">44 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.9 (0–5.3) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="8" 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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="8" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">FL (N</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">=</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">24)</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>BMB positive \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="char" 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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">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 " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">37.5%</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">87.5%</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">70.8%</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.52 (0–3.7) \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 " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.62</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>BMB negative \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="char" 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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.44 (0–2.9) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="8" 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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="8" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">MCL (N</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">=</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">9)</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>BMB positive \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="char" 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="char" 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 " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">40%</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">50%</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">44.4%</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.49 (0–9.3) \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 " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.47</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>BMB negative \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="char" 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="char" 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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.98 (0–5.5) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="8" 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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="8" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">MZL (N</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">=</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">12)</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>BMB positive \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="char" 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="char" 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 " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">60%</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">100%</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">83.3%</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.5 (0–7.4) \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 " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0.05</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>BMB negative \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="char" 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="char" 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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.3 (0.1.6) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="8" 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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="8" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">T-NHL (N</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">=</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">34)</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>BMB positive \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="char" 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="char" 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 " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">57.1%</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">81.5%</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">76.5%</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7.8 (1.3–17.9) \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 " rowspan="2" align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0.05</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>BMB negative \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">22 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.7 (0–4.8) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2209546.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Correlation analysis of bone marrow biopsy and PET–CT in various pathological types of lymphoma.</p>" ] ] 3 => array:5 [ "identificador" => "upi0005" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => false "mostrarDisplay" => true "Ecomponente" => array:2 [ "fichero" => "mmc1.docx" "ficheroTamanyo" => 17598 ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0015" "bibliografiaReferencia" => array:44 [ 0 => array:3 [ "identificador" => "bib0225" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Procedure-related pain among adult patients with hematologic malignancies" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:5 [ 0 => "Y. 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Baxa" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.ejrad.2017.01.023" "Revista" => array:6 [ "tituloSerie" => "Eur J Radiol" "fecha" => "2017" "volumen" => "94" "paginaInicial" => "A52" "paginaFinal" => "A63" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/28132716" "web" => "Medline" ] ] ] ] ] ] ] ] ] ] ] ] "agradecimientos" => array:1 [ 0 => array:4 [ "identificador" => "xack443575" "titulo" => "Acknowledgement" "texto" => "<p id="par0130" class="elsevierStylePara elsevierViewall">This work was supported by <span class="elsevierStyleGrantSponsor" id="gs1">Demonstration of Regional Application of innovative diagnosis and treatment equipment in Liaoning Province</span> (<span class="elsevierStyleGrantNumber" refid="gs1">2017YFC0114200</span>) and the National Natural Science Foundation of China (NSFC, 81900153).</p>" "vista" => "all" ] ] ] "idiomaDefecto" => "en" "url" => "/23870206/0000015400000002/v2_202001231012/S2387020619305364/v2_202001231012/en/main.assets" "Apartado" => array:4 [ "identificador" => "44147" "tipo" => "SECCION" "en" => array:2 [ "titulo" => "Review" "idiomaDefecto" => true ] "idiomaDefecto" => "en" ] "PDF" => "https://static.elsevier.es/multimedia/23870206/0000015400000002/v2_202001231012/S2387020619305364/v2_202001231012/en/main.pdf?idApp=UINPBA00004N&text.app=https://www.elsevier.es/" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2387020619305364?idApp=UINPBA00004N" ]