18F-FDG-PET-based tumor delineation in cervical cancer: Threshold contouring and lesion volumes | Revista Española de Medicina Nuclear e Imagen Molecular

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Cortes axial (A), coronal (D) y sagital (G) de secuencia T2 TSE a nivel de la pelvis. Mismos planos de corte en las reconstrucciones PET (B, E y H) y la fusión de ambas (C, F e I). Se observa un engrosamiento parietal entre las horas 8 y 12 del recto (flechas blancas) sin evidencia de adenomegalias perirrectales; este engrosamiento presenta alta avidez por la FDG sin observarse capitación patológica más allá del recto." ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "A.A. Kohan, J.L. Vercher Conejero, M.C. Gaeta, L. Pelegrí Martinez, P.R. Ros" "autores" => array:5 [ 0 => array:2 [ "nombre" => "A.A." "apellidos" => "Kohan" ] 1 => array:2 [ "nombre" => "J.L." "apellidos" => "Vercher Conejero" ] 2 => array:2 [ "nombre" => "M.C." "apellidos" => "Gaeta" ] 3 => array:2 [ "nombre" => "L." "apellidos" => "Pelegrí Martinez" ] 4 => array:2 [ "nombre" => "P.R." 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Hounsfield unit (HU), SUVmean, and SUVmax values were measured as 29.3, 2.27, and 3.6, respectively. (c and d) Demonstrates the unenhanced CT and PET images of a 71-year-old woman with a healthy liver who has HU, SUVmean, and SUVmax values of 59, 2.43, and 3.01, respectively." ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Z. Dostbil, E. Varoğlu, M. Serdengeçti, B. Kaya, H. Önder, O. Sari" "autores" => array:6 [ 0 => array:2 [ "nombre" => "Z." "apellidos" => "Dostbil" ] 1 => array:2 [ "nombre" => "E." "apellidos" => "Varoğlu" ] 2 => array:2 [ "nombre" => "M." "apellidos" => "Serdengeçti" ] 3 => array:2 [ "nombre" => "B." "apellidos" => "Kaya" ] 4 => array:2 [ "nombre" => "H." "apellidos" => "Önder" ] 5 => array:2 [ "nombre" => "O." "apellidos" => "Sari" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2253654X12001151?idApp=UINPBA00004N" "url" => "/2253654X/0000003200000003/v1_201305061035/S2253654X12001151/v1_201305061035/en/main.assets" ] "en" => array:20 [ "idiomaDefecto" => true "cabecera" => "Original article" "titulo" => "18F-FDG-PET-based tumor delineation in cervical cancer: Threshold contouring and lesion volumes" "tieneTextoCompleto" => true "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "162" "paginaFinal" => "166" ] ] "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "F. Erlich, C. Camisão, A. Nogueira-Rodrigues, S. Altino, C.G. Ferreira, M. Mamede" "autores" => array:6 [ 0 => array:3 [ "nombre" => "F." "apellidos" => "Erlich" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 1 => array:3 [ "nombre" => "C." 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"apellidos" => "Mamede" "email" => array:1 [ 0 => "mamede.mm@gmail.com" ] "referencia" => array:3 [ 0 => array:2 [ "etiqueta" => "c" "identificador" => "aff0015" ] 1 => array:2 [ "etiqueta" => "e" "identificador" => "aff0025" ] 2 => array:2 [ "etiqueta" => "¿" "identificador" => "cor0005" ] ] ] ] "afiliaciones" => array:5 [ 0 => array:3 [ "entidad" => "Radiation Oncology Service, National Cancer Institute of Brazil, Rio de Janeiro, Brazil" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Radiology Service, National Cancer Institute of Brazil, Rio de Janeiro, Brazil" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Clinical Research Coordination, National Cancer Institute of Brazil, Rio de Janeiro, Brazil" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Nuclear Medicine Section, Samaritano Hospital, Rio de Janeiro, Brazil" "etiqueta" => "d" "identificador" => "aff0020" ] 4 => array:3 [ "entidad" => "Molecular Imaging Center, Universidade Federal Minas Gerais, Belo Horizonte, Brazil" "etiqueta" => "e" "identificador" => "aff0025" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Delineación tumoral basada en 18F-FDG-PET en el cáncer cervical: delimitación del contorno umbral y volúmenes de la lesión" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0010" "etiqueta" => "Fig. 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 928 "Ancho" => 3000 "Tamanyo" => 291460 ] ] "descripcion" => array:1 [ "en" => "Typical example of tumor segmentation showing volumes generated using MR, 2SD threshold algorithm, 40%- and 50%-fixed thresholds. Note: good agreement was observed between the MR and 2SD threshold PET-image segmentation. 40%- and 50%-fixed thresholds PET-image segmentations revealed great volume underestimation. (A) MR image segmentation used as reference volume; (B) 2SD threshold of PET-image segmentation fused on 3D CT images; (C) 40% threshold of PET image segmentation fused on 3D CT images and (D) 50% threshold of PET image segmentation fused on 3D CT images. Vol.: volume." ] ] ] "textoCompleto" => "IntroductionCervical cancer is the fifth most deadly cancer in women worldwide, being the cause of 286,451 estimated deaths in 2008.<a class="elsevierStyleCrossRef" href="#bib0005">1</a> Based on NCI's SEER Cancer Statistics Review, it was estimated that 11,270 women would be diagnosed with and 4070 women would die of cancer of the cervix uteri in 2009.<a class="elsevierStyleCrossRef" href="#bib0010">2</a> In Brazil, 18,430 new cases are estimated in 2010, with a 5-year overall survival rate of 49%.<a class="elsevierStyleCrossRef" href="#bib0015">3</a> Locally advanced disease is still the most prevalent presentation, with the standard of care being concurrent chemotherapy and radiation therapy.Historically radiation therapy planning is done using computerized tomography (CT) images. Besides CT, magnetic resonance (MR) is also very useful to show more anatomic detail, especially soft tissues. However, CT and MR only demonstrate anatomic tumor extent, and do not reflect biological tumor behavior.Fluorodeoxyglucose (FDG) labeled with fluor-18 (18F-FDG), an analog of glucose, has been used extensively to diagnose, stage, re-stage and follow up patients with cancer.<a class="elsevierStyleCrossRef" href="#bib0020">4</a>18F-FDG PET images reflect the glycolitic metabolic tumoral behavior, which is important for treatment planning. Recently, 18F-FDG PET has also been applied in several studies to the radiation therapy planning for different tumor types.<a class="elsevierStyleCrossRef" href="#bib0025">5</a> They have shown significant alterations to the gross tumor volume (GTV) delineation and consequently to the radiation therapy fields.<a class="elsevierStyleCrossRefs" href="#bib0030">6–10</a> Faria et al. showed that PET altered the contour in 18 (56%) of 32 cases of non-small-cell lung cancer compared to CT alone.<a class="elsevierStyleCrossRef" href="#bib0035">7</a> Van Loon et al. showed that incorporating 18F-FDG PET information in radiotherapy planning for patients with limited-disease small-cell lung cancer changed the treatment plan in 24% of patients compared to CT.<a class="elsevierStyleCrossRef" href="#bib0040">8</a> Grisby showed that 18F-FDG PET can be useful to target active metabolic disease and aid radiotherapy planning in cervical cancer.<a class="elsevierStyleCrossRef" href="#bib0045">9</a>Although these initial studies showed the great advantages of incorporating 18F-FDG PET into radiotherapy treatment planning, there is no consensus yet on the use of these images for target delineation. Fixed-level threshold techniques have been used to delineate GTV. These fixed-level thresholds are not always accurate when compared to CT or MR defined volumes, and depending on the level used, significant variability on GTV values has been reported.<a class="elsevierStyleCrossRefs" href="#bib0055">11,12</a> Biehl et al. showed that no single threshold delineating the PET-GTV provides accurate volume definition, compared with that provided by the CT-GTV, for the majority of NSCLCs.<a class="elsevierStyleCrossRef" href="#bib0065">13</a> In another study in patients with head and neck cancer, the authors demonstrated that PET-based tumor volumes are strongly affected by the choice of threshold level, leading to a significant dosimetric impact.<a class="elsevierStyleCrossRef" href="#bib0070">14</a>However, PET-defined tumor volumes in radiotherapy treatment planning can significantly affect the contour of the GTV due to variation in setting image signal thresholds; its incorporation can reduce considerably the inter- and intra-observer evaluations. Thus, there is no consensus yet as how the PET-images should be used to generate the GTV volumes for radiation therapy planning. The goal of this study is to evaluate a semi-automated segmentation algorithm for GTV delineation by comparing the metabolic PET-derived volumes with the anatomic MR-based volumes in cervical cancer patients. The originality of this manuscript relays on its strength to correlate well with volumes generated from MR images and its simplicity which makes it suitable for routine clinical use.Material and methodsThirty-two patients with locally advanced cervical cancer were retrospectively evaluated. This cohort was part of a phase I/II trial of erlotinib combined to cisplatin and radiation.<a class="elsevierStyleCrossRefs" href="#bib0075">15,16</a> Staging was performed with clinical examination and all of the patients had CT, MR and 18F-FDG PET/CT scans before treatment, as well as cistoscopy and rectosigmodoscopy. Locally advanced disease was defined as FIGO stage greater than IB2 and lesser than IVB. <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a> shows the demographics of our patient cohort. The study protocol was approved by our local ethics committee.<elsevierMultimedia ident="tbl0005"></elsevierMultimedia>MR examinations were performed using a 1.5T superconducting magnet (Symphony, Siemens Medical Systems, Erlangen, Germany) covering the abdomen and pelvis with identical protocol. All patients received 20ml of intravaginal gel applied via syringe. All patients fasted 4h prior to the examination. No bowel relaxants were routinely administered. The acquisition protocol consisted on the following sequences: (1) spin-echo T1-weighted axial, repetition time/echo time (TR/TE) 5.2/2.6ms, slice thickness 3–5mm, interslice gap 0, matrix 512×512; 38cm FOV; (2) fast spin-echo T2-weighted with a phased array coil in sagittal, coronal and axial planes, TR/TE 4500–5000/95–116ms, slice thickness 3mm, interslice gap 0.2mm, matrix 512×512; 25cm FOV; (3) turbo spin echo T2 with fat suppression axial, TR/TE 4500–5000/95–116mm, slice 5mm, interslice 0.2mm, matrix 512×512, 30–45cm FOV; and (4) T1-weighted spin-echo axial sequences before and after intravenous injection of gadolinium (0.1mmol/kg) TR/TE 5.2/2.6ms, slice thickness 3mm, interslice gap 0, matrix 512×512; 35cm FOV. None of the images were acquired using flat table.The patients fasted for at least 4h before the intravenous injection of 18F-FDG (783.5±102.3MBq). Serum glucose levels were measured before 18F-FDG injection. The scanning was performed ∼60min after the injection of 18F-FDG using a Biograph 2 PET/CT scanner (CT: Somatom sensation 2, PET: LSO crystal, Siemens Medical Solution, Malvern, USA) with a 162mm axial field of view. The images were obtained with the patient in the supine position from the orbital-meatal line to the proximal thighs. CT studies for attenuation correction and anatomic co-registration were performed following the administration of diluted barium oral contrast, and with the following imaging parameters: 130kV, 25mAs, 0.8s per CT rotation, and a 5.0-mm slice thickness. The CT data were reconstructed in a 512×512 matrix using a filtered backprojection algorithm. Immediately after the CT scan, emission images were obtained in a 3D mode with 3min acquisitions at each level (5–7 bed positions). The PET images were reconstructed in a 128×128 matrix using an iterative-ordered subsets expectation maximization (OSEM) algorithm (4 iterations, 8 subsets), yielding a volume of 47 slices with a voxel size of 3.37mm×3.37mm×3.37mm. None of the images were acquired using flat table.For volume delineation and measurement software developed at the National Institutes of Health (NIH) was used. MIPAV (Center of Information and Technology-CIT, NIH, Bethesda, USA) software is a medical imaging tool used for image processing, segmentation, registration, fusion, and visualization.<a class="elsevierStyleCrossRef" href="#bib0085">17</a> MIPAV is user-friendly freeware, available on the Internet and runs on several platforms (Windows, MAC, UNIX, and LINUX).Semi-automated PET-image-based main tumor GTV delineation was applied using a previous established algorithm (GTV2SD)<a class="elsevierStyleCrossRef" href="#bib0090">18</a> and 2 fixed threshold-based methods (GTV40% and GTV50%). Briefly, the user defined the voxel with the highest intensity value (Itop) within the lesion on the PET image. This intensity was set up as the maximum voxel on the threshold scale. The liver was chosen as the background region because of known adequate performance.<a class="elsevierStyleCrossRefs" href="#bib0090">18,19</a> Several liver regions of interest (ROI) were drawn in various transaxial slices, and the mean intensity and SD over all voxels in those ROIs were used for further calculation. The lower level of the threshold scale (Ibottom) was defined as a result of the difference between Itop and the sum of the mean intensity in the liver (Imean) plus 2-SD (I2SD): Ibottom=Itop−(Imean+I2SD). After defining Itop and Ibottom, the user selects a point in the lesion (the “seed point”) and a 3D threshold-based region-growing algorithm segments the lesion of interest to include only pixels between Itop and Ibottom. If a pixel's intensity falls between Itop and Ibottom, it is included in the region. Iterations stop when no more neighbors fall in the acceptable range. Afterwards, MIPAV generates the total metabolic volume of the tumor (GTV2SD). GTV40% and GTV50% were determined with 40% and 50% of the Itop, respectively. Then, volumes were compared with the GTVs generated manually using MR (GTVMR). For this purpose, T2 weighted axial images were used and the drawing was performed by a radiologist specialized in gynecological MR.For comparison between the volumes, Spearman's ρ correlation test was used in a SPSS 12.0 software (SPSS, Chicago, IL) for statistical analysis.ResultsBetween 2005 and 2008, 32 patients were eligible for analysis. There were predominant moderately differentiated cancers, with 65% of the patients classified as WHO grade II. More than a half of the patients had IIIB FIGO stage (51%). Of these, 14 patients had disease extending to the pelvic wall and 3 had hydronephrosis (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>).Tumor volume analysis is shown in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>. The GTVMR ranged from 3.3 cc to 246.7cc, reflecting the heterogeneity of the patients and very different tumor sizes. Moreover, also the range of SUVmax showed an important variation, with values ranging between 5.9 and 32.2. The mean volumes obtained with 2SD-algorithm threshold, fixed 40% and fixed 50% were 85.3cc, 16.2cc and 24.1cc, respectively.<elsevierMultimedia ident="tbl0010"></elsevierMultimedia>Spearman's correlation analysis is shown in <a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>. A good correlation was achieved between the volume obtained in MR (GTVMR) and the volumes determined as the pixel with the mean value plus 2-standard deviation of the liver intensity (GTV2SD) in the 18F-FDG PET images (ρ=0.88; p<0.001), being closer to the 45° line. Both, the mean value and the volume range were well correlated, the GTV2SD being slightly over-estimated when compared to the GTVMR. However, weaker correlation was observed with the fixed level threshold volumes (ρ=0.68 and ρ=0.71 for 40%- and 50%-threshold, respectively). <a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a> shows typical relationships between PET-GTVs (GTV2SD, GTV40% and GTV50%) with that from MR (GTVMR).