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Original Article
An initial study on the comparison of diagnostic performance of 18F-FDG PET/MR and 18F-FDG PET/CT for thoracic staging of non-small cell lung cancer: Focus on pleural invasion
Estudio inicial sobre la comparación del rendimiento diagnóstico de la PET/RM con 18F-FDG y la PET/TC con 18F-FDG para la estadificación torácica del cancer de pulmón de células no pequeñas: enfoque en la invasión pleural
Ma-li Wanga,b,c, He Zhanga,b,c, Hao-jun Yua,b,c, Hui Tana,b,c, Ling-zhi Hud, Han-jing Konge, Wu-jian Maoa,b,c, Jie Xiaoa,b,c, Hong-cheng Shia,b,c,
Corresponding author
shi.hongcheng@zs-hosptal.sh.cn

Corresponding author at: Department of Nuclear Medicine, Zhongshan Hospital, 180 Fenglin Rd., Shanghai, China.
a Department of Nuclear Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
b Nuclear Medicine Institute of Fudan University, Shanghai, China
c Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
d United Imaging Research, Shanghai, China
e Central Research Institute, UIH Group, Beijing, China
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            "etiqueta" => "c"
            "identificador" => "aff0015"
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            "etiqueta" => "d"
            "identificador" => "aff0020"
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            "correspondencia" => "Corresponding author at&#58; Department of Nuclear Medicine&#44; Zhongshan Hospital&#44; 180 Fenglin Rd&#46;&#44; Shanghai&#44; China&#46;"
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        "titulo" => "Estudio inicial sobre la comparaci&#243;n del rendimiento diagn&#243;stico de la PET&#47;RM con <span class="elsevierStyleSup">18</span>F-FDG y la PET&#47;TC con <span class="elsevierStyleSup">18</span>F-FDG para la estadificaci&#243;n tor&#225;cica del cancer de pulm&#243;n de c&#233;lulas no peque&#241;as&#58; enfoque en la invasi&#243;n pleural"
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          "en" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Distribution of the different T and N stages and the corresponding ratings in PET&#47;CT and PET&#47;MRI&#46;</p>"
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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Non-small cell lung cancer&#44; accounting for 75&#8211;80&#37;<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a> of all lung cancer occurrences&#44; is the most commonly diagnosed cancer worldwide and the leading cause of tumor-related deaths&#46;<a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">2</span></a> For NSCLC patients&#44; accurate staging based on imaging plays an important role in treatment and prognosis&#46; Thoracic contrast-enhanced CT &#40;CE-CT&#41; has been widely used to evaluate locoregional staging&#44; thanks to its high spatial resolution and fast acquisition within a breath hold&#46; However&#44; CE-CT is challenging to differentiate malignancy from reactive adenopathy and for detecting distant metastasis&#46; With its growing clinical adoption&#44; 2-Deoxy-2-&#91;<span class="elsevierStyleSup">18</span>F&#93; fluoroglucose &#40;FDG&#41; positron emission tomography&#47;computed tomography <span class="elsevierStyleSup">&#40;</span>PET&#47;CT&#41; is widely regarded as the first-line staging modality with excellent diagnostic accuracy for lung cancer&#46; However&#44; differentiating malignancy from reactive adenopathy is also difficult with PET&#47;CT&#44; while no major difference is known in detecting distant metastases at primary staging for NSCLC patients compared to CE-CT&#46; The main advantage of PET&#47;CT is focused on the exclusion of mediastinal lymph node metastases&#46;<a class="elsevierStyleCrossRefs" href="#bib0015"><span class="elsevierStyleSup">3&#44;4</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Because of inadequate soft tissue contrast and frequent false-positive findings from the PET component&#44; <span class="elsevierStyleSup">18</span>F-FDG PET&#47;CT has limitations in detecting tumor invasion of the adjacent pleura&#44; chest wall&#44; mediastinal structures&#44; and thus hinders correct thoracic staging of NSCLC&#46;<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a> In comparison to PET&#47;CT&#44; integrated Positron emission tomography&#47;magnetic resonance &#40;PET&#47;MR&#41; features superior soft tissue contrast and less radiation exposure&#46; With dedicated thoracic MRI sequences&#44; PET&#47;MR is expected to manifest a better diagnostic performance in assessing mediastinal infiltration&#44; visceral or parietal pleural infiltration&#44; infiltration of the pericardium&#44; infiltration of the diaphragm&#44; infiltration of the brachial plexus&#44; and infiltration of the fissure&#47;adjacent lobe&#46; A retrospective study<a class="elsevierStyleCrossRef" href="#bib0030"><span class="elsevierStyleSup">6</span></a> analyzed a cohort of 28 patients and found that with motion-insensitive T2 BLADE sequence &#40;also known as PROPELLER or T2 ARMS&#41;&#44; PET&#47;MR demonstrated a higher diagnostic accuracy in the T stage than PET&#47;CT&#46; Additionally&#44; motion-insensitive radial sampling technology&#44; T2 ARMS<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">7</span></a> is an efficient acquisition and reconstruction technique that allows motion correction and was integrated into the thoracic MRI protocol imaging&#46; Furthermore&#44; functional MRI sequences such as DWI effectively improves the identification of malignant lymphadenopathy&#46;<a class="elsevierStyleCrossRef" href="#bib0040"><span class="elsevierStyleSup">8</span></a> However other recent studies<a class="elsevierStyleCrossRefs" href="#bib0025"><span class="elsevierStyleSup">5&#44;9&#8211;12</span></a> showed that PET&#47;MR was an equivalent alternative to PET&#47;CT for the thoracic staging of NSCLC&#44; without delivering any benefit&#46; Ohno et al&#46;<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a> conducted a prospective study on 104 NSCLC patients and found that the use of whole-body MR &#40;3&#46;0-T and 1&#46;5-T&#41;&#44; PET&#47;MRI &#40;3&#46;0-T and 1&#46;5-T&#41; and PET&#47;CT were accurate in assessing T staging&#46; The degree of PET&#47;MR is similar or even better&#44; and the difference between 3-T and 1&#46;5-TMRI systems is not significant&#46; In Xu et al&#46;&#44;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a> the authors reported that PET&#47;MR had more accurate image matching in lung tumor imaging and could locate the tumor body more accurately&#44; which implies a more accurate imaging method for delineating target areas for radiotherapy &#40;p&#8239;&#60;&#8239;0&#46;05&#41;&#46; Generally&#44; current evidence is still insufficient for using PET&#47;MR to evaluate the direct invasion of the pleura and pleural metastasis&#46;</p><p id="par0015" class="elsevierStylePara elsevierViewall">Therefore&#44; the aim of our study was to retrospectively compare the diagnostic performance of PET&#47;MR and PET&#47;CT in the thoracic staging of NSCLC&#44; and for the first time investigate the unique value of PET&#47;MR for pleural invasion evaluation&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Materials &#38; methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Patient population</span><p id="par0020" class="elsevierStylePara elsevierViewall">From September 2019 to August 2020&#44; 52 patients &#40;18 female&#44; 37 male&#44; mean age 61&#8239;&#177;&#8239;8 y&#41; that underwent whole-body <span class="elsevierStyleSup">18</span>F-FDG PET&#47;CT and subsequent thoracic <span class="elsevierStyleSup">18</span>F-FDG PET&#47;MR for accurate T and N staging of NSCLC &#40;adenocarcinoma&#58; n&#8239;&#61;&#8239;41&#44; squamous cell carcinoma&#58; n&#8239;&#61;&#8239;10&#44; adeno-squamous carcinoma&#58; n&#8239;&#61;&#8239;1&#41;&#44; without injecting contrast agent&#44; were retrospectively enrolled