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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Diffuse gliomas are the most common primary cerebral tumor of adulthood&#46;<a class="elsevierStyleCrossRef" href="#bib0125"><span class="elsevierStyleSup">1</span></a> In the management of gliomas&#44; the World Health Organization &#40;WHO&#41; tumor grade is an important prognostic factor along with clinical and radiologic findings&#46;<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">2</span></a> Molecular and genetic biomarkers of gliomas are also emerging prognostic factors predicting the biologic behavior of tumors&#46;<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">3</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Dynamic susceptibility-weighted &#40;DSC&#41; imaging remains the most commonly used perfusion technique in glioma grading&#44; and cerebral blood volume &#40;CBV&#41; has been recently identified as an important prognostic marker for survival independent of tumor grade<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">4</span></a>&#59; however&#44; those perfusion measurements may be influenced by extravascular contrast leakage from tumor vessels&#46;<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">5</span></a> Dynamic contrast-enhanced &#40;DCE&#41; perfusion Magnetic resonance imaging &#40;MRI&#41; is an alternative technique for glioma grading providing hemodynamic parameters such as volume transfer coefficient &#40;Ktrans&#41;&#44; fractional volume of the extravascular extracellular space &#40;Ve&#41; and fractional blood plasma volume &#40;Vp&#41; that characterize the microvascular environment&#46;<a class="elsevierStyleCrossRefs" href="#bib0125"><span class="elsevierStyleSup">1&#44;2&#44;5</span></a> Like CBV&#44; Ktrans has demonstrated to be able to differentiate high- and low-grade tumors and predicts prognosis in diffuse gliomas&#46;<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">6</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">Previously in the literature&#44; there are few studies published comparing DCE and DSC perfusion imaging in diffuse gliomas&#46;<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">5</span></a> Although Law et al&#46;<a class="elsevierStyleCrossRef" href="#bib0155"><span class="elsevierStyleSup">7</span></a> have previously reported a weak but positive correlation between Ktrans and CBV&#59; leakage parameters extracted from DSC and their relationship to the DCE-measures of vascular permeability remains unclear&#46;<a class="elsevierStyleCrossRef" href="#bib0160"><span class="elsevierStyleSup">8</span></a> Moreover&#44; to our knowledge&#44; permeability parameters have not yet been analyzed in function of the molecular status in diffuse gliomas&#46;</p><p id="par0020" class="elsevierStylePara elsevierViewall">The objectives of this study were&#58; &#40;1&#41; compare DCE and DSC permeability parameters&#44; &#40;2&#41; evaluate diagnostic accuracy of permeability parameters when discriminating high- and low-grade gliomas&#44; &#40;3&#41; analyze relationship of permeability with overall survival &#40;OS&#41; and progression-free survival &#40;PFS&#41;&#44; and &#40;4&#41; assess permeability differences in high-grade tumors classified on the basis of isocitrate dehydrogenase &#40;IDH&#41;&#44; O6-methylguanine-dna-methyltransferase promoter methylation &#40;MGMT&#41; and alpha-thalassemia&#47;mental retardation syndrome X-linked &#40;ATRX&#41; status&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Material and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Patient selection and histopathological analysis</span><p id="par0025" class="elsevierStylePara elsevierViewall">From February 2014 to July 2016&#44; we conducted a retrospective analysis of forty-nine patients with histologically proved diffuse gliomas&#46; Following surgical resection or biopsy&#44; two experienced neuropathologists provided histopathologic diagnosis by using the 2007 WHO classification&#46;<a class="elsevierStyleCrossRef" href="#bib0165"><span class="elsevierStyleSup">9</span></a> Histologic specimens were classified into grade II-IV gliomas based on the presence of astrocytic or oligodendroglial morphology&#44; cell density&#44; atypia&#44; mitotic activity&#44; vascular proliferation and necrosis&#46; From a prognostic and therapeutic point of view&#44; a variable percentage of high-grade gliomas were also subclassified according to IDH &#40;87&#37; analyzed&#44; <span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>36&#41;&#44; MGMT &#40;48&#46;7&#37; analyzed&#44; <span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>20&#41; and ATRX status &#40;39&#37; analyzed&#44; <span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>16&#41;&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Immunohistochemistry</span><p id="par0030" class="elsevierStylePara elsevierViewall">To detect the IDH1 R132H mutation&#44; a mouse monoclonal antibody &#40;dilution 1&#58;100&#44; DIA H09&#44; Dianova&#44; Germany&#41; was used&#46; ATRX immunohistochemistry &#40;HPA001906 rabbit polyclonal&#44; dilution 1&#58;100&#44; Sigma Aldrich&#44; USA&#41; was performed using an automated immunostainer&#46; IDH1 and IDH2 mutations were detected by direct Sanger sequencing in an ABI PRISM 310 DNA Analyzer &#40;Applied Biosystems&#44; Foster City&#44; CA&#44; USA&#41; or by pyrosequencing assays using the Pyromark Q24 ID instrument &#40;Qiagen&#41;&#46; <a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a> represents positive staining results for IDH and ATRX mutation&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">MGMT methylation-specific PCR &#40;MSP&#41;</span><p id="par0035" class="elsevierStylePara elsevierViewall">For MGMT promoter methylation analysis&#44; DNA was bisulfite-treated using the EZ DNA methylation Kit &#40;Zymo Research&#44; Orange&#44; CA&#44; USA&#41; according to the manufacturer&#39;s instructions&#46;</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Magnetic resonance imaging data acquisition</span><p id="par0040" class="elsevierStylePara elsevierViewall">All patients were examined with the same imaging acquisition protocol at a 1&#46;5<span class="elsevierStyleHsp" style=""></span>T scanner &#40;Signa Excite&#59; GE Healthcare&#44; Milwaukee&#44; Wisconsin&#41; by using an 8-channel encoding head coil&#46; Preoperative MRI protocol included pre-contrast T1-weighted 3D fast spoiled gradient-recalled acquisition in the steady state &#40;FSPGR&#41; &#40;TR&#44; 7<span class="elsevierStyleHsp" style=""></span>ms&#59; TE&#44; 2&#46;2<span class="elsevierStyleHsp" style=""></span>ms&#59; slice thickness&#44; 1&#46;6<span class="elsevierStyleHsp" style=""></span>mm&#59; flip angle&#44; 12&#176;&#59; matrix 320<span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span>320&#41;&#44; axial T2-weighted fast spin-echo &#40;TR<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>4100&#44; TE<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>85&#41;&#44; axial FLAIR &#40;TR<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>8000&#44; TE<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>120&#44; TI<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>2000&#41;&#44; and diffusion-weighted imaging &#40;DWI&#41; &#40;single-shot spin-echo echo planar imaging with 4-mm contiguous sections and <span class="elsevierStyleItalic">b</span> values of 0 and 1000<span class="elsevierStyleHsp" style=""></span>s&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#46; Data from T2WI&#44; FLAIR were obtained using 4-mm-thick sections with a 0&#46;4-mm skip&#44; a 320<span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span>256 matrix and a FOV of 24<span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span>24<span class="elsevierStyleHsp" style=""></span>cm&#46;</p><p id="par0045" class="elsevierStylePara elsevierViewall">DCE-MRI was performed with a dynamic gradient-echo T1-weighted sequence using the following parameters&#58; TR&#47;TE&#44; 3&#46;1&#47;1&#46;4<span class="elsevierStyleHsp" style=""></span>ms&#59; flip angle&#44; 15&#176;&#59; matrix&#44; 160<span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span>160&#59; section thickness&#44; 2&#46;4<span class="elsevierStyleHsp" style=""></span>mm&#46; After pre-contrast axial sequence&#44; 30-dynamic contrast-enhanced T1-weighted images were obtained with an injection of 5<span class="elsevierStyleHsp" style=""></span>mL of gadobutrol &#40;Gadovist&#44; 1<span class="elsevierStyleHsp" style=""></span>mmol&#47;mL&#59; Berlex Laboratories&#44; Wayne&#44; NJ&#41; at a rate of 3<span class="elsevierStyleHsp" style=""></span>mL&#47;s &#40;Spectris Solaris EP&#44; MR Injection System&#41;&#46; After DCE perfusion imaging&#44; dynamic contrast-enhanced T2&#42;-weighted perfusion MRI was performed by using a gradient-echo EPI acquisition during the first pass of a bolus of gadobutrol at a dose of 0&#46;1<span class="elsevierStyleHsp" style=""></span>mmol&#47;kg&#46; We used the 5<span class="elsevierStyleHsp" style=""></span>mL of gadobutrol used for DCE perfusion MRI as a preload for DSC imaging&#46;<a class="elsevierStyleCrossRef" href="#bib0170"><span class="elsevierStyleSup">10</span></a> A series of 40 multisection acquisitions was acquired at 0&#46;2-s interval&#46; The first 8 acquisitions were performed before the contrast agent was injected to establish a pre-contrast baseline&#46; For the 8<span class="elsevierStyleSup">th</span> acquisition&#44; gadobutrol was injected at a rate of 5<span class="elsevierStyleHsp" style=""></span>mL&#47;s followed by a 20-mL bolus of saline at 5<span class="elsevierStyleHsp" style=""></span>mL&#47;s&#46; After DSC perfusion imaging&#44; we acquired the post-contrast T1-weighted 3DFSPGR images&#46;</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Image post-processing and perfusion MRI analysis</span><p id="par0050" class="elsevierStylePara elsevierViewall">Post-processing of the 3D T1-weighted with contrast enhancement&#44; DCE and DSC perfusion MRI data was performed by using Olea Sphere v 2&#46;3 software &#40;Olea Medical&#44; La Ciotat&#44; France&#41;&#46; Segmentation of the preoperative enhancing tumor &#40;excluding macroscopic necrosis and cyst&#41; was performed on each slice of the volumetric post-contrast T1-weighetd images according to a semi-automated region-growing segmentation method&#46; Pharmacokinetic analysis of DCE-MRI was performed based on the extended Tofts model&#46;<a class="elsevierStyleCrossRef" href="#bib0175"><span class="elsevierStyleSup">11</span></a> Parametric maps of Ktrans&#44; Ve&#44; Vp&#44; rate constant between EES and blood plasma &#40;Kep&#41;&#44; CBV and leakage-corrected CBV were generated for each patient&#46; Those maps were calculated following automatic co-registration of perfusion parameters with post-contrast T1-weighted images&#44; which included the previously segmented enhancing tumor region of interest &#40;ROIs&#41;&#46; Then&#44; we estimated the &#8220;leakage&#8221; from the subtraction between CBV and leakage-corrected CBV at preoperative MRI based on the information obtained from all ROIs of each slice&#46;</p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Statistical analysis</span><p id="par0055" class="elsevierStylePara elsevierViewall">All statistical analysis was performed using the software Statistical Package for the Social Sciences &#40;SPSS v&#46;12&#44; Chicago&#44; IL&#41;&#46; Using the Pearson correlation we performed comparisons of DSC &#40;mean leakage&#41; and DCE-derived permeability parameters &#40;mean Ktrans&#44; Ve&#44; Vp and Kep&#41;&#46; A Mann&#8211;Whitney <span class="elsevierStyleItalic">U</span> test was used to compare the different permeability parameters between high- and low-grade tumors&#46; Receiver operating characteristic &#40;ROC&#41; curves analysis was used to determine the permeability parameters that best discriminate between high- and low-grade gliomas&#46; The area under curve &#40;AUC&#41; was obtained to indicate the degree of the relationship between permeability parameters and grade of gliomas&#46; Optimal threshold value for the parameter leakage was identified using ROC analysis for discriminating high- and