<elsevierMultimedia ident="fig0005"></elsevierMultimedia><elsevierMultimedia ident="fig0010"></elsevierMultimedia>As it can be observed in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a> and <a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>, the fixed level thresholds volumes tended to underestimate the MR-volume. Observing <a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>, we can infer that for the mean MR-volume achieved in our patients, the best fit threshold volume would be between 60% and 80% (n=17). Therefore, in order to generate better PET-image volumes for radiation planning, there is a need to adjust the threshold for each patient.<elsevierMultimedia ident="fig0015"></elsevierMultimedia>DiscussionThe recent approach to cervical cancer treatment has been the use of highly conformal Intensity Modulated Radiation Therapy (IMRT) and Image-Guided Radiation Therapy (IGRT) with concomitant dose escalation to the GTVs. These highly conformal treatments are very volume dependent, and non-accurate volume delineation could lead to geographical misses, increasing the chance of treatment failure, or overestimation of GTV, leading to more acute and chronic toxicities. Furthermore, molecular imaging with 18F-FDG PET has been extensively used to delineate the GTV for radiation therapy planning. However, there is not a consensus on how the 18F-FDG PET should be used for tumor-volume delineation, because of variations due to the threshold applied.In the present study, we evaluated volumes of the main tumor generated by using a previously published algorithm (GTV2SD) in 32 patients with locally advanced cervical cancer and compared these results with those derived from MR. MR-derived tumor volumes were also compared with those obtained by using fixed level metabolic thresholds (40% and 50%). The study showed that the GTV2SD worked better than the fixed level thresholds. Thus, the method provides preliminary evidence that tumor delineation might be feasible using computer-generated metabolic measurements and that it could be used for radiotherapy planning in cervical cancer patients.18F-FDG PET is being widely used to delineate GTV in radiotherapy planning. Currently, MR images are considered the best imaging modality to delineate lesion volumes in cervical cancer. However, MR relies only on tumor morphological patterns and does not provide metabolic information, which is known to be highly desirable to define and estimate tumor burden. This is especially important when using state-of-the-art radiotherapy techniques such as IMRT and IGRT.The first report describing the use of 18F-FDG PET in radiotherapy planning was published by Kiffer et al. in 1998.<a class="elsevierStyleCrossRef" href="#bib0100">20</a> The authors reported a 26.7% difference in the treatment fields when PET was compared to CT only.<a class="elsevierStyleCrossRef" href="#bib0100">20</a> Since then, many other papers were published showing significant alterations in GTV and treatment fields with PET. In 2004, Bradley et al. proposed the term biological tumor volume (BTV) for PET-derived metabolic bulk.<a class="elsevierStyleCrossRef" href="#bib0105">21</a> However, it still remained unclear what the real accuracy was between the traditional GTV obtained with CT and MR and the new BTV obtained with molecular imaging with PET. Only few studies dealt with this question, and most of them used fixed level thresholds, usually 40% or 50% of the maximum tumor intensity. However, as shown in <a class="elsevierStyleCrossRefs" href="#fig0005">Figs. 1–3</a>, resulting GTVs could have important volume differences according to the window used for contour delineation.Hong et al., in a trial published in 2008 in esophageal cancer patients, identified that different PET-based techniques can produce significantly different tumor volumes in a large percentage of them. They also concluded that using fixed level thresholds do not produce accurate correlations between CT and PET findings and, furthermore, proposed a semi-automated algorithm that showed the best correlation, defined by the volumes determined as the pixel with the mean value plus 2-standard deviation of the liver intensity.<a class="elsevierStyleCrossRef" href="#bib0030">6</a>In the present study, PET-image volumes generated using GTV2SD algorithm correlated very well with MR-image volumes; while weaker correlations were observed when PET-image volumes were generated applying 40%- and 50%-fixed threshold levels and compared with the ones from MR. One reason might be the SUV heterogeneity within the tumor, leading to erroneous volume estimates when fixed-threshold levels are used (either 40% or 50% of Tmax). These Tmax cutoff values often underestimate the MR-derived tumor volume, as they only represent the most active areas of the tumor and not the metabolic activity over the entire tumor volume. On the other hand, the proposed algorithm, applies an individual variable to reach the cutoff value: the tumor/liver uptake ratio. By doing this, we showed that the volumes obtained by the PET images are more reliable and well correlated to those obtained by using fixed arbitrary threshold levels.Tumor volumes were not estimated from the pathological tissue samples, and thus, we were unable to study the degree of variability, between metabolic and anatomic tumor volumes in vivo. This variability could be explained in part by the inherent limitations of PET, and/or by the biological properties of the tumor itself.It is important to point out that the measurements derived from PET data using this method suffer from certain shortcomings<a class="elsevierStyleCrossRef" href="#bib0005">1</a>: the main problem is related to limiting the effect of partial volume on the lesion-to-liver ratios. These ratios are typically higher for low- and high-contrast objects.<a class="elsevierStyleCrossRef" href="#bib0010">2</a> There were no histological measurements for comparison, which are considered to be the gold standard.<a class="elsevierStyleCrossRef" href="#bib0015">3</a> Although not observed in the present study, another limitation could be related to the evaluation of lesions that are smaller than the spatial resolution of the PET system. Partial volume effect can also contribute, in part, to the less-than-perfect correlation on this scenario.<a class="elsevierStyleCrossRef" href="#bib0020">4</a> We used MR-volume as our reference for comparisons. However, MR has reasonable resolution; we assumed errors that might have interfered in our correlations.<a class="elsevierStyleCrossRef" href="#bib0025">5</a> PET- and MR-image were not acquired using flat table; however, it may not have impacted negatively on the GTV measurements.ConclusionOur study results provide preliminary evidence that metabolic tumor volume delineation is feasible using computer-generated measurements in 18F-FDG PET images. Generation of 18F-FDG PET based tumor volumes is affected by the choice of threshold level used. Metabolic tumor bulk calculated using the pixel with the mean value plus 2-standard deviations of the liver intensity (GTV2SD) correlates better with the MR-derived tumor volumes than fixed threshold-based algorithms. The method is a simple and clinically applicable approach to generate PET-derived GTV for radiation therapy planning of cervical cancer.Conflict of interestThe authors declare no conflict of interest." "textoCompletoSecciones" => array:1 [ "secciones" => array:12 [ 0 => array:2 [ "identificador" => "xres119495" "titulo" => array:5 [ 0 => "Abstract" 1 => "Objective" 2 => "Material and methods" 3 => "Results" 4 => "Conclusions" ] ] 1 => array:2 [ "identificador" => "xpalclavsec106775" "titulo" => "Keywords" ] 2 => array:2 [ "identificador" => "xres119496" "titulo" => array:5 [ 0 => "Resumen" 1 => "Objetivo" 2 => "Material y métodos" 3 => "Resultados" 4 => "Conclusiones" ] ] 3 => array:2 [ "identificador" => "xpalclavsec106776" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:2 [ "identificador" => "sec0010" "titulo" => "Material and methods" ] 6 => array:2 [ "identificador" => "sec0015" "titulo" => "Results" ] 7 => array:2 [ "identificador" => "sec0020" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0025" "titulo" => "Conclusion" ] 9 => array:2 [ "identificador" => "sec0030" "titulo" => "Conflict of interest" ] 10 => array:2 [ "identificador" => "xack37560" "titulo" => "Acknowledgment" ] 11 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2012-03-13" "fechaAceptado" => "2012-06-11" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec106775" "palabras" => array:4 [ 0 => "18F-FDG-PET" 1 => "Cervical cancer" 2 => "Gross tumor volume" 3 => "Tumor delineation" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec106776" "palabras" => array:4 [ 0 => "18F-FDG-PET" 1 => "Cáncer cervical" 2 => "Volumen tumoral grueso" 3 => "Delimitación tumoral" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:2 [ "titulo" => "Abstract" "resumen" => "ObjectiveTo evaluate a semi-automated PET-image tumor segmentation algorithm for gross tumor volume (GTV) delineation in patients with locally advanced cervical cancer. Material and methodsThirty-two patients with locally advanced cervical cancer were retrospectively evaluated. Semi-automated PET-image-based GTV delineation was applied using a previous established algorithm (GTV2SD) and 2 fixed threshold-based methods (GTV40% and GTV50%). GTV2SD was determined as the pixel with the mean value plus 2-standard deviation of the liver intensity, and GTV40% and GTV50% with 40% and 50% of the maximum tumor intensity (Tmax), respectively. The derived volumes were then compared with the GTVs generated manually using MR (GTVMR). ResultsThe mean value of GTV2SD, GTV40% and GTV50% was 85.3cc, 16.2cc and 24.1cc, respectively. Good agreement was noticed between GTV2SD and GTVMR (ρ=0.88). GTV40% and GTV50% showed weaker correlation with GTVMR (ρ=0.68 and ρ=0.71, respectively). ConclusionsThis study provides preliminary evidence that metabolic tumor volume delineation is feasible using computer-generated measurements in 18F-FDG PET images. Generation of PET-based tumor volumes is affected by the choice of threshold level used. Metabolic tumor bulk calculated using the pixel with the mean value plus 2-standard deviations of the liver intensity (GTV2SD) correlates better with the MR-derived tumor volumes. The method is a simple and clinically applicable approach to generate PET-derived GTV for radiation therapy planning of cervical cancer." ] "es" => array:2 [ "titulo" => "Resumen" "resumen" => "ObjetivoEvaluar el algoritmo de segmentación tumoral de la imagen PET semiautomatizada para delinear el volumen tumoral grueso (GTV) en pacientes con cáncer cervical localmente avanzado. Material y métodosSe evaluó retrospectivamente a 32 pacientes con cáncer cervical localmente avanzado. Se utilizó la delineación GTV basada en imagen PET semiautomatizada, utilizando un algoritmo previamente establecido (GTV2SD) y 2 métodos basados en umbrales fijos (GTV40% y GTV50%). Se calculó GTV2SD, como el píxel con el valor medio más 2 desviaciones estándar de la intensidad del hígado, y GTV40% y GTV50% con el 40% y el 50% de intensidad tumoral máxima (Tmáx), respectivamente. A continuación se compararon los volúmenes derivados con los GTV generados manualmente, utilizando RM (GTVMR). ResultadosEl valor medio de GTV2SD, GTV40% y GTV50% fue de 85,3 cc; 16,2 cc y 24,1 cc, respectivamente. Se halló una buena concordancia entre GTV2SD y GTVMR (ρ=0,88). GTV40% y GTV50% mostraron una menor correlación con GTVMR (ρ=0,68 y ρ=0,71, respectivamente). ConclusionesEste estudio prueba de modo preliminar que la delimitación del volumen tumoral metabólico es posible utilizando las mediciones generadas informáticamente en las imágenes de 18F-FDG PET. La generación de los volúmenes tumorales basados en PET se ve afectada por la elección del nivel de umbral utilizado. El grueso del tumor metabólico calculado utilizando el píxel con el valor medio más 2 desviaciones de la intensidad del hígado (GTV2SD) guarda una mejor correlación con los volúmenes tumorales derivados de RM. El método constituye un enfoque simple y clínicamente aplicable para generar el GTV derivado del PET, para la planificación de la terapia de radiación del cáncer cervical." ] ] "multimedia" => array:5 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 923 "Ancho" => 3042 "Tamanyo" => 154963 ] ] "descripcion" => array:1 [ "en" => "Spearman's correlation analyses. Note: MR: magnetic resonance." ] ] 1 => array:7 [ "identificador" => "fig0010" "etiqueta" => "Fig. 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 928 "Ancho" => 3000 "Tamanyo" => 291460 ] ] "descripcion" => array:1 [ "en" => "Typical example of tumor segmentation showing volumes generated using MR, 2SD threshold algorithm, 40%- and 50%-fixed thresholds. Note: good agreement was observed between the MR and 2SD threshold PET-image segmentation. 40%- and 50%-fixed thresholds PET-image segmentations revealed great volume underestimation. (A) MR image segmentation used as reference volume; (B) 2SD threshold of PET-image segmentation fused on 3D CT images; (C) 40% threshold of PET image segmentation fused on 3D CT images and (D) 50% threshold of PET image segmentation fused on 3D CT images. Vol.: volume." ] ] 2 => array:7 [ "identificador" => "fig0015" "etiqueta" => "Fig. 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 1502 "Ancho" => 1597 "Tamanyo" => 68446 ] ] "descripcion" => array:1 [ "en" => "Best-fit threshold for MR-volumes. Note: plotting showed the best thresholds for a perfect correlations (r=1) between PET- and MR-image tumor volume segmentations." ] ] 3 => array:7 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:2 [ "leyenda" => "Note: WHO: World Health Association; FIGO: International Federation of Gynecology and Obstetrics." "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"><td 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" style="border-bottom: 2px solid black">Factor \t\t\t\t\t\t\n \t\t\t\t</td><td 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" style="border-bottom: 2px solid black">Number (%) \t\t\t\t\t\t\n \t\t\t\t</td></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="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Patient</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">Age (years)</td></tr><tr title="table-row"><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">Median \t\t\t\t\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">54 \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 " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">28–72 \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="char" valign="\n \t\t\t\t\ttop\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">Tumor</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">Differentiation (WHO)</td></tr><tr title="table-row"><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">Grade 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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (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 " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Grade 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">21 (65%) \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 " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Grade 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">10 (32%) \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">FIGO stage group</td></tr><tr title="table-row"><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">IIA \t\t\t\t\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 (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 " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">IIB \t\t\t\t\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">11 (34%) \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 " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">IIIA \t\t\t\t\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 (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 " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">IIIB \t\t\t\t\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 (51%) \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 " 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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (3%) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab207723.