in this study&#46; None received neoadjuvant therapy&#46; Following the imaging&#44; 6&#46;3&#8239;&#177;&#8239;5&#46;5 days after <span class="elsevierStyleSup">18</span>F-FDG PET&#47;CT and PET&#47;MR scans&#44; all patients underwent lung cancer surgeries &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;&#44; and pathology analysis&#46; All of the resection specimens as the reference standard were available for the T and N stage in all patients&#46; The patient selection process is shown in <a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>&#46; Besides&#44; 52 patients&#8217; subsequent treatment was followed up for another year&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0025" class="elsevierStylePara elsevierViewall">This study was approved by the ethics committee of Zhongshan Hospital of Fudan University&#46; Written informed consent was obtained from all patients prior to image acquisition&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">F-FDG PET&#47;CT acquisition</span><p id="par0030" class="elsevierStylePara elsevierViewall">The patients received only one injection of <span class="elsevierStyleSup">18</span>F-FDG according to body weight &#40;3&#46;1&#8239;&#177;&#8239;1&#46;2&#8239;M&#8239;Bq&#47;kg&#41; after fasting for at least 6&#8239;h&#46; Blood glucose levels were verified to be below 150&#8239;mg&#47;dl at the time of tracer injection&#46;</p><p id="par0035" class="elsevierStylePara elsevierViewall">Whole-body <span class="elsevierStyleSup">18</span>F-FDG PET&#47;CT&#40;free breathing&#41; was performed on uMI550 PET&#47;CT scanner &#40;United Imaging Healthcare&#44; Shanghai&#44; China&#41; for 9 patients&#44; uMI780 PET&#47;CT scanner &#40;United Imaging Healthcare&#44; Shanghai&#44; China&#41; for 14 patients&#44; 194-cm-long transverse FOV total-body PET&#47;CT &#40;uEXPLORER&#44; United Imaging Healthcare&#44; Shanghai&#44; China&#41; for 26 patients and Discovery VCT &#40;GE Healthcare&#44; Milwaukee&#44; Wisconsin&#44; USA&#41; for 3 patients&#46; The scan range of PET was from skull base to upper thighs&#46; Images were acquired 2&#8239;min&#47;bed for all scanners&#44; except for uEXPLORER &#40;15&#8239;min&#47;bed&#41; which used a single bed position due to its long axial coverage&#46; All PET images were reconstructed using the ordered subsets expectation maximization &#40;OSEM&#41; algorithm with 2 iterations and 20 subsets&#44; for all PET systems except uEXPLORER&#44; which used 3 iterations and 20 subsets&#46; The CT scan parameters were as follows&#58; Discovery VCT &#40;120&#8239;mA&#59; 140&#8239;kV&#59; pitch&#44; 0&#46;516&#8239;mm&#59; slice thickness&#44; 1&#46;25&#8239;mm&#41;&#44; uMI550 &#40;120&#8239;mA&#59; 140&#8239;kV&#59; pitch&#44; 0&#46;975&#8239;mm&#59; slice thickness&#44; 1&#46;5&#8239;mm&#41;&#44; uMI780 &#40;120&#8239;mA&#59; 140&#8239;kV&#59; pitch&#44; 0&#46;9875&#8239;mm&#59; slice thickness&#44; 1&#8239;mm&#41;&#44; uEXPLORER &#40;120&#8239;mA&#59; 140&#8239;kV&#59; pitch&#44;0&#46;9875&#8239;mm&#59; slice thickness&#44; 3&#8239;mm&#41;&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">F-FDG PET&#47;MR acquisition</span><p id="par0040" class="elsevierStylePara elsevierViewall">Thoracic <span class="elsevierStyleSup">18</span>F-FDG PET&#47;MR examinations were performed using an integrated 3-Tesla PET&#47;MR scanner &#40;uPMR 790&#44; United Imaging Healthcare&#44; Shanghai&#44; China&#41; with a mean delay of 167&#8239;&#177;&#8239;62&#8239;min after <span class="elsevierStyleSup">18</span>F-FDG injection&#46; The PET acquisition of the thorax was performed for one bed position &#40;acquisition time&#58;15&#8239;min&#44; reconstruction algorithms&#58; OSEM&#44; iteration&#58; 2&#44; subset numbers&#58; 20&#44; Gaussian filter&#58; 3&#8239;mm FWHM&#44; image matrix&#58; 256&#8239;&#215;&#8239;256&#41;&#46; For MR-based attenuation correction&#44; a 3D Dixon sequence was performed to generate a four-compartment model &#40;air&#44; lungs&#44; fat&#44; and muscle&#41;&#46; The thoracic MRI protocol was performed according to the current imaging guidelines for lung cancer&#46; Detailed PET&#47;MR sequence parameters are summarized in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#46;</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Image analysis</span><p id="par0045" class="elsevierStylePara elsevierViewall">Thoracic tumor staging for all NSCLC patients was assessed by two independent radiologists&#44; who were aware of patients&#8217; lung cancer diagnosis but blind to all other clinical data&#44; in separate sessions &#40;4 weeks&#41; according to the 8th edition of the American Joint Committee on Cancer staging manual&#46;<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a> Discrepant findings were resolved by discussion&#46;</p><p id="par0050" class="elsevierStylePara elsevierViewall">The gold-standard for the comparison parameters was the anatomopathological results&#44; for example&#44; in lesion size discrepancies&#46; Several factors were taken into consideration for locoregional T staging&#44; including tumor size&#44; pleural infiltration&#44; infiltration of the chest wall&#44; mediastinal infiltration&#44; infiltration of the carina of trachea or pericardium&#44; infiltration of the diaphragm or brachial plexus&#44; infiltration of the fissure&#47;adjacent lobe and presence of additional nodules&#46;<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">10</span></a></p><p id="par0055" class="elsevierStylePara elsevierViewall">Pleural involvement often appears as&#58; 1&#46; pleural thickening around the tumor&#44; 2&#46; discontinuity of the pleura&#44; 3&#46; pleural lesion with an increase of tracer uptake&#44; 4&#46; restricted diffusion of thickening pleura in DWI&#44; 5&#46; malignant pleura effusion&#46; Seok et al&#46;<a class="elsevierStyleCrossRefs" href="#bib0080"><span class="elsevierStyleSup">16&#44;17</span></a> concluded that&#44; in some solid nodules&#44; CT features of pleural contact&#44; pleural thickening&#44; a solid proportion &#62;50&#37;&#44; and nodal size &#40;&#62;2&#8239;cm&#41; were significant predictors of visceral pleural invasion&#40;VPI&#41;in T1 peripheral adenocarcinoma&#46;</p><p id="par0060" class="elsevierStylePara elsevierViewall">Morphological and metabolic signs of lymph nodes metastasis included&#58;1&#46; increased short-axis diameter &#40;such as more than 8&#8239;mm&#41;&#44; 2&#46; central necrosis&#44; 3&#46; irregular shape&#44; 4&#46; lack of a fatty hilus sign&#44; 5&#46; increased radiotracer uptake&#46;<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">9</span></a></p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Statistical analysis</span><p id="par0065" class="elsevierStylePara elsevierViewall">Data analysis was performed using IBM SPSS Statistics 25&#8482; &#40;IBM&#44; Armonk&#44; NY&#44; USA&#41; and MATLAB 2020a &#40;MathWorks&#44; Natick&#44; MA&#41;&#46; Descriptive analysis was performed and the data are presented as mean&#8239;&#177;&#8239;SD&#46; A McNemar Chi-square Test was performed to investigate whether differences in the evaluations of the correct T stage&#44; N stage as well as pleural involvement between <span class="elsevierStyleSup">18</span>F-FDG PET&#47;CT and <span class="elsevierStyleSup">18</span>F-FDG PET&#47;MRI were statistically significant&#46; The area under the receiver-operating-characteristic curve was calculated and fitted for sensitivity and specificity&#46; For the comparison of SUV<span class="elsevierStyleInf">max</span> between <span class="elsevierStyleSup">18</span>F-FDG PET&#47;CT and PET&#47;MRI&#44; a Wilcoxon signed-rank test was applied&#46; A p-value of less than 0&#46;05 was used to indicate statistical significance&#46;</p></span></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Results</span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">T staging</span><p id="par0070" class="elsevierStylePara elsevierViewall">The distribution of