low-grade tumors with the Youden&#39;s Index &#40;YI&#41; method&#44; where the YI of a cutpoint <span class="elsevierStyleItalic">c</span> is defined as YI&#40;<span class="elsevierStyleItalic">c</span>&#41; &#188; max &#40;Sensitivity&#40;<span class="elsevierStyleItalic">c</span>&#41;<span class="elsevierStyleHsp" style=""></span>&#43;<span class="elsevierStyleHsp" style=""></span>Specificity&#40;<span class="elsevierStyleItalic">c</span>&#41;<span class="elsevierStyleHsp" style=""></span>&#8722;<span class="elsevierStyleHsp" style=""></span>1 &#40;25&#41;&#46; Kaplan&#8211;Meier analysis and Cox proportional hazards models were constructed to test the relation of permeability parameters with survival calculating hazard ratios&#46; Mann&#8211;Whitney <span class="elsevierStyleItalic">U</span> test was used to evaluate the relationship of DSC and DCE-derived perfusion parameters with molecular biomarkers &#40;IDH&#44; MGMT and ATRX&#41;&#46; A value of <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;05 was regarded as statistically significant&#46;</p></span></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Results</span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Study population</span><p id="par0060" class="elsevierStylePara elsevierViewall">A total of forty-nine patients with diffuse gliomas were enrolled in the study&#46; This retrospective analysis included 28 male and 21 female patients &#40;age ranged 16&#8211;78 years&#41;&#46; Gliomas were classified into forty-one high-grade and 8 low-grade tumors&#46; Moreover&#44; in the group of high-grade gliomas&#44; 27&#46;78&#37; &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>10&#41; were positive for IDH mutation&#44; 65&#37; &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>13&#41; had methylated MGMT&#44; and 31&#46;25&#37; &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>5&#41; had ATX loss&#46; Mean follow-up was 15 months&#46;</p></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Correlation of DSC and DCE permeability parameters</span><p id="par0065" class="elsevierStylePara elsevierViewall">Leakage showed a significant positive correlation with Ktrans &#40;<span class="elsevierStyleItalic">R</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;310&#44; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;030&#41; and Vp &#40;<span class="elsevierStyleItalic">R</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;289&#44; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;044&#41;&#46; Vp also presented a significant correlation with Ve &#40;<span class="elsevierStyleItalic">R</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;388&#44; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;006&#41;&#46; The correlation was specifically significant between Ktrans and Ve &#40;<span class="elsevierStyleItalic">R</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;727&#44; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41;&#44; and between Ktrans and Kep &#40;<span class="elsevierStyleItalic">R</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;670&#44; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41;&#46; Correlations between DSC and DCE permeability parameters are displayed in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a></p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Accuracy of DSC and DCE-derived permeability parameters according to tumor grade</span><p id="par0070" class="elsevierStylePara elsevierViewall">We have demonstrated significant differences in the values of leakage &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;01&#41;&#44; Ktrans &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;002&#41;&#44; Vp &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;032&#41; and Ve &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41; between high-grade and low-grade diffuse gliomas&#46; High-grade tumors showed higher values of leakage &#40;median 1&#46;17&#59; interquartile range &#40;IQR&#41; 0&#46;47&#8211;1&#46;88&#41;&#44; Ktrans &#40;median 0&#46;24&#59; IQR 0&#46;11&#8211;0&#46;42&#41;&#44; Ve &#40;median 0&#46;18&#59; IQR 0&#46;09&#8211;0&#46;35&#41; and Vp &#40;median 0&#46;08&#59; IQR 0&#46;05&#8211;0&#46;11&#41;&#46; On the other hand&#44; low-grade tumors exhibited lower values of leakage &#40;median 0&#46;34&#59; IQR &#8722;0&#46;02&#8211;0&#46;88&#41;&#44; Ktrans &#40;median 0&#46;060&#59; IQR 0&#46;02&#8211;0&#46;13&#41;&#44; Ve &#40;median 0&#46;04&#59; IQR 0&#46;01&#8211;0&#46;07&#41; and Vp &#40;median 0&#46;035&#59; IQR 0&#46;03&#8211;0&#46;08&#41;&#46; We have not demonstrated significant differences in Kep values between high- and low-grade tumors&#46;</p><p id="par0075" class="elsevierStylePara elsevierViewall">ROC curve analysis was also performed to assess DSC and DCE as a tool to differentiate high- and low-grade gliomas&#46; The highest AUC was demonstrated by the DCE permeability parameters Ktrans &#40;AUC<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;838&#44; CI95&#37; 0&#46;710&#8211;0&#46;967&#44; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;003&#41; and Ve &#40;AUC<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;878&#44; CI95&#37; 0&#46;768&#8211;0&#46;988&#44; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41; &#40;<a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>&#41;&#46; In our series&#44; the cut off value of 0&#46;075 for the perfusion parameter Ve generated the best combination of sensitivity &#40;80&#37;&#41;&#44; specificity &#40;75&#37;&#41;&#44; positive predictive value &#40;94&#46;29&#37;&#41; and negative predictive value &#40;42&#46;86&#37;&#41; when differentiating high and low-grade tumors&#46; <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a> summarizes AUC values permeability parameters discriminating high- and low-grade tumors&#46;</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia><elsevierMultimedia ident="tbl0010"></elsevierMultimedia></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Impact of permeability parameters on survival</span><p id="par0080" class="elsevierStylePara elsevierViewall">DSC-derived leakage was the unique permeability parameter that showed a significant influence on overall survival &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;006&#59; hazard ratio &#40;HR&#41; 1&#46;560&#44; 95&#37; CI 1&#46;137&#8211;2&#46;164&#41;&#41; and progression-free survival &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;012&#59; HR 1&#46;432&#44; 95&#37; CI 1&#46;082&#8211;1&#46;895&#41;&#46; In our series&#44; including both high- and low-grade tumors&#44; median OS was 20 months &#40;CI95&#37; 7&#46;846&#8211;32&#46;154&#41; and median PFS was 9 months &#40;CI95&#37; 5&#46;32&#8211;12&#46;679&#41;&#46; For Kaplan Meier analysis&#44; the optimal cut off value of 1&#46;2 for the parameter leakage was identified using ROC curves with Youden index method&#46;</p><p id="par0085" class="elsevierStylePara elsevierViewall">Taking into account tumor enhancement&#44; all non-enhancing gliomas had leakage values &#60;1&#46;2&#46; When tumor enhancement was present&#44; 42&#46;58&#37; had leakage values &#62;1&#46;2 and the remainder 56&#46;42&#37; had leakage values &#62;1&#46;2&#46; We have not demonstrated a relationship between tumor enhancement and permeability parameters&#46;</p><p id="par0090" class="elsevierStylePara elsevierViewall">All low-grade tumors had leakage values lower than 1&#46;2&#46; In high-grade tumors&#44; 51&#46;2&#37; had leakage values &#60;1&#46;2 and the remainder 48&#46;8&#37; had leakage values &#62;1&#46;2&#46;</p><p id="par0095" class="elsevierStylePara elsevierViewall">Kaplan&#8211;Meier estimates of survival indicated that patients with a leakage mean of less than 1&#46;2 had a significant better OS &#40;Log-rank 8&#46;789&#59; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;003&#41; and PFS &#40;Log-rank 6&#46;612&#59; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;010&#41;&#46; The group of gliomas with leakage values &#62;1&#46;2 had a median overall and progression-free survival of 12 months &#40;95&#37; CI&#44; 3&#46;918&#8211;20&#46;082&#41; and 6 months &#40;95&#37; CI&#44; 4&#46;028&#8211;7&#46;792&#41;&#44; respectively&#46; Patients with leakage values &#60;1&#46;2 had a median progression-free survival of 15 months &#40;95&#37; CI&#44; 3&#46;470&#8211;26&#46;530&#41;&#46; At the end of the follow-up&#44; patients with leakage values lower than 1&#46;2 had not reached median overall survival&#46;</p><p id="par0100" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRefs" href="#fig0015">Figs&#46; 3 and 4</a> represent respectively the significant differences in OS and PFS in diffuse gliomas classified on the basis of the threshold value of 1&#46;2 for the permeability parameter leakage&#46;</p><elsevierMultimedia ident="fig0015"></elsevierMultimedia><elsevierMultimedia ident="fig0020"></elsevierMultimedia><p id="par0105" class="elsevierStylePara elsevierViewall">The remainder permeability parameters showed no significant correlation to survival&#46;</p></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Permeability differences in high-grade tumors classified according to molecular status</span><p id="par0110" class="elsevierStylePara elsevierViewall">In addition&#44; we assessed differences in DSC and DCE-derived permeability parameters in high-grade tumors classified on the basis of IDH&#44; ATRX and MGMT biomarkers&#46;</p><p id="par0115" class="elsevierStylePara elsevierViewall">Among IDH mutant &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>10&#41; and non-mutant &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>26&#41; high-grade gliomas&#44; there were significant differences in leakage &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;004&#41; and Ktrans values &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;028&#41;&#46; Median leakage values were respectively 0&#46;32 and 1&#46;46 for IDH mutant and non-mutant gliomas&#46; Median Ktrans values were 0&#46;13 for IDH mutant and 0&#46;26 for IDH non-mutant high-grade gliomas&#46; IDH mutant high-grade tumors showed lower leakage and Ktrans values&#46;</p><p id="par0120" class="elsevierStylePara elsevierViewall">Among ATRX mutant &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>5&#41; and non-mutant &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>11&#41; high-grade tumors&#44; there were significant differences in leakage &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;005&#41; and Vp values &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;027&#41;&#46; Median leakage values were 0&#46;12 for ATRX mutant and 0&#46;69 for ATRX non-mutant high-grade gliomas&#46; Regarding fractional blood plasma volume&#44; median Vp values were respectively 0&#46;05 and 0&#46;1 for ATRX mutant and non-mutant gliomas&#46; High-grade ATRX mutant tumors presented lower leakage and Vp values&#46;</p><p id="par0125" class="elsevierStylePara elsevierViewall">We have not demonstrated significant differences in perfusion parameters in MGMT methylated &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>13&#41; and non-methylated tumors &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>7&#41;&#46;</p><p id="par0130" class="elsevierStylePara elsevierViewall">In our series&#44; leakage was the best parameter discriminating high-grade gliomas classified based on IDH and ATRX status&#46;</p></span></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0140">Discussion</span><p id="par0135" class="elsevierStylePara elsevierViewall">Conventional contrast-enhanced MRI is not always precise in differentiating high- from low-grade gliomas&#46; Contrast enhancement indicates breakdown of the blood&#8211;brain-barrier&#44; and although is frequently associated with high-grade tumors&#44; it is not always accurate in predicting tumor grade&#46;<a class="elsevierStyleCrossRefs" href="#bib0145"><span class="elsevierStyleSup">5&#44;7</span></a> For this reason&#44; DSC and DCE perfusion MRI have become prognostic biomarkers providing measurements of neoangiogenesis in the preoperative grading of diffuse gliomas&#46;<a class="elsevierStyleCrossRefs" href="#bib0140"><span class="elsevierStyleSup">4&#44;12</span></a> In this study&#44; we have demonstrated