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Patients and tumor characteristics." ] ] 4 => array:7 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:2 [ "leyenda" => "Note: SUVmax: maximum standardized uptake value; 2SD: 2 standard deviation algorithm." "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"><td 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" style="border-bottom: 2px solid black">Factor \t\t\t\t\t\t\n \t\t\t\t</td><td 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" style="border-bottom: 2px solid black">Value (range) \t\t\t\t\t\t\n \t\t\t\t</td></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="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">MR</td></tr><tr title="table-row"><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">Volume (cc) \t\t\t\t\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">59.6 (3.3–246.7) \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="2" align="left" valign="\n \t\t\t\t\ttop\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">18F-FDG PET/CT</td></tr><tr title="table-row"><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">Liver mean (counts) \t\t\t\t\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">10,975 (7419–17,337) \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 " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Tumor max (counts) \t\t\t\t\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">81,824 (34,458–143,604) \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 " 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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14.7 (5.9–32.2) \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">Volume (cc)</td></tr><tr title="table-row"><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">2SD \t\t\t\t\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">85.3 (5.2–299.7) \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 " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Fixed 40% \t\t\t\t\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">16.2 (2.1–82.2) \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 " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Fixed 50% \t\t\t\t\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">24.1 (3.0–94.5) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab207722.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Tumor volume analysis." ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:21 [ 0 => array:3 [ "identificador" => "bib0005" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:1 [ "referenciaCompleta" => "WHO projections of mortality and burden of disease, 2002–2030. <a class="elsevierStyleInterRef" href="http://www.who.int/entity/healthinfo/global_burden_disease/Dth6_2008_20090416.xls">http://www.who.int/entity/healthinfo/global_burden_disease/Dth6_2008_20090416.xls</a> [last access on 15.01.2011]." ] ] ] 1 => array:3 [ "identificador" => "bib0010" "etiqueta" => "2" "referencia" => array:1 [ 0 => array:1 [ "referenciaCompleta" => "SEER Cancer Statistics Review, 1975–2006, National Cancer Institute, Bethesda, MD. <a class="elsevierStyleInterRef" href="http://seer.cancer.gov/csr/1975_2006/results_single/sect_01_table.01.pdf">http://seer.cancer.gov/csr/1975_2006/results_single/sect_01_table.01.pdf</a> [last access on 15.01.2011]." ] ] ] 2 => array:3 [ "identificador" => "bib0015" "etiqueta" => "3" "referencia" => array:1 [ 0 => array:1 [ "referenciaCompleta" => "Ministry of Health, Brazil. Secretariat for Health Assistance, National Cancer Institute, Prevention and Surveillance Coordination Unit. Estimate 2010: Brazilian Cancer Incidence. <a class="elsevierStyleInterRef" href="http://www.inca.gov.br/estimativa/2010/estimativa20091201.pdf">http://www.inca.gov.br/estimativa/2010/estimativa20091201.pdf</a>" ] ] ] 3 => array:3 [ "identificador" => "bib0020" "etiqueta" => "4" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "NCCN task force: clinical utility of PET in a variety of tumor types" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "D.A. Podoloff" 1 => "D.W. Ball" 2 => "E. Ben-Josef" 3 => "A.B. Benson 3rd" 4 => "S.J. Cohen" 5 => "R.E. Coleman" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:7 [ "tituloSerie" => "J Natl Compr Canc Netw" "fecha" => "2009" "volumen" => "7" "numero" => "Suppl. 2" "paginaInicial" => "S1" "paginaFinal" => "S26" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/19878635" "web" => "Medline" ] ] ] ] ] ] ] ] 4 => array:3 [ "identificador" => "bib0025" "etiqueta" => "5" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Tumor biology-guided radiotherapy treatment planning: gross tumor volume versus functional tumor volume" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:4 [ 0 => "C. Guha" 1 => "A. Alfieri" 2 => "M.D. Blaufox" 3 => "S. Kalnicki" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1053/j.semnuclmed.2007.12.001" "Revista" => array:6 [ "tituloSerie" => "Semin Nucl Med" "fecha" => "2008" "volumen" => "38" "paginaInicial" => "105" "paginaFinal" => "113" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/18243845" "web" => "Medline" ] ] ] ] ] ] ] ] 5 => array:3 [ "identificador" => "bib0030" "etiqueta" => "6" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Impact of manual and automated interpretation of fused PET/CT data on esophageal target definition in radiation planning" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:4 [ 0 => "T.S. Hong" 1 => "J.H. Killoran" 2 => "M. Mamede" 3 => "H.J. Mamon" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.ijrobp.2008.07.061" "Revista" => array:6 [ "tituloSerie" => "Int J Radiat Oncol Biol Phys" "fecha" => "2008" "volumen" => "72" "paginaInicial" => "1612" "paginaFinal" => "1618" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/19028285" "web" => "Medline" ] ] ] ] ] ] ] ] 6 => array:3 [ "identificador" => "bib0035" "etiqueta" => "7" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Impact of FDG-PET/CT on radiotherapy volume delineation in non-small-cell lung cancer and correlation of imaging stage with pathologic findings" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "S.L. Faria" 1 => "S. Menard" 2 => "S. Devic" 3 => "C. Sirois" 4 => "L. Souhami" 5 => "R. Lisbona" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.ijrobp.2007.07.2379" "Revista" => array:6 [ "tituloSerie" => "Int J Radiat Oncol Biol Phys" "fecha" => "2008" "volumen" => "70" "paginaInicial" => "1035" "paginaFinal" => "1038" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/17996383" "web" => "Medline" ] ] ] ] ] ] ] ] 7 => array:3 [ "identificador" => "bib0040" "etiqueta" => "8" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "18FDG-PET based radiation planning of mediastinal lymph nodes in limited disease small cell lung cancer changes radiotherapy fields: a planning study" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "J. van Loon" 1 => "C. Offermann" 2 => "G. Bosmans" 3 => "R. Wanders" 4 => "A. Dekker" 5 => "J. Borger" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.radonc.2008.02.019" "Revista" => array:6 [ "tituloSerie" => "Radiother Oncol" "fecha" => "2008" "volumen" => "87" "paginaInicial" => "49" "paginaFinal" => "54" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/18342967" "web" => "Medline" ] ] ] ] ] ] ] ] 8 => array:3 [ "identificador" => "bib0045" "etiqueta" => "9" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "PET/CT imaging to guide cervical cancer therapy" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:1 [ 0 => "P.W. Grisby" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.2217/fon.09.70" "Revista" => array:6 [ "tituloSerie" => "Future Oncol" "fecha" => "2009" "volumen" => "5" "paginaInicial" => "953" "paginaFinal" => "958" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/19792965" "web" => "Medline" ] ] ] ] ] ] ] ] 9 => array:3 [ "identificador" => "bib0050" "etiqueta" => "10" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Utility of PET-CT on radiotherapy planning of head and neck cancer. Our initial experience" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "M.E. Bellón Guardia" 1 => "L. Pérez Romasanta" 2 => "A.M. García Vicente" 3 => "M.P. Talavera Rubio" 4 => "A. Palomar Muñoz" 5 => "B. González García" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.remn.2010.03.005" "Revista" => array:6 [ "tituloSerie" => "Rev Esp Med Nucl" "fecha" => "2010" "volumen" => "29" "paginaInicial" => "157" "paginaFinal" => "164" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/20494489" "web" => "Medline" ] ] ] ] ] ] ] ] 10 => array:3 [ "identificador" => "bib0055" "etiqueta" => "11" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Evaluation of different methods of 18F-FDG-PET target volume delineation in the radiotherapy of head and neck cancer" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "C. Greco" 1 => "S.A. Nehmeh" 2 => "H. Schöder" 3 => "M. Gönen" 4 => "B. Raphael" 5 => "H.E. Stambuk" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1097/COC.0b013e318168ef82" "Revista" => array:6 [ "tituloSerie" => "Am J Clin Oncol" "fecha" => "2008" "volumen" => "31" "paginaInicial" => "439" "paginaFinal" => "445" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/18838879" "web" => "Medline" ] ] ] ] ] ] ] ] 11 => array:3 [ "identificador" => "bib0060" "etiqueta" => "12" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Correlation of PET standard uptake value and CT window-level thresholds for target delineation in CT-based radiation treatment planning" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:5 [ 0 => "R. Hong" 1 => "J. Halama" 2 => "D. Bova" 3 => "A. Sethi" 4 => "B. Emami" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.ijrobp.2006.09.039" "Revista" => array:6 [ "tituloSerie" => "Int J Radiat Oncol Biol Phys" "fecha" => "2007" "volumen" => "67" "paginaInicial" => "720" "paginaFinal" => "726" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/17293230" "web" => "Medline" ] ] ] ] ] ] ] ] 12 => array:3 [ "identificador" => "bib0065" "etiqueta" => "13" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "18F-FDG PET definition of gross tumor volume for radiotherapy of non-small cell lung cancer: is a single standardized uptake value threshold approach appropriate?" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "K.J. Biehl" 1 => "F.M. Kong" 2 => "F. Dehdashti" 3 => "J.Y. Jin" 4 => "S. Mutic" 5 => "I. El Naqa" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:6 [ "tituloSerie" => "J Nucl Med" "fecha" => "2006" "volumen" => "47" "paginaInicial" => "1808" "paginaFinal" => "1812" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/17079814" "web" => "Medline" ] ] ] ] ] ] ] ] 13 => array:3 [ "identificador" => "bib0070" "etiqueta" => "14" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Tumor delineation using PET in head and neck cancers: threshold contouring and lesion volumes" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "E.C. Ford" 1 => "P.E. Kinahan" 2 => "L. Hanlon" 3 => "A. Alessio" 4 => "J. Rajendran" 5 => "D.L. Schwartz" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1118/1.2361076" "Revista" => array:6 [ "tituloSerie" => "Med Phys" "fecha" => "2006" "volumen" => "33" "paginaInicial" => "4280" "paginaFinal" => "4288" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/17153406" "web" => "Medline" ] ] ] ] ] ] ] ] 14 => array:3 [ "identificador" => "bib0075" "etiqueta" => "15" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Phase I trial of erlotinib combined with cisplatin and radiotherapy for patients with locally advanced cervical squamous cell cancer" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "A. Nogueira-Rodrigues" 1 => "C.C. do Carmo" 2 => "C. Viegas" 3 => "F. Erlich" 4 => "C. Camisão" 5 => "K. Fontão" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1158/1078-0432.CCR-07-5112" "Revista" => array:6 [ "tituloSerie" => "Clin Cancer Res" "fecha" => "2008" "volumen" => "14" "paginaInicial" => "6324" "paginaFinal" => "6329" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/18829516" "web" => "Medline" ] ] ] ] ] ] ] ] 15 => array:3 [ "identificador" => "bib0080" "etiqueta" => "16" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Erlotinib (E) combined with cisplatin (C) and radiotherapy (RT) for patients with locally advanced squamous cell cervical cancer: a phase II trial" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:6 [ 0 => "C.G. Ferreira" 1 => "F. Erlich" 2 => "C.C. do Carmo" 3 => "I.A. Small" 4 => "K. Fontão" 5 => "A. Nogueira-Rodrigues" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1200/JCO.2007.15.2777" "Revista" => array:5 [ "tituloSerie" => "J Clin Oncol" "fecha" => "2008" "volumen" => "26" "numero" => "Suppl." "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/18445848" "web" => "Medline" ] ] ] ] ] ] ] ] 16 => array:3 [ "identificador" => "bib0085" "etiqueta" => "17" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Medical image processing, analysis and visualization in clinical research (abstract)" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:6 [ 0 => "M.J. McAuliffe" 1 => "F.M. Lalonde" 2 => "D. McGarry" 3 => "W. Gandler" 4 => "K. Csaky" 5 => "B.L. Trus" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "LibroEditado" => array:4 [ "titulo" => "CBMS’01: proceedings of the 14th IEEE symposium on computer-based medical systems" "paginaInicial" => "381" "conferencia" => "Los Alamitos, CA" "serieFecha" => "2001" ] ] ] ] ] ] 17 => array:3 [ "identificador" => "bib0090" "etiqueta" => "18" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Pre-operative estimation of esophageal tumor metabolic length in FDG-PET images with surgical pathology confirmation" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:6 [ 0 => "M. Mamede" 1 => "G. El Fakhri" 2 => "P. Abreu-e-Lima" 3 => "W. Gandler" 4 => "V. Nosé" 5 => "V.H. Gerbaudo" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1007/s12149-007-0040-0" "Revista" => array:6 [ "tituloSerie" => "Ann Nucl Med" "fecha" => "2007" "volumen" => "21" "paginaInicial" => "553" "paginaFinal" => "562" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/18092131" "web" => "Medline" ] ] ] ] ] ] ] ] 18 => array:3 [ "identificador" => "bib0095" "etiqueta" => "19" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Comparison of different methods for delineation of 18F-FDG PET-positive tissue for target volume definition in radiotherapy of patients with non-small cell lung cancer" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "U. Nestle" 1 => "S. Kremp" 2 => "A. Schaefer-Schuler" 3 => "C. Sebastian-Welsch" 4 => "D. Hellwig" 5 => "C. Rübe" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:6 [ "tituloSerie" => "J Nucl Med" "fecha" => "2005" "volumen" => "46" "paginaInicial" => "1342" "paginaFinal" => "1348" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/16085592" "web" => "Medline" ] ] ] ] ] ] ] ] 19 => array:3 [ "identificador" => "bib0100" "etiqueta" => "20" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "The contribution of 18F-fluoro-2-deoxy-glucose positron emission tomographic imaging to radiotherapy planning in lung cancer" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "J.D. Kiffer" 1 => "S.U. Berlangieri" 2 => "A.M. Scott" 3 => "C. Sebastian-Welsch" 4 => "D. Hellwig" 5 => "C. 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Original article