T stages in the 52 patients confirmed by pathology were T1 in 26 patients&#44; T2a in 14 patients&#44; T2b in 8 patients&#44; T3 in 3 patients&#44; and T4 in one patient &#40;<a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>&#41;&#46; Concordant T staging results were observed between thoracic <span class="elsevierStyleSup">18</span>F-FDG PET&#47;CT and <span class="elsevierStyleSup">18</span>F-FDG PET&#47;MR in 82&#46;7 &#37; &#40;43 patients&#41;&#44; discrepancies in thoracic tumor staging were observed in 17&#46;3&#37; &#40;9 patients&#41;&#46; Three cases were misdiagnosed by PET&#47;MR because of errors with the measurements &#40;2 cases larger&#44; one smaller&#41;&#46; The detectability of pulmonary nodules in PET&#47;MR was relatively inferior to PET&#47;CT&#44; resulting in missing pulmonary lesions for 3 patients&#44; of which one had no impact in the patient&#8217;s assessment&#46; Moreover&#44; 3 cases were correctly rated in the determination of pleural invasion only by PET&#47;MR rather than PET&#47;CT&#46;</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia><p id="par0075" class="elsevierStylePara elsevierViewall">The overall accuracies of thoracic T staging on PET&#47;MR and PET&#47;CT were 84&#46;6 &#37; &#40;44&#47;52&#41; and 82&#46;7 &#37; &#40;43&#47;52&#41; &#40;<span class="elsevierStyleItalic">p</span>&#8239;&#62;&#8239;0&#46;05&#41; with resection specimens of the primary lesion used as a reference standard&#46; T stage was overestimated by both modalities in two identical patients&#44; in 2 additional patients in PET&#47;MR only and in 2 additional patients in PET&#47;CT only&#46; In terms of T stage&#44; both modalities underestimated in 3 patients while in one patient by PET&#47;MR only and two by PET&#47;CT only&#46; The Bland&#8211;Altmann analysis shows the lower and upper limits of agreement between PET&#47;MRI and PET&#47;CT for primary tumor&#8217;s SUV<span class="elsevierStyleInf">max</span> &#40;see <a class="elsevierStyleCrossRef" href="#fig0015">Fig&#46; 3</a>&#41;&#44; but regression analysis revealed no systematic bias between the measurements of PET&#47;CT and PET&#47;MRI&#44; just a fixed difference between the measurements&#46;</p><elsevierMultimedia ident="fig0015"></elsevierMultimedia></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">N staging</span><p id="par0080" class="elsevierStylePara elsevierViewall">With respect to nodal stages&#44; there were N0 in 43 patients&#44; N1 in 4 patients&#44; N2 in 5 patients&#46; Among the 52 patients&#44; 46 patients &#40;88&#46;5&#37;&#41; were correctly diagnosed via both modalities&#46; N stage was underrated in 5 identical patients and overrated in one patient by both modalities&#46; There were no significant differences in the accuracy of nodal staging between PET&#47;CT and PET&#47;MR &#40;<span class="elsevierStyleItalic">p</span>&#8239;&#61;&#8239;1&#46;000&#41;&#46;</p></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Pleural invasion</span><p id="par0085" class="elsevierStylePara elsevierViewall">Among 52 patients&#44; there were 3 cases in which PET&#47;MR showed superiority in determining pleural invasion and allowing correct up-stage&#46;</p><p id="par0090" class="elsevierStylePara elsevierViewall">Meanwhile&#44; 11 tumors of 52 cases were confirmed to have visceral pleural invasion by pathology &#40;10 solid nodule&#44; 1 part-solid nodule&#41;&#46; 49 of 52 cases were correctly rated in the determination of pleural invasion by PET&#47;MR &#40;1 false negative and 2 false positives&#41;&#46; PET&#47;CT accurately rated 46 cases in the determination of pleural invasion &#40;2 false negatives and 4 false positives&#41;&#46; PET&#47;MR exhibited higher sensitivity&#44; specificity in the detection of pleural invasion&#59; 82 &#37; vs&#46; 64&#37; &#40;<span class="elsevierStyleItalic">p</span>&#8239;&#61;&#8239;0&#46;625&#41;&#44; 98 &#37; vs&#46; 95&#37; &#40;<span class="elsevierStyleItalic">p</span>&#8239;&#61;&#8239;1&#46;000&#41;&#44; PET&#47;MR to PET&#47;CT respectively&#46; More details are attached to <a class="elsevierStyleCrossRefs" href="#tbl0015">Tables 3 and 4</a>&#46; The receiver-operating-characteristic &#40;ROC&#41; curve of diagnostic accuracy of PET&#47;CT vs PET&#47;MR for the pleural invasion is summarized in <a class="elsevierStyleCrossRef" href="#fig0020">Fig&#46; 4</a> &#40;AUC<span class="elsevierStyleInf">PET&#47;CT</span>&#8239;&#61;&#8239;0&#46;79 &#91;95&#37; confidence interval&#58; 0&#46;78&#8211;1&#46;00&#93;&#44; AUC<span class="elsevierStyleInf">PET&#47;MR</span>&#8239;&#61;&#8239;0&#46;90 &#91;95&#37; confidence interval&#58; 0&#46;64&#8722;0&#46;95&#93;&#44; <span class="elsevierStyleItalic">p</span>&#8239;&#61;&#8239;0&#46;21&#41;&#46; However&#44; the difference in sensitivity and specificity between the two imaging techniques was not statistically significant &#40;<span class="elsevierStyleItalic">p</span>&#8239;&#62;&#8239;0&#46;05&#44; each&#41;&#46;</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><elsevierMultimedia ident="tbl0020"></elsevierMultimedia><elsevierMultimedia ident="fig0020"></elsevierMultimedia></span></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Discussion</span><p id="par0095" class="elsevierStylePara elsevierViewall">As our study indicated&#44; the diagnostic value of PET&#47;MR for thoracic staging in patients with NSCLC&#44; including detectability of pleural invasion of non-small cell lung cancer&#44; was not significantly different from that of PET&#47;CT according to the 8th edition of the American Joint Committee on Cancer staging manual&#46;</p><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">T staging</span><p id="par0100" class="elsevierStylePara elsevierViewall">Considering the almost equivalent performance of the PET component between PET&#47;MR and PET&#47;CT&#44; MRI is a great contributor to the potentially better diagnostic performance of PET&#47;MR due to its high soft tissue contrast and functional imaging capability&#46; Although our study did not reach statistical significance&#44; there were some indications that PET&#47;MR was superior&#44; particularly for pleural invasion&#46; However&#44; longer examination time and higher cost of PET&#47;MR may compromise the broader implementation of PET&#47;MR in routine clinical practice&#46; In addition&#44; pregnant women&#44; patients under 18 years of age&#44; and patients who were contraindicated for MRI &#40;e&#46; g&#46; patients with pacemakers or claustrophobia&#41;&#44; were also excluded&#46;<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">10</span></a> Recently&#44; new sequences such as Ultrashort echo-time Sequences &#40;UTE&#41;&#44; Zero echo-time Sequences &#40;ZTE&#41; and T2 radial sampling &#40;ARMS&#44; BLADE&#44; PROPELLER&#41; have been developed and applied to enhance lung tissue contrast&#44; and thus may improve the accuracy of NSCLC staging by PET&#47;MR<a class="elsevierStyleCrossRefs" href="#bib0030"><span class="elsevierStyleSup">6&#44;16&#44;17</span></a>&#46; Bae et al&#46;<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> performed thoracic MRI on 20 patients and demonstrated that ZTE sequence images show a better signal-to-noise ratio than UTE &#40;P&#8239;&#60;&#8239;0&#46;05&#41;&#46; It offers better diagnostic accuracy for sub-centimeter lung nodules and a shorter average scan time &#40;131&#8239;s vs 467&#8239;s&#41;&#46; Burris et al&#46;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> compared the effects of PET&#47;MR UTE and conventional gradient echo sequence on detecting lung nodules&#44; suggesting the detection rate of UTE sequence for nodules &#62;4&#8239;mm &#40;regardless of FDG intake or not&#41; was higher than that of the gradient echo sequence&#44; especially in 4&#8722;8&#8239;mm nodules group&#46; Zheng et al&#46;<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">20</span></a> studied 117 lung lesions identified in 113 patients and found that