a significant correlation between DSC-derived leakage and DCE-derived Ktrans and Vp&#46; Within DCE perfusion MRI&#44; the correlation was specifically significant between Ktrans and Ve &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41;&#44; and between Ktrans and Kep &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41;&#46; We are in agreement with the results previously published by Jia and cols&#44;<a class="elsevierStyleCrossRef" href="#bib0185"><span class="elsevierStyleSup">13</span></a> demonstrating a relationship between Ktrans and Ve&#44; which can be attributed to the fact that Ve values may depend markedly on the permeability of tumor vessels&#46; Unlike Alcaide-Leon and cols&#44;<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">14</span></a> we have not demonstrated a positive correlation between Vp and Ktrans&#44; which may be due to the analysis of both high- and low grade tumors in a relatively small sample series&#46;</p><p id="par0140" class="elsevierStylePara elsevierViewall">Neovascular proliferation is a hallmark in the evaluation of biological aggressiveness and malignancy of gliomas&#46;<a class="elsevierStyleCrossRef" href="#bib0185"><span class="elsevierStyleSup">13</span></a> When contrast agents move from plasma to extravascular extracellular space &#40;EES&#41; through the disrupted endothelial membrane of tumor vessels&#44; the distribution of contrast and magnetic relaxation will change in the intravascular and extravascular spaces&#46;<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">15</span></a> Therefore&#44; the preoperative non-invasive estimation of vascularity is critical in the management of diffuse gliomas&#46;<a class="elsevierStyleCrossRef" href="#bib0185"><span class="elsevierStyleSup">13</span></a> In our study&#44; we have demonstrated significant differences in leakage&#44; Ktrans&#44; Ve and Vp values between high- and low-grade tumors&#46; Higher-grade tumors showed greater values of both DSC and DCE perfusion parameters&#46; Our results&#44; which confirm the usefulness of both DSC and DCE perfusion in the preoperative grading of gliomas&#44; are in agreement with most of the series published to date&#46;<a class="elsevierStyleCrossRefs" href="#bib0145"><span class="elsevierStyleSup">5&#44;13&#44;16</span></a> These results may be explained by the fact that during the development of gliomas&#44; the microvasculature becomes aberrant&#46;<a class="elsevierStyleCrossRef" href="#bib0205"><span class="elsevierStyleSup">17</span></a> Thus&#44; there are more immature and hyperpermeable vessels&#44; and therefore with higher values in permeability parameters&#44; in high-grade than in low-grade gliomas&#46;</p><p id="par0145" class="elsevierStylePara elsevierViewall">As well as Choi et al&#46;<a class="elsevierStyleCrossRef" href="#bib0205"><span class="elsevierStyleSup">17</span></a> published in 2013&#44; Ve appeared to be comparable with Ktrans in differentiating high-grade from low-grade gliomas&#46; In our series&#44; in addition&#44; Ve was the perfusion parameter that best discriminated high- and low-grade tumors &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41;&#46;</p><p id="par0150" class="elsevierStylePara elsevierViewall">The utility of DSC perfusion MRI as a prognostic marker in diffuse gliomas is well recognized&#44; relating relative CBV with overall survival&#46;<a class="elsevierStyleCrossRef" href="#bib0180"><span class="elsevierStyleSup">12</span></a> Previous studies published by Jain<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">18</span></a> and Hirai et al&#46;<a class="elsevierStyleCrossRef" href="#bib0215"><span class="elsevierStyleSup">19</span></a> found that maximum CBV was a predictor of overall survival in glioblastoma&#46; In a previous study of our research team&#44; we have also demonstrated a significant association between CBV and survival in high- and low-grade tumors&#46;<a class="elsevierStyleCrossRef" href="#bib0180"><span class="elsevierStyleSup">12</span></a> However&#44; the use of DCE as a potential biomarker for prognosis has not been so well studied&#46; While Ktrans has been found to increase with glioma grade&#44; its prognostic value remains unclear&#46;<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">2</span></a> In this series&#44; we have analyzed not only the relationship of DCE-derived perfusion parameters with survival&#44; but also the relationship of the parameter leakage to survival&#44; not studied to date&#46;</p><p id="par0155" class="elsevierStylePara elsevierViewall">In our series&#44; DSC-derived leakage was the unique permeability parameter that showed a significant influence on OS &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;006&#41; and PFS &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;012&#41;&#46; In addition&#44; patients who had leakage values below 1&#46;2 had a significant better OS and PFS&#46; This result could be explained in part by the fact that low-grade gliomas are tumors with lower leakage values&#44; which in turn show a more favorable prognosis than high-grade tumors&#46;</p><p id="par0160" class="elsevierStylePara elsevierViewall">The major goal of this study is the assessment of permeability differences in high-grade tumors classified on the basis of molecular biomarkers&#46; To our knowledge&#44; this is the first time that the relationship between ATRX and permeability parameters is analyzed&#46; In gliomas&#44; the most frequent missense mutations in IDH genes are present at the 132 residue in IDH1 &#40;85&#37;&#41; and at 172 in IDH2 &#40;3&#37;&#41;&#46; They have been mainly found in secondary glioblastomas &#40;73&#8211;85&#37;&#41;&#44; and along with grades II and III astrocytic and oligodendroglial tumors &#40;72&#8211;100&#37;&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0220"><span class="elsevierStyleSup">20</span></a></p><p id="par0165" class="elsevierStylePara elsevierViewall">We have demonstrated significant differences in leakage and Ktrans values among IDH-mutated and non-mutated high-grade gliomas&#46; IDH mutant tumors showed lower leakage and Ktrans values&#46; The presence of IDH mutations has been shown to correlate with better survival in patients with glioblastoma&#46;<a class="elsevierStyleCrossRef" href="#bib0220"><span class="elsevierStyleSup">20</span></a> Since lower leakage values are also associated with a longer survival&#44; it would be expected that high-grade IDH-mutated would show lower values in the permeability parameters&#46;</p><p id="par0170" class="elsevierStylePara elsevierViewall">Alterations in the telomere maintenance-related gene ATRX have also been the subject of many investigations into glioma classification and prognosis&#46;<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">21</span></a> ATRX mutations&#44; which are characterized by loss of ATRX protein expression on immunochemistry&#44; occur in nearly 75&#37; of grade II&#8211;III astrocytomas and secondary glioblastomas&#46;<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">22</span></a> Previously&#44; it has been demonstrated that modifications in ATRX gene is not only associated with histologic subgroups&#44; but also related with survival stratifying glioblastomas into prognostically relevant subgroups&#46;<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">23</span></a> Chaurasia et al&#46;<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">23</span></a> have recently exhibited that aberrant expression of ATRX and IDH1 proteins was associated with a significantly increased survival rates&#46;</p><p id="par0175" class="elsevierStylePara elsevierViewall">In our series&#44; we have exhibited that high-grade tumors with ATRX loss presented significantly lower leakage and Vp values&#46; In the same way as with IDH mutation&#44; and probably because most tumors with ATRX loss have also IDH mutation&#44; high-grade gliomas with loss of ATRX expression showed lower leakage values at DSC perfusion MRI&#46; In our series&#44; leakage was the best parameter discriminating high-grade gliomas classified based on IDH and ATRX status&#46;</p><p id="par0180" class="elsevierStylePara elsevierViewall">Disorders of MGMT promoter methylation are related to transcriptional silencing of the MGMT gene&#44; thus permitting alkylating agents to be more effective in patients with MGMT promoter hypermethylation&#46;<a class="elsevierStyleCrossRef" href="#bib0220"><span class="elsevierStyleSup">20</span></a> In our study&#44; we have not found significant differences in permeability parameters in MGMT methylated and non-methylated tumors&#46; Our results are in disagreement with those published in 2014 by Ahn et al&#46;<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">24</span></a> who demonstrated in a group of glioblastomas that Ktrans values were significantly higher in the MGMT methylated group&#46; MGMT methylation is not related to tumor permeability&#44; but predisposes GBM treated with alkylating agents to a better prognosis&#46;</p><p id="par0185" class="elsevierStylePara elsevierViewall">This study has some limitations&#44; such as the retrospective nature&#44; the amount of enrolled patients and the composition of our sample&#44; with a relatively low number of grade II tumors and absence of molecular markers of all high-grade tumors&#46; Through promising&#44; these data need to be confirmed in a larger cohort of patients in an attempt to find permeability differences in MGMT methylated and non-methylated tumors&#46;</p></span><span id="sec0080" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0145">Conclusion</span><p id="par0190" class="elsevierStylePara elsevierViewall">The results of our study demonstrate a significant correlation between the permeability parameters leakage &#40;DSC&#41;&#44; Ktrans and Vp &#40;DCE&#41;&#46; Both DSC and DCE perfusion MRI-derived parameters can serve as a noninvasive method for approximating tumor grade&#46; Ve and Ktrans were the best parameters distinguishing high- and low-grade gliomas&#46; Leakage was the only permeability parameter significantly related to OS and PFS&#59; with prolonged survival for patients with leakage values lower than 1&#46;2&#46; Leakage was also the best parameter discriminating high-grade gliomas classified on the basis of IDH and ATRX status&#46;</p></span><span id="sec0085" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0150">Conflict of interest</span><p id="par0195" class="elsevierStylePara elsevierViewall">None declared&#46;</p></span></span>"
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          "titulo" => "Abbreviations"
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              "titulo" => "Introducci&#243;n y objetivos"
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              "titulo" => "Material y m&#233;todos"
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              "titulo" => "Patient selection and histopathological analysis"
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              "titulo" => "Immunohistochemistry"
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              "identificador" => "sec0025"
              "titulo" => "MGMT methylation-specific PCR &#40;MSP&#41;"
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            3 => array:2 [
              "identificador" => "sec0030"
              "titulo" => "Magnetic resonance imaging data acquisition"
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              "titulo" => "Image post-processing and perfusion MRI analysis"
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              "titulo" => "Study population"
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              "identificador" => "sec0055"
              "titulo" => "Correlation of DSC and DCE permeability parameters"
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              "identificador" => "sec0060"
              "titulo" => "Accuracy of DSC and DCE-derived permeability parameters according to tumor grade"
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              "identificador" => "sec0065"
              "titulo" => "Impact of permeability parameters on survival"