18F-FDG-PET-based tumor delineation in cervical cancer: Threshold contouring and lesion volumes

Delineación tumoral basada en 18F-FDG-PET en el cáncer cervical: delimitación del contorno umbral y volúmenes de la lesión

F. Erlicha, C. Camisãob, A. Nogueira-Rodriguesc, S. Altinod, C.G. Ferreirac, M. Mamedec,e,

Corresponding author

mamede.mm@gmail.com

Corresponding author.

a Radiation Oncology Service, National Cancer Institute of Brazil, Rio de Janeiro, Brazil

b Radiology Service, National Cancer Institute of Brazil, Rio de Janeiro, Brazil

c Clinical Research Coordination, National Cancer Institute of Brazil, Rio de Janeiro, Brazil

d Nuclear Medicine Section, Samaritano Hospital, Rio de Janeiro, Brazil

e Molecular Imaging Center, Universidade Federal Minas Gerais, Belo Horizonte, Brazil

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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Cervical cancer is the fifth most deadly cancer in women worldwide&#44; being the cause of 286&#44;451 estimated deaths in 2008&#46;<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a> Based on NCI&#39;s SEER Cancer Statistics Review&#44; it was estimated that 11&#44;270 women would be diagnosed with and 4070 women would die of cancer of the cervix uteri in 2009&#46;<a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">2</span></a> In Brazil&#44; 18&#44;430 new cases are estimated in 2010&#44; with a 5-year overall survival rate of 49&#37;&#46;<a class="elsevierStyleCrossRef" href="#bib0015"><span class="elsevierStyleSup">3</span></a> Locally advanced disease is still the most prevalent presentation&#44; with the standard of care being concurrent chemotherapy and radiation therapy&#46;</p><p id="par0010" class="elsevierStylePara elsevierViewall">Historically radiation therapy planning is done using computerized tomography &#40;CT&#41; images&#46; Besides CT&#44; magnetic resonance &#40;MR&#41; is also very useful to show more anatomic detail&#44; especially soft tissues&#46; However&#44; CT and MR only demonstrate anatomic tumor extent&#44; and do not reflect biological tumor behavior&#46;</p><p id="par0015" class="elsevierStylePara elsevierViewall">Fluorodeoxyglucose &#40;FDG&#41; labeled with fluor-18 &#40;<span class="elsevierStyleSup">18</span>F-FDG&#41;&#44; an analog of glucose&#44; has been used extensively to diagnose&#44; stage&#44; re-stage and follow up patients with cancer&#46;<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">4</span></a><span class="elsevierStyleSup">18</span>F-FDG PET images reflect the glycolitic metabolic tumoral behavior&#44; which is important for treatment planning&#46; Recently&#44; <span class="elsevierStyleSup">18</span>F-FDG PET has also been applied in several studies to the radiation therapy planning for different tumor types&#46;<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a> They have shown significant alterations to the gross tumor volume &#40;GTV&#41; delineation and consequently to the radiation therapy fields&#46;<a class="elsevierStyleCrossRefs" href="#bib0030"><span class="elsevierStyleSup">6&#8211;10</span></a> Faria et al&#46; showed that PET altered the contour in 18 &#40;56&#37;&#41; of 32 cases of non-small-cell lung cancer compared to CT alone&#46;<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">7</span></a> Van Loon et al&#46; showed that incorporating <span class="elsevierStyleSup">18</span>F-FDG PET information in radiotherapy planning for patients with limited-disease small-cell lung cancer changed the treatment plan in 24&#37; of patients compared to CT&#46;<a class="elsevierStyleCrossRef" href="#bib0040"><span class="elsevierStyleSup">8</span></a> Grisby showed that <span class="elsevierStyleSup">18</span>F-FDG PET can be useful to target active metabolic disease and aid radiotherapy planning in cervical cancer&#46;<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">9</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">Although these initial studies showed the great advantages of incorporating <span class="elsevierStyleSup">18</span>F-FDG PET into radiotherapy treatment planning&#44; there is no consensus yet on the use of these images for target delineation&#46; Fixed-level threshold techniques have been used to delineate GTV&#46; These fixed-level thresholds are not always accurate when compared to CT or MR defined volumes&#44; and depending on the level used&#44; significant variability on GTV values has been reported&#46;<a class="elsevierStyleCrossRefs" href="#bib0055"><span class="elsevierStyleSup">11&#44;12</span></a> Biehl et al&#46; showed that no single threshold delineating the PET-GTV provides accurate volume definition&#44; compared with that provided by the CT-GTV&#44; for the majority of NSCLCs&#46;<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a> In another study in patients with head and neck cancer&#44; the authors demonstrated that PET-based tumor volumes are strongly affected by the choice of threshold level&#44; leading to a significant dosimetric impact&#46;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a></p><p id="par0025" class="elsevierStylePara elsevierViewall">However&#44; PET-defined tumor volumes in radiotherapy treatment planning can significantly affect the contour of the GTV due to variation in setting image signal thresholds&#59; its incorporation can reduce considerably the inter- and intra-observer evaluations&#46; Thus&#44; there is no consensus yet as how the PET-images should be used to generate the GTV volumes for radiation therapy planning&#46; The goal of this study is to evaluate a semi-automated segmentation algorithm for GTV delineation by comparing the metabolic PET-derived volumes with the anatomic MR-based volumes in cervical cancer patients&#46; The originality of this manuscript relays on its strength to correlate well with volumes generated from MR images and its simplicity which makes it suitable for routine clinical use&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle">Material and methods</span><p id="par0030" class="elsevierStylePara elsevierViewall">Thirty-two patients with locally advanced cervical cancer were retrospectively evaluated&#46; This cohort was part of a phase I&#47;II trial of erlotinib combined to cisplatin and radiation&#46;<a class="elsevierStyleCrossRefs" href="#bib0075"><span class="elsevierStyleSup">15&#44;16</span></a> Staging was performed with clinical examination and all of the patients had CT&#44; MR and <span class="elsevierStyleSup">18</span>F-FDG PET&#47;CT scans before treatment&#44; as well as cistoscopy and rectosigmodoscopy&#46; Locally advanced disease was defined as FIGO stage greater than IB2 and lesser than IVB&#46; <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a> shows the demographics of our patient cohort&#46; The study protocol was approved by our local ethics committee&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0035" class="elsevierStylePara elsevierViewall">MR examinations were performed using a 1&#46;5<span class="elsevierStyleHsp" style=""></span>T superconducting magnet &#40;Symphony&#44; Siemens Medical Systems&#44; Erlangen&#44; Germany&#41; covering the abdomen and pelvis with identical protocol&#46; All patients received 20<span class="elsevierStyleHsp" style=""></span>ml of intravaginal gel applied <span class="elsevierStyleItalic">via</span> syringe&#46; All patients fasted 4<span class="elsevierStyleHsp" style=""></span>h prior to the examination&#46; No bowel relaxants were routinely administered&#46; The acquisition protocol consisted on the following sequences&#58; &#40;1&#41; spin-echo T1-weighted axial&#44; repetition time&#47;echo time &#40;TR&#47;TE&#41; 5&#46;2&#47;2&#46;6<span class="elsevierStyleHsp" style=""></span>ms&#44; slice thickness 3&#8211;5<span class="elsevierStyleHsp" style=""></span>mm&#44; interslice gap 0&#44; matrix 512<span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span>512&#59; 38<span class="elsevierStyleHsp" style=""></span>cm FOV&#59; &#40;2&#41; fast spin-echo T2-weighted with a phased array coil in sagittal&#44; coronal and axial planes&#44; TR&#47;TE 4500&#8211;5000&#47;95&#8211;116<span class="elsevierStyleHsp" style=""></span>ms&#44; slice thickness 3<span class="elsevierStyleHsp" style=""></span>mm&#44; interslice gap 0&#46;2<span class="elsevierStyleHsp" style=""></span>mm&#44; matrix 512<span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span>512&#59; 25<span class="elsevierStyleHsp" style=""></span>cm FOV&#59; &#40;3&#41; turbo spin echo T2 with fat suppression axial&#44; TR&#47;TE 4500&#8211;5000&#47;95&#8211;116<span class="elsevierStyleHsp" style=""></span>mm&#44; slice 5<span class="elsevierStyleHsp" style=""></span>mm&#44; interslice 0&#46;2<span class="elsevierStyleHsp" style=""></span>mm&#44; matrix 512<span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span>512&#44; 30&#8211;45<span class="elsevierStyleHsp" style=""></span>cm FOV&#59; and &#40;4&#41; T1-weighted spin-echo axial sequences before and after intravenous injection of gadolinium &#40;0&#46;1<span class="elsevierStyleHsp" style=""></span>mmol&#47;kg&#41; TR&#47;TE 5&#46;2&#47;2&#46;6<span class="elsevierStyleHsp" style=""></span>ms&#44; slice thickness 3<span class="elsevierStyleHsp" style=""></span>mm&#44; interslice gap 0&#44; matrix 512<span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span>512&#59; 35<span class="elsevierStyleHsp" style=""></span>cm FOV&#46; None of the images were acquired using flat table&#46;</p><p id="par0040" class="elsevierStylePara elsevierViewall">The patients fasted for at least 4<span class="elsevierStyleHsp" style=""></span>h before the intravenous injection of <span class="elsevierStyleSup">18</span>F-FDG &#40;783&#46;5<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>102&#46;3<span class="elsevierStyleHsp" style=""></span>MBq&#41;&#46; Serum glucose levels were measured before <span class="elsevierStyleSup">18</span>F-FDG injection&#46; The scanning was performed &#8764;60<span class="elsevierStyleHsp" style=""></span>min after the injection of <span class="elsevierStyleSup">18</span>F-FDG using a Biograph 2 PET&#47;CT scanner &#40;CT&#58; Somatom sensation 2&#44; PET&#58; LSO crystal&#44; Siemens Medical Solution&#44; Malvern&#44; USA&#41; with a 162<span class="elsevierStyleHsp" style=""></span>mm axial field of view&#46; The images were obtained with the patient in the supine position from the orbital-meatal line to the proximal thighs&#46; CT studies for attenuation correction and anatomic co-registration were performed following the administration of diluted barium oral contrast&#44; and with the following imaging parameters&#58; 130<span class="elsevierStyleHsp" style=""></span>kV&#44; 25<span class="elsevierStyleHsp" style=""></span>mAs&#44; 0&#46;8<span class="elsevierStyleHsp" style=""></span>s per CT rotation&#44; and a 5&#46;0-mm slice thickness&#46; The CT data were reconstructed in a 512<span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span>512 matrix using a filtered backprojection algorithm&#46; Immediately after the CT scan&#44; emission images were obtained in a 3D mode with 3<span class="elsevierStyleHsp" style=""></span>min acquisitions at each level &#40;5&#8211;7 bed positions&#41;&#46; The PET images were reconstructed in a 128<span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span>128 matrix using an iterative-ordered subsets expectation maximization &#40;OSEM&#41; algorithm &#40;4 iterations&#44; 8 subsets&#41;&#44; yielding a volume of 47 slices with a voxel size of 3&#46;37<span class="elsevierStyleHsp" style=""></span>mm<span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span>3&#46;37<span class="elsevierStyleHsp" style=""></span>mm<span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span>3&#46;37<span class="elsevierStyleHsp" style=""></span>mm&#46; None of the images were acquired using flat table&#46;</p><p id="par0045" class="elsevierStylePara elsevierViewall">For volume delineation and measurement software developed at the National Institutes of Health &#40;NIH&#41; was used&#46; MIPAV &#40;Center of Information and Technology-CIT&#44; NIH&#44; Bethesda&#44; USA&#41; software is a medical imaging tool used for image processing&#44; segmentation&#44; registration&#44; fusion&#44; and visualization&#46;<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a> MIPAV is user-friendly freeware&#44; available on the Internet and runs on several platforms &#40;Windows&#44; MAC&#44; UNIX&#44; and LINUX&#41;&#46;</p><p id="par0050" class="elsevierStylePara elsevierViewall">Semi-automated PET-image-based main tumor GTV delineation was applied using a previous established algorithm &#40;GTV<span class="elsevierStyleInf">2SD</span>&#41;<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> and 2 fixed threshold-based methods &#40;GTV<span class="elsevierStyleInf">40&#37;</span> and GTV<span class="elsevierStyleInf">50&#37;</span>&#41;&#46; Briefly&#44; the user defined the voxel with the highest intensity value &#40;<span class="elsevierStyleItalic">I</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">top</span></span>&#41; within the lesion on the PET image&#46; This intensity was set up as the maximum voxel on the threshold scale&#46; The liver was chosen as the background region because of known adequate performance&#46;<a class="elsevierStyleCrossRefs" href="#bib0090"><span class="elsevierStyleSup">18&#44;19</span></a> Several liver regions of interest &#40;ROI&#41; were drawn in various transaxial slices&#44; and the mean intensity and SD over all voxels in those ROIs were used for further calculation&#46; The lower level of the threshold scale &#40;<span class="elsevierStyleItalic">I</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">bottom</span></span>&#41; was defined as a result of the difference between <span class="elsevierStyleItalic">I</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">top</span></span> and the sum of the mean intensity in the liver &#40;<span class="elsevierStyleItalic">I</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">mean</span></span>&#41; plus 2-SD &#40;<span class="elsevierStyleItalic">I</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">2SD</span></span>&#41;&#58; <span class="elsevierStyleItalic">I</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">bottom</span></span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">I</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">top</span></span><span class="elsevierStyleHsp" style=""></span>&#8722;<span class="elsevierStyleHsp" style=""></span>&#40;<span class="elsevierStyleItalic">I</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">mean</span></span><span class="elsevierStyleHsp" style=""></span>&#43;<span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">I</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">2SD</span></span>&#41;&#46; After defining <span class="elsevierStyleItalic">I</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">top</span></span> and <span class="elsevierStyleItalic">I</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">bottom</span></span>&#44; the user selects a point in the lesion &#40;the &#8220;seed point&#8221;&#41; and a 3D threshold-based region-growing algorithm segments the lesion of interest to include only pixels between <span class="elsevierStyleItalic">I</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">top</span></span> and <span class="elsevierStyleItalic">I</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">bottom</span></span>&#46; If a pixel&#39;s