the detectability of PET&#47;ZTE was better than that of PET&#47;Dixon for lesions with a SUV<span class="elsevierStyleInf">max</span> of less than 3&#46;0 or lesions smaller than 4&#8239;mm&#46;</p><p id="par0105" class="elsevierStylePara elsevierViewall">In terms of T staging&#44; our study is generally consistent with Kirchner et al&#46;<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">9</span></a> However&#44; the accuracies of T1 and T2 staging in our study estimated by PET&#47;MR is slightly lower &#40;T1 stage&#44; 92&#46;3&#37; in our study vs&#46; 100 &#37;&#59; T2 stage&#44; 77&#46;3 &#37; in our study vs&#46; 94&#46;1&#37;&#41; than Kirchner et al&#46;<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">9</span></a> This may be caused by the uneven data distribution in our study&#46; For example&#44; 50&#37; of the study population are at T1 stages&#44; there was just one primary lung cancer involving the chest wall and adjacent ribs&#44; and there was relatively fewer central bronchogenic carcinoma adjacent to the hilum&#46; It is worth noting that there was a case missing one tiny solitary pulmonary nodule &#40;longest diameter less than 1&#8239;cm&#44; close to the diaphragm&#41; by PET&#47;MR only&#44; resulting in inappropriate downstage from T3 to T2b&#46; And this demonstrated the inferior detectability of PET&#47;MR for nodules located at the lung basement&#46;</p></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">N staging</span><p id="par0110" class="elsevierStylePara elsevierViewall">Kirchner et al&#46;<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">9</span></a> reported that PET&#47;MR correctly diagnosed the nodal stage in 77 of 84 patients &#40;91&#46;7 &#37;&#41; while PET&#47;CT correctly diagnosed the nodal stage in 78 of 84 patients &#40;92&#46;9 &#37;&#41;&#44; resulting in no significant difference&#46; Our study used dedicated pulmonary MR sequences &#40;including DWI and T2-ARMS accepted widely&#41; and showed similar accuracy &#40;88&#46;5&#37;&#41; for nodal staging on both PET&#47;MR and PET&#47;CT&#46;</p></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Pleural invasion</span><p id="par0115" class="elsevierStylePara elsevierViewall">As is well-known&#44; VPI is a negative independent prognosis factor of NSCLC with tumor size less than 3&#8239;cm and non-size-based T2 factor&#44; regardless of N status &#40;N0 or N1&#47;2&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">21</span></a> VPI was categorized into four degrees &#40;PL1 or PL2 was defined as the presence of VPI&#41;&#58; PL1 represents a tumor invading beyond the elastic layer&#44; but not exposed on the visceral pleural surface&#44; while PL2 represents a tumor invading and exposed on the visceral pleural surface&#44; but not involving adjacent anatomic structures&#46;<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">22</span></a> However&#44; the presence of VPI&#44; rather than the extent&#44; influences postoperative survival in patients with NSCLC&#46;<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">21</span></a> Previous studies manifested that the patients with VPI correlated with a higher incidence of pleural effusion&#44; mediastinal nodal metastasis and postoperative recurrence&#44; leading to optimistic treatment strategies&#44; for instance&#44; postoperative chemotherapy and rational extended resection&#46;<a class="elsevierStyleCrossRefs" href="#bib0105"><span class="elsevierStyleSup">21&#44;23&#44;24</span></a> When general preoperative examination revealed risk factors of VPI or intraoperative exploration suspected the diagnosis of VPI&#44; surgeons were advised to perform a more extensive lymphadenectomy to optimize the survival benefit&#46;<a class="elsevierStyleCrossRef" href="#bib0125"><span class="elsevierStyleSup">25</span></a></p><p id="par0120" class="elsevierStylePara elsevierViewall">Zhao et al&#46;<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">26</span></a> suggested radiological signs&#44; such as nodule abutment or a pleural tag&#44; did not reliably predict or exclude VPI&#46; Because of its high detection of pleural thickening&#44; PET&#47;MR may be helpful to distinguish pleural invasion to choose the best operative way such as nonsublobar resection&#44;<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">27</span></a> especially for solid or subsolid nodules&#46; In our study&#44; results showed that PET&#47;MR has a higher value for pleural involvement evaluation when comparing with PET&#47;CT &#40;<a class="elsevierStyleCrossRef" href="#fig0025">Fig&#46; 5</a>&#41;&#46; 49 of 52 cases were correctly rated in the determination of pleural invasion by PET&#47;MR&#46; PET&#47;MR had a specificity of 98 &#37;&#44; a sensitivity of 82 &#37; and an accuracy of 94&#37;&#46; PET&#47;CT accurately rated 46 cases&#46; The sensitivity&#44; specificity and accuracy of PET&#47;CT were 64&#37;&#44; 95&#37; and 89&#37;&#44; respectively&#46; During one-year follow-up&#44; most of 11 VPI-positive patients chose pulmonary lobectomy instead of pulmonary wedge resection&#44; some even received adjuvant treatment &#40;<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>&#41;&#44; resulting in more optimistic prognosis relatively&#46; However&#44; we believe that the sample size of our study is small&#46; At the same time&#44; few partial solid nodules or ground glass nodules with pleural invasion were included&#46; Therefore&#44; additional prospective studies were warranted to have a larger sample size&#46; On the whole&#44; PET&#47;MR was equivalent to PET&#47;CT in the evaluation of pleural invasion as well as the preoperative staging of patients with non-small cell lung cancer and may be useful to make decisions on choose proper surgery way and adjuvant therapy&#46;</p><elsevierMultimedia ident="fig0025"></elsevierMultimedia><p id="par0125" class="elsevierStylePara elsevierViewall">Finally&#44; our study had several drawbacks&#46; First&#44; the number of patients with a higher stage of lung cancer was small because only patients with clinically resectable status were included&#46; Secondly&#44; our study is a retrospective study with inherent disadvantages such as recognition bias&#46; Thirdly&#44; each PET&#47;CT scanners might have different performance&#44; and we have combined new state-of-art PET&#47;CT &#40;uEXPLORER&#41; with older scanners &#40;GE system&#41; in our study&#46; For instance&#44; different slice thicknesses used among the PET&#47;CT&#39;s were used in this study&#46; The thickness of PET&#47;CT used in many studies is thinner than that of PET&#47;MRI&#44; so the time resolution and signal strength of PET&#47;CT are improved&#44; which may also be one of the reasons for the low detection rate of small pulmonary lesions by PET&#47;MRI&#46;<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">28</span></a> Also&#44; uEXPLORER had a much higher count statistics due to its high sensitivity and use of a single bed position &#40;15&#8239;min&#41;&#44; compared to 2&#8239;min per bed used in the other PET&#47;CT&#39;s&#46; However&#44; our research was using the method of self-comparison with PET&#47;CT and PET&#47;MRI&#44; so the difference among PET&#47;CT scanners used in different patients had less impact&#46; Next&#44; it was only thoracic PET&#47;MRI instead of whole-body PET&#47;MRI utilized because not all patients could tolerate long-time scanning if we used whole-body PET&#47;MRI&#46; In addition&#44; PET&#47;MR was performed after a longer interval than PET&#47;CT&#44; leading to a higher lesion-to-background contrast&#46; Therefore&#44; more lesions may show <span class="elsevierStyleSup">18</span>F-FDG uptake&#44; but it did not improve the overall evaluation of pulmonary lesions&#46;<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">29</span></a> Besides&#44; the regression analysis revealed no systematic bias between the tumor&#8217;s SUV<span