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              "titulo" => "Permeability differences in high-grade tumors classified according to molecular status"
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    "fechaRecibido" => "2017-12-20"
    "fechaAceptado" => "2018-06-01"
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          "clase" => "keyword"
          "titulo" => "Keywords"
          "identificador" => "xpalclavsec1065206"
          "palabras" => array:5 [
            0 => "Brain"
            1 => "Glioma"
            2 => "Neoplasms"
            3 => "Perfusion"
            4 => "Permeability"
          ]
        ]
        1 => array:4 [
          "clase" => "abr"
          "titulo" => "Abbreviations"
          "identificador" => "xpalclavsec1065205"
          "palabras" => array:21 [
            0 => "ATRX"
            1 => "AUC"
            2 => "CBV"
            3 => "DCE"
            4 => "DSC"
            5 => "DWI"
            6 => "EES"
            7 => "HR"
            8 => "IDH"
            9 => "IQR"
            10 => "Kep"
            11 => "Ktrans"
            12 => "MGMT"
            13 => "MRI"
            14 => "OS"
            15 => "PFS"
            16 => "ROC"
            17 => "ROI"
            18 => "Vp"
            19 => "Ve"
            20 => "WHO"
          ]
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          "palabras" => array:5 [
            0 => "Cerebro"
            1 => "Gliomas"
            2 => "Neoplasias"
            3 => "Perfusi&#243;n"
            4 => "Permeabilidad"
          ]
        ]
      ]
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    "resumen" => array:2 [
      "en" => array:3 [
        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Background and purpose</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Our objectives were&#58; &#40;1&#41; compare dynamic susceptibility-weighted &#40;DSC&#41; and dynamic contrast-enhanced &#40;DCE&#41; permeability parameters&#44; &#40;2&#41; evaluate diagnostic accuracy of DSC and DCE discriminating high- and low-grade tumors&#44; &#40;3&#41; analyze relationship of permeability parameters with overall &#40;OS&#41; and progression-free survival &#40;PFS&#41; and &#40;4&#41; assess differences in high-grade tumors classified according to molecular biomarkers&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Materials and methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">49 patients with histologically proved diffuse gliomas underwent DSC and DCE imaging&#46; Parametric maps of cerebral blood volume &#40;CBV&#41;&#44; CBV-leakage corrected&#44; volume transfer coefficient &#40;Ktrans&#41;&#44; fractional volume of the extravascular extracellular space &#40;EES&#41; &#40;Ve&#41;&#44; fractional blood plasma volume &#40;Vp&#41; and rate constant between EES and blood plasma &#40;Kep&#41; were calculated&#46; High-grade gliomas were also classified according to isocitrate dehydrogenase &#40;IDH&#41;&#44; alpha-thalassemia&#47;mental retardation syndrome X-linked &#40;ATRX&#41; and O6-methylguanine-dna-methyltransferase promoter methylation &#40;MGMT&#41; status&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">There is correlation between parameters leakage&#44; Ktrans and Vp&#46; ROC curve analysis showed significance in both Ktrans and Ve for glioma grading&#46; Threshold value of 0&#46;075 for Ve generated the best combination of sensitivity &#40;80&#37;&#41; and specificity &#40;75&#37;&#41; in tumor gradation&#46; Leakage was the only permeability parameter related to OS &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;006&#41; and PFS &#40;0&#46;012&#41;&#59; with prolonged survival for leakage values lower than 1&#46;2&#46; IDH-mutated high-grade tumors showed lower leakage and Ktrans values&#46; High-grade tumors with loss of ATRX presented lower leakage and Vp values&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Both DSC and DCE permeability parameters serve as non-invasive method for glioma grading&#46; Leakage was the unique permeability parameter related to survival and the best discriminating high-grade gliomas classified according to IDH and ATRX status&#46;</p></span>"
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        "titulo" => "Resumen"
        "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Introducci&#243;n y objetivos</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">1&#41; Evaluar la utilidad de los par&#225;metros de permeabilidad para clasificar gliomas de alto y bajo grado&#59; 2&#41; Analizar diferencias de permeabilidad de glioblastomas clasificados seg&#250;n marcadores moleculares&#59; 3&#41; Analizar la relaci&#243;n de la permeabilidad con la supervivencia global &#40;SG&#41; y libre de progresi&#243;n &#40;SLP&#41;&#44; y 4&#41; Comparar par&#225;metros de perfusi&#243;n T1 y T2&#42;&#46;</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Material y m&#233;todos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Cuarenta y nueve pacientes con gliomas difusos confirmados histol&#243;gicamente fueron estudiados con perfusi&#243;n T1 y T2&#42;&#46; Calculamos los mapas param&#233;tricos del volumen sangu&#237;neo cerebral &#40;CBV&#41;&#44; CBV-leakage corregido&#44; constante de permeabilidad &#40;Ktrans&#41;&#44; fracci&#243;n de volumen vascular &#40;Vp&#41;&#44; fracci&#243;n de volumen del espacio intersticial &#40;Ve&#41; y coeficiente de extracci&#243;n &#40;Kep&#41;&#46; El an&#225;lisis histol&#243;gico se bas&#243; en criterios OMS 2007 y los glioblastomas se clasificaron seg&#250;n mutaci&#243;n de genes isocitrato deshidrogenasa &#40;IDH&#41;&#44; Alpha Thalassemia&#47;Mental Retardation Syndrome X-Linked &#40;ATRX&#41; y metilguanidina-ADN metiltransferasa &#40;MGMT&#41;&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Incluimos 28 varones y 21 mujeres &#40;16-78 a&#241;os&#41;&#46; Los gliomas se clasificaron en 41 tumores de alto grado y 8 de bajo grado&#46; Leakage se correlacion&#243; con SG y SLP&#59; y mostr&#243; correlaci&#243;n lineal con Ktrans y Vp&#46; Los gliomas de alto y de bajo grado mostraron diferencias en los valores de leakage&#44; Ktrans&#44; Vp y Ve&#46; Leakage fue el par&#225;metro que mejor discrimin&#243; los glioblastomas clasificados seg&#250;n mutaci&#243;n IDH y ATRX&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusi&#243;n</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">La perfusi&#243;n T1 y T2&#42; sirven para clasificar a los gliomas difusos en funci&#243;n del grado tumoral&#46; Leakage se relaciona con la SG y SLP y es el par&#225;metro que mejor discrimina glioblastomas clasificados en funci&#243;n de IDH y ATRX&#46;</p></span>"
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            "titulo" => "Material y m&#233;todos"
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          3 => array:2 [
            "identificador" => "abst0040"
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          "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Immunostaining for the mutated form of isocitrate dehydrogenase &#40;A&#41; and for the loss of ATRX protein expression &#40;B&#41;&#46;</p>"
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        "etiqueta" => "Fig&#46; 2"
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          "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Receiver operating characteristic curves depicting the true positive rate &#40;specificity&#41; and the false positive rate &#40;sensitivity&#41; of DSC and DCE-MRI perfusion permeability parameters in classifying low- and high-grade gliomas&#46;</p>"
        ]
      ]
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        "identificador" => "fig0015"
        "etiqueta" => "Fig&#46; 3"
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          "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Overall survival calculated by using Kaplan&#8211;Meier curves for all patients stratified by the leakage threshold value of 1&#46;2&#46; Leakage values had a significant influence on overall survival&#46; In our series&#44; the median survival for diffuse gliomas with leakage values higher than 1&#46;2 was 12 months&#46; At the end of the follow-up&#44; patients with leakage values lower than 1&#46;2 had no reached median overall survival&#46;</p>"
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        "etiqueta" => "Fig&#46; 4"
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          "en" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Kaplan&#8211;Meier survival curves of 49 patients with diffuse gliomas&#46; Progression-free survival curves are plotted according to classification based on the cut off value of 1&#46;2 for leakage parameter&#46; Leakage values had also a significant influence on progression-free survival&#44; with a median survival of 15 months for patients with leakage values &#60;1&#46;2 and 6 months for patients with leakage values &#62;1&#46;2&#46;</p>"
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                  <table border="0" frame="\n
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                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head  " align="" valign="top" scope="col">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col">Leakage and Ktrans&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col">Leakage and Vp&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Pearson correlation coefficient&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;310 &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;030&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;727 &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;670 &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;388 &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;006&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
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          "en" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Results of the correlation study performed between DSC and DCE perfusion parameters&#46;</p>"
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                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Leakage&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;13&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;642&#8211;0&#46;919&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">K2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;814&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;005&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;065&#8211;0&#46;307&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Ktrans&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;838&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;003&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;710&#8211;0&#46;967&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Ve&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;878&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;768&#8211;0&#46;988&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Vp&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;741&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;033&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;550&#8211;0&#46;931&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
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          "en" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">ROC curve analysis of permeability parameters for differentiation between high- and low-grade gliomas&#46;</p>"
        ]
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    ]
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      "titulo" => "References"
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        0 => array:2 [
          "identificador" => "bibs0015"
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                  "host" => array:1 [
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Clinical Research
Perfusion MRI grading diffuse gliomas: Impact of permeability parameters on molecular biomarkers and survival
Utilidad de la RM perfusión en la gradación de los gliomas difusos: relación entre parámetros de permeabilidad, marcadores moleculares y supervivencia
Amaya Hilarioa,
Autor para correspondencia
amayahilario@yahoo.es

Corresponding author.