intensity falls between <span class="elsevierStyleItalic">I</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">top</span></span> and <span class="elsevierStyleItalic">I</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">bottom</span></span>&#44; it is included in the region&#46; Iterations stop when no more neighbors fall in the acceptable range&#46; Afterwards&#44; MIPAV generates the total metabolic volume of the tumor &#40;GTV<span class="elsevierStyleInf">2SD</span>&#41;&#46; GTV<span class="elsevierStyleInf">40&#37;</span> and GTV<span class="elsevierStyleInf">50&#37;</span> were determined with 40&#37; and 50&#37; of the <span class="elsevierStyleItalic">I</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">top</span></span>&#44; respectively&#46; Then&#44; volumes were compared with the GTVs generated manually using MR &#40;GTV<span class="elsevierStyleInf">MR</span>&#41;&#46; For this purpose&#44; T2 weighted axial images were used and the drawing was performed by a radiologist specialized in gynecological MR&#46;</p><p id="par0055" class="elsevierStylePara elsevierViewall">For comparison between the volumes&#44; Spearman&#39;s <span class="elsevierStyleItalic">&#961;</span> correlation test was used in a SPSS 12&#46;0 software &#40;SPSS&#44; Chicago&#44; IL&#41; for statistical analysis&#46;</p></span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle">Results</span><p id="par0060" class="elsevierStylePara elsevierViewall">Between 2005 and 2008&#44; 32 patients were eligible for analysis&#46; There were predominant moderately differentiated cancers&#44; with 65&#37; of the patients classified as WHO grade II&#46; More than a half of the patients had IIIB FIGO stage &#40;51&#37;&#41;&#46; Of these&#44; 14 patients had disease extending to the pelvic wall and 3 had hydronephrosis &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;&#46;</p><p id="par0065" class="elsevierStylePara elsevierViewall">Tumor volume analysis is shown in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#46; The GTV<span class="elsevierStyleInf">MR</span> ranged from 3&#46;3 cc to 246&#46;7<span class="elsevierStyleHsp" style=""></span>cc&#44; reflecting the heterogeneity of the patients and very different tumor sizes&#46; Moreover&#44; also the range of SUV<span class="elsevierStyleInf">max</span> showed an important variation&#44; with values ranging between 5&#46;9 and 32&#46;2&#46; The mean volumes obtained with 2SD-algorithm threshold&#44; fixed 40&#37; and fixed 50&#37; were 85&#46;3<span class="elsevierStyleHsp" style=""></span>cc&#44; 16&#46;2<span class="elsevierStyleHsp" style=""></span>cc and 24&#46;1<span class="elsevierStyleHsp" style=""></span>cc&#44; respectively&#46;</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0070" class="elsevierStylePara elsevierViewall">Spearman&#39;s correlation analysis is shown in <a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>&#46; A good correlation was achieved between the volume obtained in MR &#40;GTV<span class="elsevierStyleInf">MR</span>&#41; and the volumes determined as the pixel with the mean value plus 2-standard deviation of the liver intensity &#40;GTV<span class="elsevierStyleInf">2SD</span>&#41; in the <span class="elsevierStyleSup">18</span>F-FDG PET images &#40;<span class="elsevierStyleItalic">&#961;</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;88&#59; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41;&#44; being closer to the 45&#176; line&#46; Both&#44; the mean value and the volume range were well correlated&#44; the GTV<span class="elsevierStyleInf">2SD</span> being slightly over-estimated when compared to the GTV<span class="elsevierStyleInf">MR</span>&#46; However&#44; weaker correlation was observed with the fixed level threshold volumes &#40;<span class="elsevierStyleItalic">&#961;</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;68 and <span class="elsevierStyleItalic">&#961;</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;71 for 40&#37;- and 50&#37;-threshold&#44; respectively&#41;&#46; <a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a> shows typical relationships between PET-GTVs &#40;GTV<span class="elsevierStyleInf">2SD</span>&#44; GTV<span class="elsevierStyleInf">40&#37;</span> and GTV<span class="elsevierStyleInf">50&#37;</span>&#41; with that from MR &#40;GTV<span class="elsevierStyleInf">MR</span>&#41;&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><elsevierMultimedia ident="fig0010"></elsevierMultimedia><p id="par0075" class="elsevierStylePara elsevierViewall">As it can be observed in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a> and <a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>&#44; the fixed level thresholds volumes tended to underestimate the MR-volume&#46; Observing <a class="elsevierStyleCrossRef" href="#fig0015">Fig&#46; 3</a>&#44; we can infer that for the mean MR-volume achieved in our patients&#44; the best fit threshold volume would be between 60&#37; and 80&#37; &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>17&#41;&#46; Therefore&#44; in order to generate better PET-image volumes for radiation planning&#44; there is a need to adjust the threshold for each patient&#46;</p><elsevierMultimedia ident="fig0015"></elsevierMultimedia></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle">Discussion</span><p id="par0080" class="elsevierStylePara elsevierViewall">The recent approach to cervical cancer treatment has been the use of highly conformal Intensity Modulated Radiation Therapy &#40;IMRT&#41; and Image-Guided Radiation Therapy &#40;IGRT&#41; with concomitant dose escalation to the GTVs&#46; These highly conformal treatments are very volume dependent&#44; and non-accurate volume delineation could lead to geographical misses&#44; increasing the chance of treatment failure&#44; or overestimation of GTV&#44; leading to more acute and chronic toxicities&#46; Furthermore&#44; molecular imaging with <span class="elsevierStyleSup">18</span>F-FDG PET has been extensively used to delineate the GTV for radiation therapy planning&#46; However&#44; there is not a consensus on how the <span class="elsevierStyleSup">18</span>F-FDG PET should be used for tumor-volume delineation&#44; because of variations due to the threshold applied&#46;</p><p id="par0085" class="elsevierStylePara elsevierViewall">In the present study&#44; we evaluated volumes of the main tumor generated by using a previously published algorithm &#40;GTV<span class="elsevierStyleInf">2SD</span>&#41; in 32 patients with locally advanced cervical cancer and compared these results with those derived from MR&#46; MR-derived tumor volumes were also compared with those obtained by using fixed level metabolic thresholds &#40;40&#37; and 50&#37;&#41;&#46; The study showed that the GTV<span class="elsevierStyleInf">2SD</span> worked better than the fixed level thresholds&#46; Thus&#44; the method provides preliminary evidence that tumor delineation might be feasible using computer-generated metabolic measurements and that it could be used for radiotherapy planning in cervical cancer patients&#46;</p><p id="par0090" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleSup">18</span>F-FDG PET is being widely used to delineate GTV in radiotherapy planning&#46; Currently&#44; MR images are considered the best imaging modality to delineate lesion volumes in cervical cancer&#46; However&#44; MR relies only on tumor morphological patterns and does not provide metabolic information&#44; which is known to be highly desirable to define and estimate tumor burden&#46; This is especially important when using state-of-the-art radiotherapy techniques such as IMRT and IGRT&#46;</p><p id="par0095" class="elsevierStylePara elsevierViewall">The first report describing the use of <span class="elsevierStyleSup">18</span>F-FDG PET in radiotherapy planning was published by Kiffer et al&#46; in 1998&#46;<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">20</span></a> The authors reported a 26&#46;7&#37; difference in the treatment fields when PET was compared to CT only&#46;<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">20</span></a> Since then&#44; many other papers were published showing significant alterations in GTV and treatment fields with PET&#46; In 2004&#44; Bradley et al&#46; proposed the term biological tumor volume &#40;BTV&#41; for PET-derived metabolic bulk&#46;<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">21</span></a> However&#44; it still remained unclear what the real accuracy was between the traditional GTV obtained with CT and MR and the new BTV obtained with molecular imaging with PET&#46; Only few studies dealt with this question&#44; and most of them used fixed level thresholds&#44; usually 40&#37; or 50&#37; of the maximum tumor intensity&#46; However&#44; as shown in <a class="elsevierStyleCrossRefs" href="#fig0005">Figs&#46; 1&#8211;3</a>&#44; resulting GTVs could have important volume differences according to the window used for contour delineation&#46;</p><p id="par0100" class="elsevierStylePara elsevierViewall">Hong et al&#46;&#44; in a trial published in 2008 in esophageal cancer patients&#44; identified that different PET-based techniques can produce significantly different tumor volumes in a large percentage of them&#46; They also concluded that using fixed level thresholds do not produce accurate correlations between CT and PET findings and&#44; furthermore&#44; proposed a semi-automated algorithm that showed the best correlation&#44; defined by the volumes determined as the pixel with the mean value plus 2-standard deviation of the liver intensity&#46;<a class="elsevierStyleCrossRef" href="#bib0030"><span class="elsevierStyleSup">6</span></a></p><p id="par0105" class="elsevierStylePara elsevierViewall">In the present study&#44; PET-image volumes generated using GTV<span class="elsevierStyleInf">2SD</span> algorithm correlated very well with MR-image volumes&#59; while weaker correlations were observed when PET-image volumes were generated applying 40&#37;- and 50&#37;-fixed threshold levels and compared with the ones from MR&#46; One reason might be the SUV heterogeneity within the tumor&#44; leading to erroneous volume estimates when fixed-threshold levels are used &#40;either 40&#37; or 50&#37; of <span class="elsevierStyleItalic">T</span><span class="elsevierStyleInf">max</span>&#41;&#46; These <span class="elsevierStyleItalic">T</span><span class="elsevierStyleInf">max</span> cutoff values often underestimate the MR-derived tumor volume&#44; as they only represent the most active areas of the tumor and not the metabolic activity over the entire tumor volume&#46; On the other hand&#44; the proposed algorithm&#44; applies an individual variable to reach the cutoff value&#58; the tumor&#47;liver uptake ratio&#46; By doing this&#44; we showed that the volumes obtained by the PET images are more reliable and well correlated to those obtained by using fixed arbitrary threshold levels&#46;</p><p id="par0110" class="elsevierStylePara elsevierViewall">Tumor volumes were not estimated from the pathological tissue samples&#44; and thus&#44; we were unable to study the degree of variability&#44; between metabolic and anatomic tumor volumes <span class="elsevierStyleItalic">in vivo</span>&#46; This variability could be explained in part by the inherent limitations of PET&#44; and&#47;or by the biological properties of the tumor itself&#46;</p><p id="par0115" class="elsevierStylePara elsevierViewall">It is important to point out that the measurements derived from PET data using this method suffer from certain shortcomings<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a>&#58; the main problem is related to limiting the effect of partial volume on the lesion-to-liver ratios&#46; These ratios are typically higher for low- and high-contrast objects&#46;<a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">2</span></a> There were no histological measurements for comparison&#44; which are considered to be the gold standard&#46;<a class="elsevierStyleCrossRef" href="#bib0015"><span class="elsevierStyleSup">3</span></a> Although not observed in the present study&#44; another limitation could be related to the evaluation of lesions that are smaller than the spatial resolution of the PET system&#46; Partial volume effect can also contribute&#44; in part&#44; to the less-than-perfect correlation on this scenario&#46;<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">4</span></a> We used MR-volume as our reference for comparisons&#46; However&#44; MR has reasonable resolution&#59; we assumed errors that might have interfered in our correlations&#46;<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a> PET- and MR-image were not acquired using flat table&#59; however&#44; it may not have impacted negatively on the GTV measurements&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle">Conclusion</span><p id="par0120" class="elsevierStylePara elsevierViewall">Our study results provide preliminary evidence that metabolic tumor volume delineation is feasible using computer-generated measurements in <span class="elsevierStyleSup">18</span>F-FDG PET images&#46; Generation of <span class="elsevierStyleSup">18</span>F-FDG PET based tumor volumes is affected by the choice of threshold level used&#46; Metabolic tumor bulk calculated using the pixel with the mean value plus 2-standard deviations of the liver intensity &#40;GTV<span class="elsevierStyleInf">2SD</span>&#41; correlates better with the MR-derived tumor volumes than fixed threshold-based algorithms&#46; The method is a simple and clinically applicable approach to generate PET-derived GTV for radiation therapy planning of cervical cancer&#46;</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle">Conflict of interest</span><p id="par0125" class="elsevierStylePara elsevierViewall">The authors declare no conflict of interest&#46;</p></span></span>"
    "textoCompletoSecciones" => array:1 [
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        0 => array:2 [
          "identificador" => "xres119495"
          "titulo" => array:5 [
            0 => "Abstract"
            1 => "Objective"
            2 => "Material and methods"
            3 => "Results"
            4 => "Conclusions"
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        1 => array:2 [
          "identificador" => "xpalclavsec106775"
          "titulo" => "Keywords"
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        2 => array:2 [
          "identificador" => "xres119496"
          "titulo" => array:5 [
            0 => "Resumen"
            1 => "Objetivo"
            2 => "Material y m&#233;todos"
            3 => "Resultados"
            4 => "Conclusiones"
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        3 => array:2 [
          "identificador" => "xpalclavsec106776"
          "titulo" => "Palabras clave"
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        4 => array:2 [
          "identificador" => "sec0005"
          "titulo" => "Introduction"
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        5 => array:2 [
          "identificador" => "sec0010"
          "titulo" => "Material and methods"
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          "identificador" => "sec0025"
          "titulo" => "Conclusion"
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          "identificador" => "sec0030"
          "titulo" => "Conflict of interest"
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          "identificador" => "xack37560"
          "titulo" => "Acknowledgment"