class="elsevierStyleInf">max</span> measurements of PET&#47;CT and PET&#47;MRI&#44; which was helpful to prove that the delay had fewer impacts on T staging assessment&#46; At the same time&#44; Yoon et al&#46;<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">30</span></a> thought that the gains in correct N staging with the PET&#47;MR imaging system were attributed to the delayed scanning than an inherent advantage of the MR imaging sequence in detecting metastatic mediastinal lymph nodes&#44; but our study found that PET&#47;MR was equivalent to PET&#47;CT in the preoperative N staging evaluation&#46; A final consideration&#44; which was limited by clinical routine and some patients&#8217; renal function abnormality&#44; contrast media and some advanced sequences such as ZTE were lacked&#46; To a certain degree&#44; it decreased soft tissue contrast of two modalities&#44; leading to relatively lower accuracy for assessing the preoperative staging and pleural invasion of patients with NSCLC&#46;</p></span></span><span id="sec0080" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0140">Conclusions</span><p id="par0130" class="elsevierStylePara elsevierViewall">In conclusion&#44; this study demonstrated that PET&#47;MR was equivalent to PET&#47;CT in the preoperative thoracic staging of NSCLC patients&#46; Our results show that PET&#47;MR may have potential advantages over PET&#47;CT in detecting capacity of pleural invasion of non-small cell lung cancer&#44; which is crucial to clinical decision-making such as rational extended resection and postoperative chemotherapy&#46;</p></span><span id="sec0085" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0145">Funding</span><p id="par0135" class="elsevierStylePara elsevierViewall">This study is supported by the <span class="elsevierStyleGrantSponsor" id="gs0005">Shanghai Municipal Key Clinical Specialty</span> &#40;No&#46; <span class="elsevierStyleGrantNumber" refid="gs0005">shslczdzk03401</span>&#41;&#44; <span class="elsevierStyleGrantSponsor" id="gs0010">Three-year Action Plan of Clinical Skills and Innovation of Shanghai Hospital Development Center</span> &#40;No&#46; <span class="elsevierStyleGrantNumber" refid="gs0010">SHDC2020CR3079B</span> to Hong-cheng Shi&#41;&#44; and the <span class="elsevierStyleGrantSponsor" id="gs0015">Shanghai Science and Technology Committee</span> &#40;No&#46; <span class="elsevierStyleGrantNumber" refid="gs0015">19DZ1930702</span>&#41;&#46; Key research program &#8220;<span class="elsevierStyleGrantSponsor" id="gs0020">Development of Digital Diagnostic and Therapeutic Equipment</span>&#8221; &#40;NO&#46; <span class="elsevierStyleGrantNumber" refid="gs0020">2016YFC0103900</span>&#41;&#44; Ministry of Science and Technology of People&#8217;s Republic of China&#46;</p></span><span id="sec0090" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0150">Conflict of interest</span><p id="par0140" class="elsevierStylePara elsevierViewall">Ling-zhi Hu and Han-jing Kong are employees of United Imaging Research&#46; The other authors working in Zhongshan Hospital have full control of the data&#46; No other potential conflicts of interest relevant to this article exist&#46;</p></span><span id="sec0095" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0155">Ethical approval</span><p id="par0145" class="elsevierStylePara elsevierViewall">All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and&#47;or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards&#46;</p></span><span id="sec0100" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0160">Informed consent</span><p id="par0150" class="elsevierStylePara elsevierViewall">Informed consent was obtained from all individual participants included in the study&#46;</p></span></span>"
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              "titulo" => "F-FDG PET&#47;CT acquisition"
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              "titulo" => "F-FDG PET&#47;MR acquisition"
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    "fechaRecibido" => "2021-09-03"
    "fechaAceptado" => "2021-12-16"
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            0 => "PET&#47;MR"
            1 => "PET&#47;CT"
            2 => "Lung cancer"
            3 => "NSCLC"
            4 => "Pleural invasion"
            5 => "Non-small cell lung cancer"
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            0 => "PET&#47;RM"
            1 => "PET&#47;TC"
            2 => "C&#225;ncer de pulm&#243;n"
            3 => "NSCLC"
            4 => "Invasi&#243;n pleural"
            5 => "C&#225;ncer de pulm&#243;n de c&#233;lulas no peque&#241;as"
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        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Objective</span><p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">To compare the diagnostic performance of <span class="elsevierStyleSup">18</span>F-FDG PET&#47;MR and PET&#47;CT preliminarily for the thoracic staging of non-small cell lung cancer &#40;NSCLC&#41; with a special focus on pleural invasion evaluation&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Methods</span><p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">52 patients with pathologically confirmed NSCLC were included and followed for another year&#46; Whole-body <span class="elsevierStyleSup">18</span>F-FDG PET&#47;CT and subsequent thoracic PET&#47;MR were performed for initial thoracic staging&#46; Thoracic &#40;simultaneous&#41; PET&#47;MR acquired PET images and MRI sequences including T2 weighted imaging&#44; with and without fat saturation&#44; T1 weighted imaging&#44; and diffusion weighted imaging &#40;DWI&#41;&#46; Two radiologists independently assessed the thoracic T&#44; N staging and pleural involvement&#46; The McNemar Chi-square test was used to compare the differences between PET&#47;CT and PET&#47;MR in the criteria&#46; The area under the receiver-operating-characteristic curves &#40;AUC&#41; was calculated&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">Compared to PET&#47;CT&#44; PET&#47;MR exhibited higher sensitivity&#44; specificity in the detection of pleural invasion&#59; 82 &#37; vs&#46; 64&#37; &#40;<span class="elsevierStyleItalic">p</span>&#8239;&#61;&#8239;0&#46;625&#41;&#44; 98 &#37; vs&#46; 95&#37; &#40;<span class="elsevierStyleItalic">p</span>&#8239;&#61;&#8239;1&#46;000&#41;&#44; PET&#47;MR to PET&#47;CT respectively&#46; The receiver-operating-characteristic analysis results of PET&#47;CT vs PET&#47;MR for the pleural invasion were as follow&#58; AUC<span class="elsevierStyleInf">PET&#47;CT</span>&#8239;&#61;&#8239;0&#46;79&#44; AUC<span class="elsevierStyleInf">PET&#47;MR</span>&#8239;&#61;&#8239;0&#46;90&#44; p&#8239;&#61;&#8239;0&#46;21&#46; Both T staging results and N staging results were approximately identical in PET&#47;CT and PET&#47;MR&#46; Differences between PET&#47;CT and PET&#47;MR in T staging&#44; N staging as well as pleural invasion accuracy were not statistically significant &#40;<span class="elsevierStyleItalic">p</span>&#8239;&#62;&#8239;0&#46;05&#44; each&#41;&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusion</span><p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">PET&#47;MR and PET&#47;CT demonstrated equivalent performance about the evaluation of preoperative thoracic staging of NSCLC patients&#46; PET&#47;MR may have greater potential in pleural invasion evaluation for NSCLC&#44; especially for solid nodules&#44; crucial to clinical decision-making&#44; though our results did not demonstrate statistical significance&#46;</p></span>"