, Aurelio Hernandez-Lainb, Juan Manuel Sepulvedac, Alfonso Lagaresd, Angel Perez-Nuñezd, Ana Ramosa
a Department of Radiology, Neuroradiology Section, Universitary Hospital 12 de Octubre, Madrid, Spain
b Department of Neuropathology, Universitary Hospital 12 de Octubre, Madrid, Spain
c Department of Medical Oncology, Universitary Hospital 12 de Octubre, Madrid, Spain
d Department of Neurosurgery, Universitary Hospital 12 de Octubre, Madrid, Spain
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imaging remains the most commonly used perfusion technique in glioma grading&#44; and cerebral blood volume &#40;CBV&#41; has been recently identified as an important prognostic marker for survival independent of tumor grade<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">4</span></a>&#59; however&#44; those perfusion measurements may be influenced by extravascular contrast leakage from tumor vessels&#46;<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">5</span></a> Dynamic contrast-enhanced &#40;DCE&#41; perfusion Magnetic resonance imaging &#40;MRI&#41; is an alternative technique for glioma grading providing hemodynamic parameters such as volume transfer coefficient &#40;Ktrans&#41;&#44; fractional volume of the extravascular extracellular space &#40;Ve&#41; and fractional blood plasma volume &#40;Vp&#41; that characterize the microvascular environment&#46;<a class="elsevierStyleCrossRefs" href="#bib0125"><span class="elsevierStyleSup">1&#44;2&#44;5</span></a> Like CBV&#44; Ktrans has demonstrated to be able to differentiate high- and low-grade tumors and predicts prognosis in diffuse gliomas&#46;<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">6</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">Previously in the literature&#44; there are few studies published comparing DCE and DSC perfusion imaging in diffuse gliomas&#46;<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">5</span></a> Although Law et al&#46;<a class="elsevierStyleCrossRef" href="#bib0155"><span class="elsevierStyleSup">7</span></a> have previously reported a weak but positive correlation between Ktrans and CBV&#59; leakage parameters extracted from DSC and their relationship to the DCE-measures of vascular permeability remains unclear&#46;<a class="elsevierStyleCrossRef" href="#bib0160"><span class="elsevierStyleSup">8</span></a> Moreover&#44; to our knowledge&#44; permeability parameters have not yet been analyzed in function of the molecular status in diffuse gliomas&#46;</p><p id="par0020" class="elsevierStylePara elsevierViewall">The objectives of this study were&#58; &#40;1&#41; compare DCE and DSC permeability parameters&#44; &#40;2&#41; evaluate diagnostic accuracy of permeability parameters when discriminating high- and low-grade gliomas&#44; &#40;3&#41; analyze relationship of permeability with overall survival &#40;OS&#41; and progression-free survival &#40;PFS&#41;&#44; and &#40;4&#41; assess permeability differences in high-grade tumors classified on the basis of isocitrate dehydrogenase &#40;IDH&#41;&#44; O6-methylguanine-dna-methyltransferase promoter methylation &#40;MGMT&#41; and alpha-thalassemia&#47;mental retardation syndrome X-linked &#40;ATRX&#41; status&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Material and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Patient selection and histopathological analysis</span><p id="par0025" class="elsevierStylePara elsevierViewall">From February 2014 to July 2016&#44; we conducted a retrospective analysis of forty-nine patients with histologically proved diffuse gliomas&#46; Following surgical resection or biopsy&#44; two experienced neuropathologists provided histopathologic diagnosis by using the 2007 WHO classification&#46;<a class="elsevierStyleCrossRef" href="#bib0165"><span class="elsevierStyleSup">9</span></a> Histologic specimens were classified into grade II-IV gliomas based on the presence of astrocytic or oligodendroglial morphology&#44; cell density&#44; atypia&#44; mitotic activity&#44; vascular proliferation and necrosis&#46; From a prognostic and therapeutic point of view&#44; a variable percentage of high-grade gliomas were also subclassified according to IDH &#40;87&#37; analyzed&#44; <span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>36&#41;&#44; MGMT &#40;48&#46;7&#37; analyzed&#44; <span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>20&#41; and ATRX status &#40;39&#37; analyzed&#44; <span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>16&#41;&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Immunohistochemistry</span><p id="par0030" class="elsevierStylePara elsevierViewall">To detect the IDH1 R132H mutation&#44; a mouse monoclonal antibody &#40;dilution 1&#58;100&#44; DIA H09&#44; Dianova&#44; Germany&#41; was used&#46; ATRX immunohistochemistry &#40;HPA001906 rabbit polyclonal&#44; dilution 1&#58;100&#44; Sigma Aldrich&#44; USA&#41; was performed using an automated immunostainer&#46; IDH1 and IDH2 mutations were detected by direct Sanger sequencing in an ABI PRISM 310 DNA Analyzer &#40;Applied Biosystems&#44; Foster City&#44; CA&#44; USA&#41; or by pyrosequencing assays using the Pyromark Q24 ID instrument &#40;Qiagen&#41;&#46; <a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a> represents positive staining results for IDH and ATRX mutation&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">MGMT methylation-specific PCR &#40;MSP&#41;</span><p id="par0035" class="elsevierStylePara elsevierViewall">For MGMT promoter methylation analysis&#44; DNA was bisulfite-treated using the EZ DNA methylation Kit &#40;Zymo Research&#44; Orange&#44; CA&#44; USA&#41; according to the manufacturer&#39;s instructions&#46;</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Magnetic resonance imaging data acquisition</span><p id="par0040" class="elsevierStylePara elsevierViewall">All patients were examined with the same imaging acquisition protocol at a 1&#46;5<span class="elsevierStyleHsp" style=""></span>T scanner &#40;Signa Excite&#59; GE Healthcare&#44; Milwaukee&#44; Wisconsin&#41; by using an 8-channel encoding head coil&#46; Preoperative MRI protocol included pre-contrast T1-weighted 3D fast spoiled gradient-recalled acquisition in the steady state &#40;FSPGR&#41; &#40;TR&#44; 7<span class="elsevierStyleHsp" style=""></span>ms&#59; TE&#44; 2&#46;2<span class="elsevierStyleHsp" style=""></span>ms&#59; slice thickness&#44; 1&#46;6<span class="elsevierStyleHsp" style=""></span>mm&#59; flip angle&#44; 12&#176;&#59; matrix 320<span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span>320&#41;&#44; axial T2-weighted fast spin-echo &#40;TR<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>4100&#44; TE<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>85&#41;&#44; axial FLAIR &#40;TR<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>8000&#44; TE<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>120&#44; TI<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>2000&#41;&#44; and diffusion-weighted imaging &#40;DWI&#41; &#40;single-shot spin-echo echo planar imaging with 4-mm contiguous sections and <span class="elsevierStyleItalic">b</span> values of 0 and 1000<span class="elsevierStyleHsp" style=""></span>s&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#46; Data from T2WI&#44; FLAIR were obtained using 4-mm-thick sections with a 0&#46;4-mm skip&#44; a 320<span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span>256 matrix and a FOV of 24<span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span>24<span class="elsevierStyleHsp" style=""></span>cm&#46;</p><p id="par0045" class="elsevierStylePara elsevierViewall">DCE-MRI was performed with a dynamic gradient-echo T1-weighted sequence using the following parameters&#58; TR&#47;TE&#44; 3&#46;1&#47;1&#46;4<span class="elsevierStyleHsp" style=""></span>ms&#59; flip angle&#44; 15&#176;&#59; matrix&#44; 160<span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span>160&#59; section thickness&#44; 2&#46;4<span class="elsevierStyleHsp" style=""></span>mm&#46; After pre-contrast axial sequence&#44; 30-dynamic contrast-enhanced T1-weighted images were obtained with an injection of 5<span class="elsevierStyleHsp" style=""></span>mL of gadobutrol &#40;Gadovist&#44; 1<span class="elsevierStyleHsp" style=""></span>mmol&#47;mL&#59; Berlex Laboratories&#44; Wayne&#44; NJ&#41; at a rate of 3<span class="elsevierStyleHsp" style=""></span>mL&#47;s &#40;Spectris Solaris EP&#44; MR Injection System&#41;&#46; After DCE perfusion imaging&#44; dynamic contrast-enhanced T2&#42;-weighted perfusion MRI was performed by using a gradient-echo EPI acquisition during the first pass of a bolus of gadobutrol at a dose of 0&#46;1<span class="elsevierStyleHsp" style=""></span>mmol&#47;kg&#46; We used the 5<span class="elsevierStyleHsp" style=""></span>mL of gadobutrol used for DCE perfusion MRI as a preload for DSC imaging&#46;<a class="elsevierStyleCrossRef" href="#bib0170"><span class="elsevierStyleSup">10</span></a> A series of 40 multisection acquisitions was acquired at 0&#46;2-s interval&#46; The first 8 acquisitions were performed before the contrast agent was injected to establish a pre-contrast baseline&#46; For the 8<span class="elsevierStyleSup">th</span> acquisition&#44; gadobutrol was injected at a rate of 5<span class="elsevierStyleHsp" style=""></span>mL&#47;s followed by a 20-mL bolus of saline at 5<span class="elsevierStyleHsp" style=""></span>mL&#47;s&#46; After DSC perfusion imaging&#44; we acquired the post-contrast T1-weighted 3DFSPGR images&#46;</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Image post-processing and perfusion MRI analysis</span><p id="par0050" class="elsevierStylePara elsevierViewall">Post-processing of the 3D T1-weighted with contrast enhancement&#44; DCE and DSC perfusion MRI data was performed by using Olea Sphere v 2&#46;3 software &#40;Olea Medical&#44; La Ciotat&#44; France&#41;&#46; Segmentation of the preoperative enhancing tumor &#40;excluding macroscopic necrosis and cyst&#41; was performed on each slice of the volumetric post-contrast T1-weighetd images according to a semi-automated region-growing segmentation method&#46; Pharmacokinetic analysis of DCE-MRI was performed based on the extended Tofts model&#46;<a class="elsevierStyleCrossRef" href="#bib0175"><span class="elsevierStyleSup">11</span></a> Parametric maps of Ktrans&#44; Ve&#44; Vp&#44; rate constant between EES and blood plasma &#40;Kep&#41;&#44; CBV and leakage-corrected CBV were generated for each patient&#46; Those maps were calculated following automatic co-registration of perfusion parameters with post-contrast T1-weighted images&#44; which included the previously segmented enhancing tumor region of interest &#40;ROIs&#41;&#46; Then&#44; we estimated the &#8220;leakage&#8221; from the subtraction between CBV and leakage-corrected CBV at preoperative MRI based on the information obtained from all ROIs of each slice&#46;</p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Statistical analysis</span><p id="par0055" class="elsevierStylePara