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          "titulo" => "References"
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    "pdfFichero" => "main.pdf"
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    "fechaRecibido" => "2012-03-13"
    "fechaAceptado" => "2012-06-11"
    "PalabrasClave" => array:2 [
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          "clase" => "keyword"
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          "identificador" => "xpalclavsec106775"
          "palabras" => array:4 [
            0 => "<span class="elsevierStyleSup">18</span>F-FDG-PET"
            1 => "Cervical cancer"
            2 => "Gross tumor volume"
            3 => "Tumor delineation"
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        0 => array:4 [
          "clase" => "keyword"
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          "palabras" => array:4 [
            0 => "<span class="elsevierStyleSup">18</span>F-FDG-PET"
            1 => "C&#225;ncer cervical"
            2 => "Volumen tumoral grueso"
            3 => "Delimitaci&#243;n tumoral"
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        "titulo" => "Abstract"
        "resumen" => "<span class="elsevierStyleSectionTitle">Objective</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">To evaluate a semi-automated PET-image tumor segmentation algorithm for gross tumor volume &#40;GTV&#41; delineation in patients with locally advanced cervical cancer&#46;</p> <span class="elsevierStyleSectionTitle">Material and methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Thirty-two patients with locally advanced cervical cancer were retrospectively evaluated&#46; Semi-automated PET-image-based GTV delineation was applied using a previous established algorithm &#40;GTV<span class="elsevierStyleInf">2SD</span>&#41; and 2 fixed threshold-based methods &#40;GTV<span class="elsevierStyleInf">40&#37;</span> and GTV<span class="elsevierStyleInf">50&#37;</span>&#41;&#46; GTV<span class="elsevierStyleInf">2SD</span> was determined as the pixel with the mean value plus 2-standard deviation of the liver intensity&#44; and GTV<span class="elsevierStyleInf">40&#37;</span> and GTV<span class="elsevierStyleInf">50&#37;</span> with 40&#37; and 50&#37; of the maximum tumor intensity &#40;<span class="elsevierStyleItalic">T</span><span class="elsevierStyleInf">max</span>&#41;&#44; respectively&#46; The derived volumes were then compared with the GTVs generated manually using MR &#40;GTV<span class="elsevierStyleInf">MR</span>&#41;&#46;</p> <span class="elsevierStyleSectionTitle">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">The mean value of GTV<span class="elsevierStyleInf">2SD</span>&#44; GTV<span class="elsevierStyleInf">40&#37;</span> and GTV<span class="elsevierStyleInf">50&#37;</span> was 85&#46;3<span class="elsevierStyleHsp" style=""></span>cc&#44; 16&#46;2<span class="elsevierStyleHsp" style=""></span>cc and 24&#46;1<span class="elsevierStyleHsp" style=""></span>cc&#44; respectively&#46; Good agreement was noticed between GTV<span class="elsevierStyleInf">2SD</span> and GTV<span class="elsevierStyleInf">MR</span> &#40;<span class="elsevierStyleItalic">&#961;</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;88&#41;&#46; GTV<span class="elsevierStyleInf">40&#37;</span> and GTV<span class="elsevierStyleInf">50&#37;</span> showed weaker correlation with GTV<span class="elsevierStyleInf">MR</span> &#40;<span class="elsevierStyleItalic">&#961;</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;68 and <span class="elsevierStyleItalic">&#961;</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;71&#44; respectively&#41;&#46;</p> <span class="elsevierStyleSectionTitle">Conclusions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">This study provides preliminary evidence that metabolic tumor volume delineation is feasible using computer-generated measurements in <span class="elsevierStyleSup">18</span>F-FDG PET images&#46; Generation of PET-based tumor volumes is affected by the choice of threshold level used&#46; Metabolic tumor bulk calculated using the pixel with the mean value plus 2-standard deviations of the liver intensity &#40;GTV<span class="elsevierStyleInf">2SD</span>&#41; correlates better with the MR-derived tumor volumes&#46; The method is a simple and clinically applicable approach to generate PET-derived GTV for radiation therapy planning of cervical cancer&#46;</p>"
      ]
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        "titulo" => "Resumen"
        "resumen" => "<span class="elsevierStyleSectionTitle">Objetivo</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Evaluar el algoritmo de segmentaci&#243;n tumoral de la imagen PET semiautomatizada para delinear el volumen tumoral grueso &#40;GTV&#41; en pacientes con c&#225;ncer cervical localmente avanzado&#46;</p> <span class="elsevierStyleSectionTitle">Material y m&#233;todos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Se evalu&#243; retrospectivamente a 32 pacientes con c&#225;ncer cervical localmente avanzado&#46; Se utiliz&#243; la delineaci&#243;n GTV basada en imagen PET semiautomatizada&#44; utilizando un algoritmo previamente establecido &#40;GTV<span class="elsevierStyleInf">2SD</span>&#41; y 2 m&#233;todos basados en umbrales fijos &#40;GTV<span class="elsevierStyleInf">40&#37;</span> y GTV<span class="elsevierStyleInf">50&#37;</span>&#41;&#46; Se calcul&#243; GTV<span class="elsevierStyleInf">2SD</span>&#44; como el p&#237;xel con el valor medio m&#225;s 2 desviaciones est&#225;ndar de la intensidad del h&#237;gado&#44; y GTV<span class="elsevierStyleInf">40&#37;</span> y GTV<span class="elsevierStyleInf">50&#37;</span> con el 40&#37; y el 50&#37; de intensidad tumoral m&#225;xima &#40;Tm&#225;x&#41;&#44; respectivamente&#46; A continuaci&#243;n se compararon los vol&#250;menes derivados con los GTV generados manualmente&#44; utilizando RM &#40;GTV<span class="elsevierStyleInf">MR</span>&#41;&#46;</p> <span class="elsevierStyleSectionTitle">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">El valor medio de GTV<span class="elsevierStyleInf">2SD</span>&#44; GTV<span class="elsevierStyleInf">40&#37;</span> y GTV<span class="elsevierStyleInf">50&#37;</span> fue de 85&#44;3 cc&#59; 16&#44;2 cc y 24&#44;1 cc&#44; respectivamente&#46; Se hall&#243; una buena concordancia entre GTV<span class="elsevierStyleInf">2SD</span> y GTV<span class="elsevierStyleInf">MR</span> &#40;<span class="elsevierStyleItalic">&#961;</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;88&#41;&#46; GTV<span class="elsevierStyleInf">40&#37;</span> y GTV<span class="elsevierStyleInf">50&#37;</span> mostraron una menor correlaci&#243;n con GTV<span class="elsevierStyleInf">MR</span> &#40;<span class="elsevierStyleItalic">&#961;</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;68 y <span class="elsevierStyleItalic">&#961;</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;71&#44; respectivamente&#41;&#46;</p> <span class="elsevierStyleSectionTitle">Conclusiones</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Este estudio prueba de modo preliminar que la delimitaci&#243;n del volumen tumoral metab&#243;lico es posible utilizando las mediciones generadas inform&#225;ticamente en las im&#225;genes de <span class="elsevierStyleSup">18</span>F-FDG PET&#46; La generaci&#243;n de los vol&#250;menes tumorales basados en PET se ve afectada por la elecci&#243;n del nivel de umbral utilizado&#46; El grueso del tumor metab&#243;lico calculado utilizando el p&#237;xel con el valor medio m&#225;s 2 desviaciones de la intensidad del h&#237;gado &#40;GTV<span class="elsevierStyleInf">2SD</span>&#41; guarda una mejor correlaci&#243;n con los vol&#250;menes tumorales derivados de RM&#46; El m&#233;todo constituye un enfoque simple y cl&#237;nicamente aplicable para generar el GTV derivado del PET&#44; para la planificaci&#243;n de la terapia de radiaci&#243;n del c&#225;ncer cervical&#46;</p>"
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          "leyenda" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleItalic">Note</span>&#58; WHO&#58; World Health Association&#59; FIGO&#58; International Federation of Gynecology and Obstetrics&#46;</p>"
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleHsp" style=""></span>IIIA&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">2 &#40;6&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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      "titulo" => "References"
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        0 => array:2 [
          "identificador" => "bibs0005"
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            0 => array:3 [
              "identificador" => "bib0005"
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                0 => array:1 [
                  "referenciaCompleta" => "WHO projections of mortality and burden of disease&#44; 2002&#8211;2030&#46; <a class="elsevierStyleInterRef" href="http://www.who.int/entity/healthinfo/global_burden_disease/Dth6_2008_20090416.xls">http&#58;&#47;&#47;www&#46;who&#46;int&#47;entity&#47;healthinfo&#47;global&#95;burden&#95;disease&#47;Dth6&#95;2008&#95;20090416&#46;xls</a> &#91;last access on 15&#46;01&#46;2011&#93;&#46;"
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              "identificador" => "bib0010"
              "etiqueta" => "2"
              "referencia" => array:1 [
                0 => array:1 [
                  "referenciaCompleta" => "SEER Cancer Statistics Review&#44; 1975&#8211;2006&#44; National Cancer Institute&#44; Bethesda&#44; MD&#46; <a class="elsevierStyleInterRef" href="http://seer.cancer.gov/csr/1975_2006/results_single/sect_01_table.01.pdf">http&#58;&#47;&#47;seer&#46;cancer&#46;gov&#47;csr&#47;1975&#95;2006&#47;results&#95;single&#47;sect&#95;01&#95;table&#46;01&#46;pdf</a> &#91;last access on 15&#46;01&#46;2011&#93;&#46;"
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            2 => array:3 [
              "identificador" => "bib0015"
              "etiqueta" => "3"
              "referencia" => array:1 [
                0 => array:1 [
                  "referenciaCompleta" => "Ministry of Health&#44; Brazil&#46; Secretariat for Health Assistance&#44; National Cancer Institute&#44; Prevention and Surveillance Coordination Unit&#46; Estimate 2010&#58; Brazilian Cancer Incidence&#46; <a class="elsevierStyleInterRef" href="http://www.inca.gov.br/estimativa/2010/estimativa20091201.pdf">http&#58;&#47;&#47;www&#46;inca&#46;gov&#46;br&#47;estimativa&#47;2010&#47;estimativa20091201&#46;pdf</a>"
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                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "NCCN task force&#58; clinical utility of PET in a variety of tumor types"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
                            0 => "D&#46;A&#46; Podoloff"
                            1 => "D&#46;W&#46; Ball"
                            2 => "E&#46; Ben-Josef"
                            3 => "A&#46;B&#46; Benson 3rd"
                            4 => "S&#46;J&#46; Cohen"
                            5 => "R&#46;E&#46; Coleman"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:1 [
                      "Revista" => array:7 [
                        "tituloSerie" => "J Natl Compr Canc Netw"
                        "fecha" => "2009"
                        "volumen" => "7"
                        "numero" => "Suppl&#46; 2"
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                        "paginaFinal" => "S26"
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                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/19878635"
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                ]
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                0 => array:2 [
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                    0 => array:2 [
                      "titulo" => "Tumor biology-guided radiotherapy treatment planning&#58; gross tumor volume versus functional tumor volume"
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                        0 => array:2 [
                          "etal" => false
                          "autores" => array:4 [
                            0 => "C&#46; Guha"
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                            2 => "M&#46;D&#46; Blaufox"
                            3 => "S&#46; Kalnicki"
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                    0 => array:2 [
                      "titulo" => "Impact of manual and automated interpretation of fused PET&#47;CT data on esophageal target definition in radiation planning"
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                        0 => array:2 [
                          "etal" => false
                          "autores" => array:4 [
                            0 => "T&#46;S&#46; Hong"
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                            2 => "M&#46; Mamede"
                            3 => "H&#46;J&#46; Mamon"
                          ]
                        ]
                      ]
                    ]
                  ]
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                    0 => array:2 [
                      "doi" => "10.1016/j.ijrobp.2008.07.061"
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                        "tituloSerie" => "Int J Radiat Oncol Biol Phys"
                        "fecha" => "2008"
                        "volumen" => "72"
                        "paginaInicial" => "1612"
                        "paginaFinal" => "1618"
                        "link" => array:1 [
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                            "web" => "Medline"
                          ]
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              "identificador" => "bib0035"
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                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Impact of FDG-PET&#47;CT on radiotherapy volume delineation in non-small-cell lung cancer and correlation of imaging stage with pathologic findings"
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                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
                            0 => "S&#46;L&#46; Faria"
                            1 => "S&#46; Menard"
                            2 => "S&#46; Devic"
                            3 => "C&#46; Sirois"
                            4 => "L&#46; Souhami"
                            5 => "R&#46; Lisbona"
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                      ]
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                        "paginaInicial" => "1035"
                        "paginaFinal" => "1038"
                        "link" => array:1 [
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                            "web" => "Medline"
                          ]
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                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "18FDG-PET based radiation planning of mediastinal lymph nodes in limited disease small cell lung cancer changes radiotherapy fields&#58; a planning study"
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                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
                            0 => "J&#46; van Loon"
                            1 => "C&#46; Offermann"