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        "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Objetivo</span><p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">Comparar el rendimiento diagn&#243;stico de la PET&#47;RM con <span class="elsevierStyleSup">18</span>F-FDG y la PET&#47;TC de forma preliminar para la estadificaci&#243;n tor&#225;cica del c&#225;ncer de pulm&#243;n de c&#233;lulas no peque&#241;as &#40;NSCLC&#41; con un enfoque especial en la evaluaci&#243;n de la invasi&#243;n pleural&#46;</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">M&#233;todos</span><p id="spar0095" class="elsevierStyleSimplePara elsevierViewall">Se incluyeron 52 pacientes con NSCLC patol&#243;gicamente confirmado y se les dio seguimiento durante otro a&#241;o&#46; Se realizaron PET&#47;TC con <span class="elsevierStyleSup">18</span>F-FDG de cuerpo entero y PET&#47;RM tor&#225;cica posterior para la estadificaci&#243;n tor&#225;cica inicial&#46; Im&#225;genes de PET&#47;RM adquiridas tor&#225;cicas &#40;simult&#225;neas&#41; y secuencias de RM que incluyen im&#225;genes ponderadas en T2&#44; con y sin saturaci&#243;n de grasa&#44; im&#225;genes ponderadas en T1 e im&#225;genes ponderadas por difusi&#243;n &#40;DWI&#41;&#46; Dos radi&#243;logos evaluaron de forma independiente la estadificaci&#243;n T&#44; N tor&#225;cica y la afectaci&#243;n pleural&#46; Se utiliz&#243; la prueba de Chi-cuadrado de McNemar para comparar las diferencias entre PET&#47;TC y PET&#47;RM en los criterios&#46; Se realiz&#243; an&#225;lisis ROC con calcul&#243; el &#225;rea bajo la curva &#40;AUC&#41; para la invasi&#243;n pleural&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0100" class="elsevierStyleSimplePara elsevierViewall">En comparaci&#243;n con la PET&#47;TC&#44; la PET&#47;RM mostr&#243; una mayor sensibilidad y especificidad en la detecci&#243;n de invasi&#243;n pleural&#59; 82&#37; frente a 64&#37; &#40;<span class="elsevierStyleItalic">p</span>&#8239;&#61;&#8239;0&#44;625&#41;&#44; 98&#37; frente a 95&#37; &#40;<span class="elsevierStyleItalic">p</span>&#8239;&#61;&#8239;1&#46;000&#41;&#44; PET&#47;RM a PET&#47;TC respectivamente&#46; Los resultados del an&#225;lisis ROC de PET&#47;TC vs PET&#47;RM para la invasi&#243;n pleural fueron los siguientes&#58; AUC <span class="elsevierStyleInf">PET&#47;TC</span>&#8239;&#61;&#8239;0&#46;79&#44; AUC <span class="elsevierStyleInf">PET&#47;RM</span>&#8239;&#61;&#8239;0&#46;90&#44; <span class="elsevierStyleItalic">p</span>&#8239;&#61;&#8239;0&#46;21&#46; Tanto los resultados de la estadificaci&#243;n T como los resultados de la estadificaci&#243;n N fueron aproximadamente id&#233;nticos en PET&#47;TC y PET&#47;RM&#46; Las diferencias entre PET&#47;TC y PET&#47;RM en la estadificaci&#243;n T&#44; la estadificaci&#243;n N y la precisi&#243;n de la invasi&#243;n pleural no fueron estad&#237;sticamente significativas &#40;<span class="elsevierStyleItalic">p</span>&#8239;&#62;&#8239;0&#44;05&#44; cada una&#41;&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusi&#243;n</span><p id="spar0105" class="elsevierStyleSimplePara elsevierViewall">La PET&#47;RM y PET&#47;TC demostraron un rendimiento equivalente en la evaluaci&#243;n de la estadificaci&#243;n tor&#225;cica preoperatoria de pacientes con NSCLC&#46; La PET&#47;RM puede tener un mayor potencial en la evaluaci&#243;n de invasi&#243;n pleural para NSCLC&#44; especialmente para n&#243;dulos s&#243;lidos&#44; cruciales para la toma de decisiones cl&#237;nicas&#44; aunque nuestros resultados no demostraron significaci&#243;n estad&#237;stica&#46;</p></span>"
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        "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Please cite this article as&#58; Wang M-l&#44; Zhang H&#44; Yu H-j&#44; Tan H&#44; Hu L-z&#44; Kong H-j&#44; et al&#46; Estudio inicial sobre la comparaci&#243;n del rendimiento diagn&#243;stico de la PET&#47;RM con <span class="elsevierStyleSup">18</span>F-FDG y la PET&#47;TC con <span class="elsevierStyleSup">18</span>F-FDG para la estadificaci&#243;n tor&#225;cica del cancer de pulm&#243;n de c&#233;lulas no peque&#241;as&#58; enfoque en la invasi&#243;n pleural&#46; Rev Esp Med Nucl Imagen Mol&#46; 2023&#59;42&#58;16&#8211;23&#46;</p>"
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            "imagen" => "gr1.jpeg"
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          0 => array:3 [
            "identificador" => "at0005"
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          "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">A chart showing the patient selection process used in this study&#46;</p>"
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      1 => array:8 [
        "identificador" => "fig0010"
        "etiqueta" => "Figure 2"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
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            "identificador" => "at0010"
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          "en" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Distribution of the different T and N stages and the corresponding ratings in PET&#47;CT and PET&#47;MRI&#46;</p>"
        ]
      ]
      2 => array:8 [
        "identificador" => "fig0015"
        "etiqueta" => "Figure 3"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "figura" => array:1 [
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          0 => array:3 [
            "identificador" => "at0015"
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          "en" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Bland&#8211;Altman analysis showing lower and upper limits of agreement between <span class="elsevierStyleSup">18</span>F-FDG PET&#47;CT and PET&#47;MRI for SUV<span class="elsevierStyleInf">max</span>&#46; The difference between SUV<span class="elsevierStyleInf">max</span> on <span class="elsevierStyleSup">18</span>F-FDG PET&#47;MRI and PET&#47;CT was plotted against their mean&#46; The mean difference between 18&#8239;F-FDG PET&#47;MRI and PET&#47;CT was 0&#46;69 &#40;95&#37; confidence interval&#58; &#8722;5&#46;89&#59; &#43;7&#46;27&#41;&#46; No systematic bias was revealed by regression analysis&#46;</p>"
        ]
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      3 => array:8 [
        "identificador" => "fig0020"
        "etiqueta" => "Figure 4"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "figura" => array:1 [
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            "imagen" => "gr4.jpeg"
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          0 => array:3 [
            "identificador" => "at0020"
            "detalle" => "Figure "
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          "en" => "<p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">ROC curve and AUC calculation for PET&#47;CT and PET&#47;MR for pleural invasion&#46; AUC<span class="elsevierStyleInf">PET&#47;CT</span>&#8239;&#61;&#8239;0&#46;79 &#91;0&#46;78&#8211;1&#46;00&#93;&#44; AUC<span class="elsevierStyleInf">PET&#47;MR</span>&#8239;&#61;&#8239;0&#46;90 &#91;0&#46;64&#8211;0&#46;95&#93;&#44; <span class="elsevierStyleItalic">p</span>&#8239;&#61;&#8239;0&#46;21&#46;</p>"
        ]
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      4 => array:8 [
        "identificador" => "fig0025"
        "etiqueta" => "Figure 5"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "figura" => array:1 [
          0 => array:4 [
            "imagen" => "gr5.jpeg"
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            "Tamanyo" => 345624
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            "identificador" => "at0025"
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          "en" => "<p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Both PET&#47;MR and PET&#47;CT showed a nearly 2&#8239;cm solid nodule &#40;arrow&#41; in the right upper lobe of a 71-year-old woman&#44; confirmed as adenocarcinoma by lobectomy&#46; While no definite sign of pleural invasion could be observed in PET&#47;CT &#40;a &#38; b&#41;&#44; extensive pleural thickening under the mass was detectable in the subsequent <span class="elsevierStyleSup">18</span>F-FDG PET&#47;MR examination &#40;c &#38; d&#41;&#44; leading to an upgrade from a T1-stage in PET&#47;CT to a T2-stage in PET&#47;MR&#46; During the follow-up year&#44; this patient received postoperative chemotherapy in order to improve the survival rate&#46;</p>"