elsevierViewall">All statistical analysis was performed using the software Statistical Package for the Social Sciences &#40;SPSS v&#46;12&#44; Chicago&#44; IL&#41;&#46; Using the Pearson correlation we performed comparisons of DSC &#40;mean leakage&#41; and DCE-derived permeability parameters &#40;mean Ktrans&#44; Ve&#44; Vp and Kep&#41;&#46; A Mann&#8211;Whitney <span class="elsevierStyleItalic">U</span> test was used to compare the different permeability parameters between high- and low-grade tumors&#46; Receiver operating characteristic &#40;ROC&#41; curves analysis was used to determine the permeability parameters that best discriminate between high- and low-grade gliomas&#46; The area under curve &#40;AUC&#41; was obtained to indicate the degree of the relationship between permeability parameters and grade of gliomas&#46; Optimal threshold value for the parameter leakage was identified using ROC analysis for discriminating high- and low-grade tumors with the Youden&#39;s Index &#40;YI&#41; method&#44; where the YI of a cutpoint <span class="elsevierStyleItalic">c</span> is defined as YI&#40;<span class="elsevierStyleItalic">c</span>&#41; &#188; max &#40;Sensitivity&#40;<span class="elsevierStyleItalic">c</span>&#41;<span class="elsevierStyleHsp" style=""></span>&#43;<span class="elsevierStyleHsp" style=""></span>Specificity&#40;<span class="elsevierStyleItalic">c</span>&#41;<span class="elsevierStyleHsp" style=""></span>&#8722;<span class="elsevierStyleHsp" style=""></span>1 &#40;25&#41;&#46; Kaplan&#8211;Meier analysis and Cox proportional hazards models were constructed to test the relation of permeability parameters with survival calculating hazard ratios&#46; Mann&#8211;Whitney <span class="elsevierStyleItalic">U</span> test was used to evaluate the relationship of DSC and DCE-derived perfusion parameters with molecular biomarkers &#40;IDH&#44; MGMT and ATRX&#41;&#46; A value of <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;05 was regarded as statistically significant&#46;</p></span></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Results</span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Study population</span><p id="par0060" class="elsevierStylePara elsevierViewall">A total of forty-nine patients with diffuse gliomas were enrolled in the study&#46; This retrospective analysis included 28 male and 21 female patients &#40;age ranged 16&#8211;78 years&#41;&#46; Gliomas were classified into forty-one high-grade and 8 low-grade tumors&#46; Moreover&#44; in the group of high-grade gliomas&#44; 27&#46;78&#37; &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>10&#41; were positive for IDH mutation&#44; 65&#37; &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>13&#41; had methylated MGMT&#44; and 31&#46;25&#37; &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>5&#41; had ATX loss&#46; Mean follow-up was 15 months&#46;</p></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Correlation of DSC and DCE permeability parameters</span><p id="par0065" class="elsevierStylePara elsevierViewall">Leakage showed a significant positive correlation with Ktrans &#40;<span class="elsevierStyleItalic">R</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;310&#44; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;030&#41; and Vp &#40;<span class="elsevierStyleItalic">R</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;289&#44; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;044&#41;&#46; Vp also presented a significant correlation with Ve &#40;<span class="elsevierStyleItalic">R</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;388&#44; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;006&#41;&#46; The correlation was specifically significant between Ktrans and Ve &#40;<span class="elsevierStyleItalic">R</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;727&#44; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41;&#44; and between Ktrans and Kep &#40;<span class="elsevierStyleItalic">R</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;670&#44; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41;&#46; Correlations between DSC and DCE permeability parameters are displayed in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a></p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Accuracy of DSC and DCE-derived permeability parameters according to tumor grade</span><p id="par0070" class="elsevierStylePara elsevierViewall">We have demonstrated significant differences in the values of leakage &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;01&#41;&#44; Ktrans &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;002&#41;&#44; Vp &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;032&#41; and Ve &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41; between high-grade and low-grade diffuse gliomas&#46; High-grade tumors showed higher values of leakage &#40;median 1&#46;17&#59; interquartile range &#40;IQR&#41; 0&#46;47&#8211;1&#46;88&#41;&#44; Ktrans &#40;median 0&#46;24&#59; IQR 0&#46;11&#8211;0&#46;42&#41;&#44; Ve &#40;median 0&#46;18&#59; IQR 0&#46;09&#8211;0&#46;35&#41; and Vp &#40;median 0&#46;08&#59; IQR 0&#46;05&#8211;0&#46;11&#41;&#46; On the other hand&#44; low-grade tumors exhibited lower values of leakage &#40;median 0&#46;34&#59; IQR &#8722;0&#46;02&#8211;0&#46;88&#41;&#44; Ktrans &#40;median 0&#46;060&#59; IQR 0&#46;02&#8211;0&#46;13&#41;&#44; Ve &#40;median 0&#46;04&#59; IQR 0&#46;01&#8211;0&#46;07&#41; and Vp &#40;median 0&#46;035&#59; IQR 0&#46;03&#8211;0&#46;08&#41;&#46; We have not demonstrated significant differences in Kep values between high- and low-grade tumors&#46;</p><p id="par0075" class="elsevierStylePara elsevierViewall">ROC curve analysis was also performed to assess DSC and DCE as a tool to differentiate high- and low-grade gliomas&#46; The highest AUC was demonstrated by the DCE permeability parameters Ktrans &#40;AUC<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;838&#44; CI95&#37; 0&#46;710&#8211;0&#46;967&#44; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;003&#41; and Ve &#40;AUC<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;878&#44; CI95&#37; 0&#46;768&#8211;0&#46;988&#44; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41; &#40;<a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>&#41;&#46; In our series&#44; the cut off value of 0&#46;075 for the perfusion parameter Ve generated the best combination of sensitivity &#40;80&#37;&#41;&#44; specificity &#40;75&#37;&#41;&#44; positive predictive value &#40;94&#46;29&#37;&#41; and negative predictive value &#40;42&#46;86&#37;&#41; when differentiating high and low-grade tumors&#46; <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a> summarizes AUC values permeability parameters discriminating high- and low-grade tumors&#46;</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia><elsevierMultimedia ident="tbl0010"></elsevierMultimedia></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Impact of permeability parameters on survival</span><p id="par0080" class="elsevierStylePara elsevierViewall">DSC-derived leakage was the unique permeability parameter that showed a significant influence on overall survival &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;006&#59; hazard ratio &#40;HR&#41; 1&#46;560&#44; 95&#37; CI 1&#46;137&#8211;2&#46;164&#41;&#41; and progression-free survival &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;012&#59; HR 1&#46;432&#44; 95&#37; CI 1&#46;082&#8211;1&#46;895&#41;&#46; In our series&#44; including both high- and low-grade tumors&#44; median OS was 20 months &#40;CI95&#37; 7&#46;846&#8211;32&#46;154&#41; and median PFS was 9 months &#40;CI95&#37; 5&#46;32&#8211;12&#46;679&#41;&#46; For Kaplan Meier analysis&#44; the optimal cut off value of 1&#46;2 for the parameter leakage was identified using ROC curves with Youden index method&#46;</p><p id="par0085" class="elsevierStylePara elsevierViewall">Taking into account tumor enhancement&#44; all non-enhancing gliomas had leakage values &#60;1&#46;2&#46; When tumor enhancement was present&#44; 42&#46;58&#37; had leakage values &#62;1&#46;2 and the remainder 56&#46;42&#37; had leakage values &#62;1&#46;2&#46; We have not demonstrated a relationship between tumor enhancement and permeability parameters&#46;</p><p id="par0090" class="elsevierStylePara elsevierViewall">All low-grade tumors had leakage values lower than 1&#46;2&#46; In high-grade tumors&#44; 51&#46;2&#37; had leakage values &#60;1&#46;2 and the remainder 48&#46;8&#37; had leakage values &#62;1&#46;2&#46;</p><p id="par0095" class="elsevierStylePara elsevierViewall">Kaplan&#8211;Meier estimates of survival indicated that patients with a leakage mean of less than 1&#46;2 had a significant better OS &#40;Log-rank 8&#46;789&#59; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;003&#41; and PFS &#40;Log-rank 6&#46;612&#59; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;010&#41;&#46; The group of gliomas with leakage values &#62;1&#46;2 had a median overall and progression-free survival of 12 months &#40;95&#37; CI&#44; 3&#46;918&#8211;20&#46;082&#41; and 6 months &#40;95&#37; CI&#44; 4&#46;028&#8211;7&#46;792&#41;&#44; respectively&#46; Patients with leakage values &#60;1&#46;2 had a median progression-free survival of 15 months &#40;95&#37; CI&#44; 3&#46;470&#8211;26&#46;530&#41;&#46; At the end of the follow-up&#44; patients with leakage values lower than 1&#46;2 had not reached median overall survival&#46;</p><p id="par0100" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRefs" href="#fig0015">Figs&#46; 3 and 4</a> represent respectively the significant differences in OS and PFS in diffuse gliomas classified on the basis of the threshold value of 1&#46;2 for the permeability parameter leakage&#46;</p><elsevierMultimedia ident="fig0015"></elsevierMultimedia><elsevierMultimedia ident="fig0020"></elsevierMultimedia><p id="par0105" class="elsevierStylePara elsevierViewall">The remainder permeability parameters showed no significant correlation to survival&#46;</p></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Permeability differences in high-grade tumors classified according to molecular status</span><p id="par0110" class="elsevierStylePara elsevierViewall">In addition&#44; we assessed differences in DSC and DCE-derived permeability parameters in high-grade tumors classified on the basis of IDH&#44; ATRX and MGMT biomarkers&#46;</p><p id="par0115" class="elsevierStylePara elsevierViewall">Among IDH mutant &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>10&#41; and non-mutant &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>26&#41; high-grade gliomas&#44; there were significant differences in leakage &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;004&#41; and Ktrans values &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;028&#41;&#46; Median leakage values were respectively 0&#46;32 and 1&#46;46 for IDH mutant and non-mutant gliomas&#46; Median Ktrans values were 0&#46;13 for IDH mutant and 0&#46;26 for IDH non-mutant