                            2 => "G&#46; Bosmans"
                            3 => "R&#46; Wanders"
                            4 => "A&#46; Dekker"
                            5 => "J&#46; Borger"
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                      "titulo" => "PET&#47;CT imaging to guide cervical cancer therapy"
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                        0 => array:2 [
                          "etal" => false
                          "autores" => array:1 [
                            0 => "P&#46;W&#46; Grisby"
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                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.2217/fon.09.70"
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                        "tituloSerie" => "Future Oncol"
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                        "volumen" => "5"
                        "paginaInicial" => "953"
                        "paginaFinal" => "958"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/19792965"
                            "web" => "Medline"
                          ]
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                    ]
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                ]
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                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Utility of PET-CT on radiotherapy planning of head and neck cancer&#46; Our initial experience"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
                            0 => "M&#46;E&#46; Bell&#243;n Guardia"
                            1 => "L&#46; P&#233;rez Romasanta"
                            2 => "A&#46;M&#46; Garc&#237;a Vicente"
                            3 => "M&#46;P&#46; Talavera Rubio"
                            4 => "A&#46; Palomar Mu&#241;oz"
                            5 => "B&#46; Gonz&#225;lez Garc&#237;a"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1016/j.remn.2010.03.005"
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                        "tituloSerie" => "Rev Esp Med Nucl"
                        "fecha" => "2010"
                        "volumen" => "29"
                        "paginaInicial" => "157"
                        "paginaFinal" => "164"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/20494489"
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                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Evaluation of different methods of 18F-FDG-PET target volume delineation in the radiotherapy of head and neck cancer"
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                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
                            0 => "C&#46; Greco"
                            1 => "S&#46;A&#46; Nehmeh"
                            2 => "H&#46; Sch&#246;der"
                            3 => "M&#46; G&#246;nen"
                            4 => "B&#46; Raphael"
                            5 => "H&#46;E&#46; Stambuk"
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                        ]
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                    ]
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                        "paginaFinal" => "445"
                        "link" => array:1 [
                          0 => array:2 [
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              "identificador" => "bib0060"
              "etiqueta" => "12"
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                    0 => array:2 [
                      "titulo" => "Correlation of PET standard uptake value and CT window-level thresholds for target delineation in CT-based radiation treatment planning"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => false
                          "autores" => array:5 [
                            0 => "R&#46; Hong"
                            1 => "J&#46; Halama"
                            2 => "D&#46; Bova"
                            3 => "A&#46; Sethi"
                            4 => "B&#46; Emami"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1016/j.ijrobp.2006.09.039"
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                        "tituloSerie" => "Int J Radiat Oncol Biol Phys"
                        "fecha" => "2007"
                        "volumen" => "67"
                        "paginaInicial" => "720"
                        "paginaFinal" => "726"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/17293230"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
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              "identificador" => "bib0065"
              "etiqueta" => "13"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "18F-FDG PET definition of gross tumor volume for radiotherapy of non-small cell lung cancer&#58; is a single standardized uptake value threshold approach appropriate&#63;"
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                        0 => array:2 [
                          "etal" => true
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                            1 => "F&#46;M&#46; Kong"
                            2 => "F&#46; Dehdashti"
                            3 => "J&#46;Y&#46; Jin"
                            4 => "S&#46; Mutic"
                            5 => "I&#46; El Naqa"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:1 [
                      "Revista" => array:6 [
                        "tituloSerie" => "J Nucl Med"
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                        "volumen" => "47"
                        "paginaInicial" => "1808"
                        "paginaFinal" => "1812"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/17079814"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
            13 => array:3 [
              "identificador" => "bib0070"
              "etiqueta" => "14"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Tumor delineation using PET in head and neck cancers&#58; threshold contouring and lesion volumes"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
                            0 => "E&#46;C&#46; Ford"
                            1 => "P&#46;E&#46; Kinahan"
                            2 => "L&#46; Hanlon"
                            3 => "A&#46; Alessio"
                            4 => "J&#46; Rajendran"
                            5 => "D&#46;L&#46; Schwartz"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1118/1.2361076"
                      "Revista" => array:6 [
                        "tituloSerie" => "Med Phys"
                        "fecha" => "2006"
                        "volumen" => "33"
                        "paginaInicial" => "4280"
                        "paginaFinal" => "4288"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/17153406"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
            14 => array:3 [
              "identificador" => "bib0075"
              "etiqueta" => "15"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Phase I trial of erlotinib combined with cisplatin and radiotherapy for patients with locally advanced cervical squamous cell cancer"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
                            0 => "A&#46; Nogueira-Rodrigues"
                            1 => "C&#46;C&#46; do Carmo"
                            2 => "C&#46; Viegas"
                            3 => "F&#46; Erlich"
                            4 => "C&#46; Camis&#227;o"
                            5 => "K&#46; Font&#227;o"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1158/1078-0432.CCR-07-5112"
                      "Revista" => array:6 [
                        "tituloSerie" => "Clin Cancer Res"
                        "fecha" => "2008"
                        "volumen" => "14"
                        "paginaInicial" => "6324"
                        "paginaFinal" => "6329"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/18829516"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
            15 => array:3 [
              "identificador" => "bib0080"
              "etiqueta" => "16"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Erlotinib &#40;E&#41; combined with cisplatin &#40;C&#41; and radiotherapy &#40;RT&#41; for patients with locally advanced squamous cell cervical cancer&#58; a phase II trial"
                      "autores" => array:1 [
                        0 => array:2 [
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                            1 => "F&#46; Erlich"
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                            4 => "K&#46; Font&#227;o"
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                        ]
                      ]
                    ]
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                        "tituloSerie" => "J Clin Oncol"
                        "fecha" => "2008"
                        "volumen" => "26"
                        "numero" => "Suppl&#46;"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/18445848"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
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              "identificador" => "bib0085"
              "etiqueta" => "17"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Medical image processing&#44; analysis and visualization in clinical research &#40;abstract&#41;"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => false
                          "autores" => array:6 [
                            0 => "M&#46;J&#46; McAuliffe"
                            1 => "F&#46;M&#46; Lalonde"
                            2 => "D&#46; McGarry"
                            3 => "W&#46; Gandler"
                            4 => "K&#46; Csaky"
                            5 => "B&#46;L&#46; Trus"
                          ]
                        ]
                      ]
                    ]
                  ]
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                    0 => array:1 [
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                        "titulo" => "CBMS&#8217;01&#58; proceedings of the 14th IEEE symposium on computer-based medical systems"
                        "paginaInicial" => "381"
                        "conferencia" => "Los Alamitos&#44; CA"
                        "serieFecha" => "2001"
                      ]
                    ]
                  ]
                ]
              ]
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                0 => array:2 [
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                    0 => array:2 [
                      "titulo" => "Pre-operative estimation of esophageal tumor metabolic length in FDG-PET images with surgical pathology confirmation"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => false
                          "autores" => array:6 [
                            0 => "M&#46; Mamede"
                            1 => "G&#46; El Fakhri"
                            2 => "P&#46; Abreu-e-Lima"
                            3 => "W&#46; Gandler"
                            4 => "V&#46; Nos&#233;"
                            5 => "V&#46;H&#46; Gerbaudo"
                          ]
                        ]
                      ]
                    ]
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                    0 => array:2 [
                      "doi" => "10.1007/s12149-007-0040-0"
                      "Revista" => array:6 [
                        "tituloSerie" => "Ann Nucl Med"
                        "fecha" => "2007"
                        "volumen" => "21"
                        "paginaInicial" => "553"
                        "paginaFinal" => "562"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/18092131"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
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              "identificador" => "bib0095"
              "etiqueta" => "19"
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                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Comparison of different methods for delineation of 18F-FDG PET-positive tissue for target volume definition in radiotherapy of patients with non-small cell lung cancer"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
                            0 => "U&#46; Nestle"
                            1 => "S&#46; Kremp"
                            2 => "A&#46; Schaefer-Schuler"
                            3 => "C&#46; Sebastian-Welsch"
                            4 => "D&#46; Hellwig"
                            5 => "C&#46; R&#252;be"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:1 [
                      "Revista" => array:6 [
                        "tituloSerie" => "J Nucl Med"
                        "fecha" => "2005"
                        "volumen" => "46"
                        "paginaInicial" => "1342"
                        "paginaFinal" => "1348"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/16085592"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
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              "identificador" => "bib0100"
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                0 => array:2 [
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                    0 => array:2 [
                      "titulo" => "The contribution of 18F-fluoro-2-deoxy-glucose positron emission tomographic imaging to radiotherapy planning in lung cancer"
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                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
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                            2 => "A&#46;M&#46; Scott"
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                            5 => "C&#46; R&#252;be"
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                        ]
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                    ]
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                        "paginaInicial" => "167"
                        "paginaFinal" => "177"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/9631364"
                            "web" => "Medline"
                          ]
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                      ]
                    ]
                  ]
                ]
              ]
            ]
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                    0 => array:2 [
                      "titulo" => "Implementing biologic target volumes in radiation treatment planning for non-small cell lung cancer"
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                          "etal" => false
                          "autores" => array:4 [
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                            2 => "F&#46; Dehdashti"
                            3 => "B&#46;A&#46; Siegel"
                          ]
                        ]
                      ]
                    ]
                  ]
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                      "Revista" => array:7 [
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                        "fecha" => "2004"
                        "volumen" => "45"
                        "numero" => "Suppl&#46;"
                        "paginaInicial" => "96S"
                        "paginaFinal" => "101S"
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Article information