        ]
      ]
      5 => array:8 [
        "identificador" => "tbl0005"
        "etiqueta" => "Table 1"
        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "at0030"
            "detalle" => "Table "
            "rol" => "short"
          ]
        ]
        "tabla" => array:2 [
          "leyenda" => "<p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Note&#58; pGGN&#8239;&#61;&#8239;pure ground glass nodule&#59; PSN&#8239;&#61;&#8239;part-solid nodule&#59; SN&#8239;&#61;&#8239;solid nodule&#46;</p>"
          "tablatextoimagen" => array:1 [
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                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Variable&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Cases and percentage&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Sex&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Male&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">34 &#40;65&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Female&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">18 &#40;35&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Average Age&#40;years&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">61&#46;9&#8239;&#177;&#8239;8&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Range&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">41&#8722;77&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Nodule type&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>pGGN&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">5 &#40;10&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>PSN&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">13 &#40;25&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>SN&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">34 &#40;65&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Surgery Type&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Conventional thoracotomy&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">10 &#40;19&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Video-assisted surgery&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">42 &#40;81&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Surgery method&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Pulmonary lobectomy&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">39 &#40;75&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Pulmonary wedge resection&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">10 &#40;19&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Pneumonectomy&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2 &#40;4&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Pulmonary sleeve resection&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1 &#40;2&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
            ]
          ]
        ]
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        "etiqueta" => "Table 2"
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            "identificador" => "at0035"
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        "tabla" => array:2 [
          "leyenda" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Note&#58; TR&#8239;&#61;&#8239;Time of Repetition&#59; TE&#8239;&#61;&#8239;Time of echo&#59; TSE&#8239;&#61;&#8239;turbo spin-echo&#59; STIR&#8239;&#61;&#8239;Short time inversion recovery&#59; DWI&#8239;&#61;&#8239;diffusion-weighted imaging&#59; FOV&#8239;&#61;&#8239;field of view&#46;</p>"
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              "tabla" => array:1 [
                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col">Parameters&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col">Transverse&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col">Transverse&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col">Transverse&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col">Coronal&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col">DWI&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr><tr title="table-row"><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">T1-TSE&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">T2-Arms&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">110&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">110&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">90&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t">voxel size &#40;mm&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">50&#44;800&nbsp;\t\t\t\t\t\t\n
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                  """
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      7 => array:8 [
        "identificador" => "tbl0015"
        "etiqueta" => "Table 3"
        "tipo" => "MULTIMEDIATABLA"
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          "leyenda" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Note&#58; TP&#8239;&#61;&#8239;True Positive&#59; TN&#8239;&#61;&#8239;True Negative&#59; FP&#8239;&#61;&#8239;False Positive&#59; FN&#8239;&#61;&#8239;False Negative&#59; PPV&#8239;&#61;&#8239;Positive Predictive Value&#59; NPV&#8239;&#61;&#8239;Negative Predictive Value&#59; 95&#37; confidence intervals are indicated in square brackets&#46;</p>"
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                0 => """
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">NPV&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;82 &#91;0&#46;48&#59;0&#46;97&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;98 &#91;0&#46;86&#59;1&#46;00&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;90 &#91;0&#46;54&#59;1&#46;00&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;95 &#91;0&#46;83&#59;0&#46;99&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">PET&#47;CT&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">39&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;64 &#91;0&#46;32&#59;0&#46;88&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;95 &#91;0&#46;82&#59;0&#46;99&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;78 &#91;0&#46;40&#59;0&#46;96&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;91 &#91;0&#46;77&#59;0&#46;97&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Statistical difference&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;625&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;000&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;635&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;00&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
            ]
          ]
        ]
        "descripcion" => array:1 [
          "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Diagnostic efficacy of PET&#47;CT and PET&#47;MRI for pleural invasion in non-small cell lung cancer&#46;</p>"
        ]
      ]
      8 => array:8 [
        "identificador" => "tbl0020"
        "etiqueta" => "Table 4"
        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "at0045"
            "detalle" => "Table "
            "rol" => "short"
          ]
        ]
        "tabla" => array:2 [
          "leyenda" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Note&#58; SCC&#8239;&#61;&#8239;Squamous cell carcinoma&#59; PET&#8239;&#61;&#8239;positron emission tomography&#59; MRI&#8239;&#61;&#8239;magnetic resonance imaging&#59; CT&#8239;&#61;&#8239;computed tomography&#59; TNM&#8239;&#61;&#8239;tumor&#44; nodes and metastasis AJCC malignant pleural mesothelioma staging system&#44; 7th edition&#59; PSN&#8239;&#61;&#8239;part-solid nodule&#59; SN&#8239;&#61;&#8239;solid nodule&#46;</p>"
          "tablatextoimagen" => array:1 [
            0 => array:1 [
              "tabla" => array:1 [