high-grade gliomas&#46; IDH mutant high-grade tumors showed lower leakage and Ktrans values&#46;</p><p id="par0120" class="elsevierStylePara elsevierViewall">Among ATRX mutant &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>5&#41; and non-mutant &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>11&#41; high-grade tumors&#44; there were significant differences in leakage &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;005&#41; and Vp values &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;027&#41;&#46; Median leakage values were 0&#46;12 for ATRX mutant and 0&#46;69 for ATRX non-mutant high-grade gliomas&#46; Regarding fractional blood plasma volume&#44; median Vp values were respectively 0&#46;05 and 0&#46;1 for ATRX mutant and non-mutant gliomas&#46; High-grade ATRX mutant tumors presented lower leakage and Vp values&#46;</p><p id="par0125" class="elsevierStylePara elsevierViewall">We have not demonstrated significant differences in perfusion parameters in MGMT methylated &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>13&#41; and non-methylated tumors &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>7&#41;&#46;</p><p id="par0130" class="elsevierStylePara elsevierViewall">In our series&#44; leakage was the best parameter discriminating high-grade gliomas classified based on IDH and ATRX status&#46;</p></span></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0140">Discussion</span><p id="par0135" class="elsevierStylePara elsevierViewall">Conventional contrast-enhanced MRI is not always precise in differentiating high- from low-grade gliomas&#46; Contrast enhancement indicates breakdown of the blood&#8211;brain-barrier&#44; and although is frequently associated with high-grade tumors&#44; it is not always accurate in predicting tumor grade&#46;<a class="elsevierStyleCrossRefs" href="#bib0145"><span class="elsevierStyleSup">5&#44;7</span></a> For this reason&#44; DSC and DCE perfusion MRI have become prognostic biomarkers providing measurements of neoangiogenesis in the preoperative grading of diffuse gliomas&#46;<a class="elsevierStyleCrossRefs" href="#bib0140"><span class="elsevierStyleSup">4&#44;12</span></a> In this study&#44; we have demonstrated a significant correlation between DSC-derived leakage and DCE-derived Ktrans and Vp&#46; Within DCE perfusion MRI&#44; the correlation was specifically significant between Ktrans and Ve &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41;&#44; and between Ktrans and Kep &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41;&#46; We are in agreement with the results previously published by Jia and cols&#44;<a class="elsevierStyleCrossRef" href="#bib0185"><span class="elsevierStyleSup">13</span></a> demonstrating a relationship between Ktrans and Ve&#44; which can be attributed to the fact that Ve values may depend markedly on the permeability of tumor vessels&#46; Unlike Alcaide-Leon and cols&#44;<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">14</span></a> we have not demonstrated a positive correlation between Vp and Ktrans&#44; which may be due to the analysis of both high- and low grade tumors in a relatively small sample series&#46;</p><p id="par0140" class="elsevierStylePara elsevierViewall">Neovascular proliferation is a hallmark in the evaluation of biological aggressiveness and malignancy of gliomas&#46;<a class="elsevierStyleCrossRef" href="#bib0185"><span class="elsevierStyleSup">13</span></a> When contrast agents move from plasma to extravascular extracellular space &#40;EES&#41; through the disrupted endothelial membrane of tumor vessels&#44; the distribution of contrast and magnetic relaxation will change in the intravascular and extravascular spaces&#46;<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">15</span></a> Therefore&#44; the preoperative non-invasive estimation of vascularity is critical in the management of diffuse gliomas&#46;<a class="elsevierStyleCrossRef" href="#bib0185"><span class="elsevierStyleSup">13</span></a> In our study&#44; we have demonstrated significant differences in leakage&#44; Ktrans&#44; Ve and Vp values between high- and low-grade tumors&#46; Higher-grade tumors showed greater values of both DSC and DCE perfusion parameters&#46; Our results&#44; which confirm the usefulness of both DSC and DCE perfusion in the preoperative grading of gliomas&#44; are in agreement with most of the series published to date&#46;<a class="elsevierStyleCrossRefs" href="#bib0145"><span class="elsevierStyleSup">5&#44;13&#44;16</span></a> These results may be explained by the fact that during the development of gliomas&#44; the microvasculature becomes aberrant&#46;<a class="elsevierStyleCrossRef" href="#bib0205"><span class="elsevierStyleSup">17</span></a> Thus&#44; there are more immature and hyperpermeable vessels&#44; and therefore with higher values in permeability parameters&#44; in high-grade than in low-grade gliomas&#46;</p><p id="par0145" class="elsevierStylePara elsevierViewall">As well as Choi et al&#46;<a class="elsevierStyleCrossRef" href="#bib0205"><span class="elsevierStyleSup">17</span></a> published in 2013&#44; Ve appeared to be comparable with Ktrans in differentiating high-grade from low-grade gliomas&#46; In our series&#44; in addition&#44; Ve was the perfusion parameter that best discriminated high- and low-grade tumors &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41;&#46;</p><p id="par0150" class="elsevierStylePara elsevierViewall">The utility of DSC perfusion MRI as a prognostic marker in diffuse gliomas is well recognized&#44; relating relative CBV with overall survival&#46;<a class="elsevierStyleCrossRef" href="#bib0180"><span class="elsevierStyleSup">12</span></a> Previous studies published by Jain<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">18</span></a> and Hirai et al&#46;<a class="elsevierStyleCrossRef" href="#bib0215"><span class="elsevierStyleSup">19</span></a> found that maximum CBV was a predictor of overall survival in glioblastoma&#46; In a previous study of our research team&#44; we have also demonstrated a significant association between CBV and survival in high- and low-grade tumors&#46;<a class="elsevierStyleCrossRef" href="#bib0180"><span class="elsevierStyleSup">12</span></a> However&#44; the use of DCE as a potential biomarker for prognosis has not been so well studied&#46; While Ktrans has been found to increase with glioma grade&#44; its prognostic value remains unclear&#46;<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">2</span></a> In this series&#44; we have analyzed not only the relationship of DCE-derived perfusion parameters with survival&#44; but also the relationship of the parameter leakage to survival&#44; not studied to date&#46;</p><p id="par0155" class="elsevierStylePara elsevierViewall">In our series&#44; DSC-derived leakage was the unique permeability parameter that showed a significant influence on OS &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;006&#41; and PFS &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;012&#41;&#46; In addition&#44; patients who had leakage values below 1&#46;2 had a significant better OS and PFS&#46; This result could be explained in part by the fact that low-grade gliomas are tumors with lower leakage values&#44; which in turn show a more favorable prognosis than high-grade tumors&#46;</p><p id="par0160" class="elsevierStylePara elsevierViewall">The major goal of this study is the assessment of permeability differences in high-grade tumors classified on the basis of molecular biomarkers&#46; To our knowledge&#44; this is the first time that the relationship between ATRX and permeability parameters is analyzed&#46; In gliomas&#44; the most frequent missense mutations in IDH genes are present at the 132 residue in IDH1 &#40;85&#37;&#41; and at 172 in IDH2 &#40;3&#37;&#41;&#46; They have been mainly found in secondary glioblastomas &#40;73&#8211;85&#37;&#41;&#44; and along with grades II and III astrocytic and oligodendroglial tumors &#40;72&#8211;100&#37;&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0220"><span class="elsevierStyleSup">20</span></a></p><p id="par0165" class="elsevierStylePara elsevierViewall">We have demonstrated significant differences in leakage and Ktrans values among IDH-mutated and non-mutated high-grade gliomas&#46; IDH mutant tumors showed lower leakage and Ktrans values&#46; The presence of IDH mutations has been shown to correlate with better survival in patients with glioblastoma&#46;<a class="elsevierStyleCrossRef" href="#bib0220"><span class="elsevierStyleSup">20</span></a> Since lower leakage values are also associated with a longer survival&#44; it would be expected that high-grade IDH-mutated would show lower values in the permeability parameters&#46;</p><p id="par0170" class="elsevierStylePara elsevierViewall">Alterations in the telomere maintenance-related gene ATRX have also been the subject of many investigations into glioma classification and prognosis&#46;<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">21</span></a> ATRX mutations&#44; which are characterized by loss of ATRX protein expression on immunochemistry&#44; occur in nearly 75&#37; of grade II&#8211;III astrocytomas and secondary glioblastomas&#46;<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">22</span></a> Previously&#44; it has been demonstrated that modifications in ATRX gene is not only associated with histologic subgroups&#44; but also related with survival stratifying glioblastomas into prognostically relevant subgroups&#46;<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">23</span></a> Chaurasia et al&#46;<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">23</span></a> have recently exhibited that aberrant expression of ATRX and IDH1 proteins was associated with a significantly increased survival rates&#46;</p><p id="par0175" class="elsevierStylePara elsevierViewall">In our series&#44; we have exhibited that high-grade tumors with ATRX loss presented significantly lower leakage and Vp values&#46; In the same way as with IDH mutation&#44; and probably because most tumors with ATRX loss have also IDH mutation&#44; high-grade gliomas with loss of ATRX expression showed lower leakage values at DSC perfusion MRI&#46; In our series&#44; leakage was the best parameter discriminating high-grade gliomas classified based on IDH and ATRX status&#46;</p><p id="par0180" class="elsevierStylePara elsevierViewall">Disorders of MGMT promoter methylation are related to transcriptional silencing of the MGMT gene&#44; thus permitting alkylating agents to be more effective in patients with MGMT promoter hypermethylation&#46;<a class="elsevierStyleCrossRef" href="#bib0220"><span class="elsevierStyleSup">20</span></a> In our study&#44; we have not found significant differences in permeability parameters in MGMT methylated and non-methylated tumors&#46; Our results are in disagreement with those published in 2014 by Ahn et al&#46;<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">24</span></a> who demonstrated in a group of