ISSN: 2253654X
Original language: English

DOI:10.1016/j.remn.2012.06.003

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Year/Month	Html	Pdf	Total

2023 March	1	0	1
2021 September	1	0	1
2018 February	7	0	7
2018 January	8	0	8
2017 December	9	0	9
2017 November	12	0	12
2017 October	13	1	14
2017 September	10	2	12
2017 August	13	2	15
2017 July	14	1	15
2017 June	16	12	28
2017 May	14	3	17
2017 April	22	3	25
2017 March	17	13	30
2017 February	16	2	18
2017 January	16	3	19
2016 December	13	4	17
2016 November	21	5	26
2016 October	47	5	52
2016 September	34	6	40
2016 August	22	3	25
2016 July	24	1	25
2016 June	23	3	26
2016 May	17	8	25
2016 April	7	8	15
2016 March	12	15	27
2016 February	16	12	28
2016 January	25	14	39
2015 December	21	11	32
2015 November	19	13	32
2015 October	28	18	46
2015 September	21	6	27
2015 August	33	8	41
2015 July	30	3	33
2015 June	5	2	7
2015 May	18	3	21
2015 April	21	9	30
2015 March	17	7	24
2015 February	11	1	12
2015 January	7	2	9
2014 December	23	4	27
2014 November	11	0	11
2014 October	28	4	32
2014 September	16	1	17
2014 August	13	4	17
2014 July	13	1	14
2014 June	19	1	20
2014 May	12	4	16
2014 March	0	1	1
2014 February	1	1	2
2014 January	1	2	3
2013 October	0	1	1
2013 August	0	3	3
2013 July	5	0	5
2013 June	3	1	4
2013 May	4	0	4
2013 April	180	0	180

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