                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Age&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Sex&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Nodule Type&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Histopathological subtype&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">TNM stage PET&#47;MRI&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">TNM stage PET&#47;CT&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">TNM Stage pathological&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Treatment &#40;with one-year follow up&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">66&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Male&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">SN&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Adenocarcinoma&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pulmonary lobectomy&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">55&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Female&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">SN&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Adenocarcinoma&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pulmonary lobectomy&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">66&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Female&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">SN&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Adenocarcinoma&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN2M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN2M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN2M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pulmonary lobectomy followed by targeted therapy&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">71&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Female&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">SN&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Adenocarcinoma&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T1N0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pulmonary wedge resection&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">69&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Male&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">SN&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Adenocarcinoma&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T3N0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pulmonary lobectomy&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">65&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Male&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">SN&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">SCC&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pulmonary lobectomy followed by chemotherapy&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">58&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Male&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">SN&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">SCC&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T3N2M1b&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T3N2M1b&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T3N2M1b&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Palliative surgery followed by chemo-radiotherapy&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">62&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Female&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">SN&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Adenocarcinoma&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pulmonary lobectomy&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">54&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Male&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">PSN&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Adenocarcinoma&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T1N0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T1N0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN2M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pulmonary lobectomy&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">77&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Male&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">SN&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Adenocarcinoma&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T4N0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T4N0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T4N0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pulmonary lobectomy&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">62&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Male&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">SN&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Adenocarcinoma&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T1N0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">T2aN0M0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pulmonary wedge resection followed by chemotherapy and immune therapy&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
            ]
          ]
        ]
        "descripcion" => array:1 [
          "en" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Summary of clinical and pathological staging for VPI-positive patients&#46;</p>"
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      "titulo" => "References"
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                    0 => array:2 [
                      "titulo" => "Surgery for non-small cell lung cancer&#58; postoperative survival based on the revised tumor-node-metastasis classification and its time trend"
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                        0 => array:2 [
                          "etal" => true
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                            0 => "F&#46; Tanaka"
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                            2 => "Y&#46; Otake"
                            3 => "R&#46; Miyahara"
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                        "tituloSerie" => "Eur J Cardiothorac Surg"
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                        "volumen" => "18"
                        "numero" => "2"
                        "paginaInicial" => "147"
                        "paginaFinal" => "155"
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                          0 => array:2 [
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                      "titulo" => "Global cancer statistics 2018&#58; GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries"
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                          "etal" => false
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                            4 => "L&#46;A&#46; Torre"
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                    0 => array:2 [
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                        "tituloSerie" => "CA Cancer J Clin"
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                        "volumen" => "68"
                        "numero" => "6"
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                        "paginaFinal" => "424"
                        "link" => array:1 [
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                    0 => array:2 [
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                      "titulo" => "Thoracic staging with 18F-FDG PET&#47;MR in non-small cell lung cancer &#8211; does it change therapeutic decisions in comparson to 18F-FDG PET&#47;CT&#63;"
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                        0 => array:2 [
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                            3 => "B&#46; Gomez"
                            4 => "T&#46; Gauler"
                            5 => "C&#46; Roesel"
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Article information
ISSN: 22538089
Original language: English
DOI:10.1016/j.remnie.2021.12.007
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