glioblastomas that Ktrans values were significantly higher in the MGMT methylated group&#46; MGMT methylation is not related to tumor permeability&#44; but predisposes GBM treated with alkylating agents to a better prognosis&#46;</p><p id="par0185" class="elsevierStylePara elsevierViewall">This study has some limitations&#44; such as the retrospective nature&#44; the amount of enrolled patients and the composition of our sample&#44; with a relatively low number of grade II tumors and absence of molecular markers of all high-grade tumors&#46; Through promising&#44; these data need to be confirmed in a larger cohort of patients in an attempt to find permeability differences in MGMT methylated and non-methylated tumors&#46;</p></span><span id="sec0080" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0145">Conclusion</span><p id="par0190" class="elsevierStylePara elsevierViewall">The results of our study demonstrate a significant correlation between the permeability parameters leakage &#40;DSC&#41;&#44; Ktrans and Vp &#40;DCE&#41;&#46; Both DSC and DCE perfusion MRI-derived parameters can serve as a noninvasive method for approximating tumor grade&#46; Ve and Ktrans were the best parameters distinguishing high- and low-grade gliomas&#46; Leakage was the only permeability parameter significantly related to OS and PFS&#59; with prolonged survival for patients with leakage values lower than 1&#46;2&#46; Leakage was also the best parameter discriminating high-grade gliomas classified on the basis of IDH and ATRX status&#46;</p></span><span id="sec0085" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0150">Conflict of interest</span><p id="par0195" class="elsevierStylePara elsevierViewall">None declared&#46;</p></span></span>"
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          "titulo" => "Abbreviations"
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          "titulo" => "Resumen"
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              "titulo" => "Introducci&#243;n y objetivos"
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              "titulo" => "Material y m&#233;todos"
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          "titulo" => "Introduction"
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              "titulo" => "Patient selection and histopathological analysis"
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              "titulo" => "Immunohistochemistry"
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            2 => array:2 [
              "identificador" => "sec0025"
              "titulo" => "MGMT methylation-specific PCR &#40;MSP&#41;"
            ]
            3 => array:2 [
              "identificador" => "sec0030"
              "titulo" => "Magnetic resonance imaging data acquisition"
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              "titulo" => "Image post-processing and perfusion MRI analysis"
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              "titulo" => "Statistical analysis"
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              "titulo" => "Study population"
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              "identificador" => "sec0055"
              "titulo" => "Correlation of DSC and DCE permeability parameters"
            ]
            2 => array:2 [
              "identificador" => "sec0060"
              "titulo" => "Accuracy of DSC and DCE-derived permeability parameters according to tumor grade"
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              "identificador" => "sec0065"
              "titulo" => "Impact of permeability parameters on survival"
            ]
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              "identificador" => "sec0070"
              "titulo" => "Permeability differences in high-grade tumors classified according to molecular status"
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          "titulo" => "Discussion"
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    "pdfFichero" => "main.pdf"
    "tienePdf" => true
    "fechaRecibido" => "2017-12-20"
    "fechaAceptado" => "2018-06-01"
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        0 => array:4 [
          "clase" => "keyword"
          "titulo" => "Keywords"
          "identificador" => "xpalclavsec1065206"
          "palabras" => array:5 [
            0 => "Brain"
            1 => "Glioma"
            2 => "Neoplasms"
            3 => "Perfusion"
            4 => "Permeability"
          ]
        ]
        1 => array:4 [
          "clase" => "abr"
          "titulo" => "Abbreviations"
          "identificador" => "xpalclavsec1065205"
          "palabras" => array:21 [
            0 => "ATRX"
            1 => "AUC"
            2 => "CBV"
            3 => "DCE"
            4 => "DSC"
            5 => "DWI"
            6 => "EES"
            7 => "HR"
            8 => "IDH"
            9 => "IQR"
            10 => "Kep"
            11 => "Ktrans"
            12 => "MGMT"
            13 => "MRI"
            14 => "OS"
            15 => "PFS"
            16 => "ROC"
            17 => "ROI"
            18 => "Vp"
            19 => "Ve"
            20 => "WHO"
          ]
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          "titulo" => "Palabras clave"
          "identificador" => "xpalclavsec1065207"
          "palabras" => array:5 [
            0 => "Cerebro"
            1 => "Gliomas"
            2 => "Neoplasias"
            3 => "Perfusi&#243;n"
            4 => "Permeabilidad"
          ]
        ]
      ]
    ]
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    "resumen" => array:2 [
      "en" => array:3 [
        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Background and purpose</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Our objectives were&#58; &#40;1&#41; compare dynamic susceptibility-weighted &#40;DSC&#41; and dynamic contrast-enhanced &#40;DCE&#41; permeability parameters&#44; &#40;2&#41; evaluate diagnostic accuracy of DSC and DCE discriminating high- and low-grade tumors&#44; &#40;3&#41; analyze relationship of permeability parameters with overall &#40;OS&#41; and progression-free survival &#40;PFS&#41; and &#40;4&#41; assess differences in high-grade tumors classified according to molecular biomarkers&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Materials and methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">49 patients with histologically proved diffuse gliomas underwent DSC and DCE imaging&#46; Parametric maps of cerebral blood volume &#40;CBV&#41;&#44; CBV-leakage corrected&#44; volume transfer coefficient &#40;Ktrans&#41;&#44; fractional volume of the extravascular extracellular space &#40;EES&#41; &#40;Ve&#41;&#44; fractional blood plasma volume &#40;Vp&#41; and rate constant between EES and blood plasma &#40;Kep&#41; were calculated&#46; High-grade gliomas were also classified according to isocitrate dehydrogenase &#40;IDH&#41;&#44; alpha-thalassemia&#47;mental retardation syndrome X-linked &#40;ATRX&#41; and O6-methylguanine-dna-methyltransferase promoter methylation &#40;MGMT&#41; status&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">There is correlation between parameters leakage&#44; Ktrans and Vp&#46; ROC curve analysis showed significance in both Ktrans and Ve for glioma grading&#46; Threshold value of 0&#46;075 for Ve generated the best combination of sensitivity &#40;80&#37;&#41; and specificity &#40;75&#37;&#41; in tumor gradation&#46; Leakage was the only permeability parameter related to OS &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;006&#41; and PFS &#40;0&#46;012&#41;&#59; with prolonged survival for leakage values lower than 1&#46;2&#46; IDH-mutated high-grade tumors showed lower leakage and Ktrans values&#46; High-grade tumors with loss of ATRX presented lower leakage and Vp values&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Both DSC and DCE permeability parameters serve as non-invasive method for glioma grading&#46; Leakage was the unique permeability parameter related to survival and the best discriminating high-grade gliomas classified according to IDH and ATRX status&#46;</p></span>"
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        "titulo" => "Resumen"
        "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Introducci&#243;n y objetivos</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">1&#41; Evaluar la utilidad de los par&#225;metros de permeabilidad para clasificar gliomas de alto y bajo grado&#59; 2&#41; Analizar diferencias de permeabilidad de glioblastomas clasificados seg&#250;n marcadores moleculares&#59; 3&#41; Analizar la relaci&#243;n de la permeabilidad con la supervivencia global &#40;SG&#41; y libre de progresi&#243;n &#40;SLP&#41;&#44; y 4&#41; Comparar par&#225;metros de perfusi&#243;n T1 y T2&#42;&#46;</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Material y m&#233;todos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Cuarenta y nueve pacientes con gliomas difusos confirmados histol&#243;gicamente fueron estudiados con perfusi&#243;n T1 y T2&#42;&#46; Calculamos los mapas param&#233;tricos del volumen sangu&#237;neo cerebral &#40;CBV&#41;&#44; CBV-leakage corregido&#44; constante de permeabilidad &#40;Ktrans&#41;&#44; fracci&#243;n de volumen vascular &#40;Vp&#41;&#44; fracci&#243;n de volumen del espacio intersticial &#40;Ve&#41; y coeficiente de extracci&#243;n &#40;Kep&#41;&#46; El an&#225;lisis histol&#243;gico se bas&#243; en criterios OMS 2007 y los glioblastomas se clasificaron seg&#250;n mutaci&#243;n de genes isocitrato deshidrogenasa &#40;IDH&#41;&#44; Alpha Thalassemia&#47;Mental Retardation Syndrome X-Linked &#40;ATRX&#41; y metilguanidina-ADN metiltransferasa &#40;MGMT&#41;&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Incluimos 28 varones y 21 mujeres &#40;16-78 a&#241;os&#41;&#46; Los gliomas se clasificaron en 41 tumores de alto grado y 8 de bajo grado&#46; Leakage se correlacion&#243; con SG y SLP&#59; y mostr&#243; correlaci&#243;n lineal con Ktrans y Vp&#46; Los gliomas de alto y de bajo grado mostraron diferencias en los valores de leakage&#44; Ktrans&#44; Vp y Ve&#46; Leakage fue el par&#225;metro que mejor discrimin&#243; los glioblastomas clasificados seg&#250;n mutaci&#243;n IDH y ATRX&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusi&#243;n</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">La perfusi&#243;n T1 y T2&#42; sirven para clasificar a los gliomas difusos en funci&#243;n del grado tumoral&#46; Leakage se relaciona con la SG y SLP y es el par&#225;metro que mejor discrimina glioblastomas clasificados en funci&#243;n de IDH y ATRX&#46;</p></span>"
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            "titulo" => "Material y m&#233;todos"
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          3 => array:2 [
            "identificador" => "abst0040"
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          "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Immunostaining for the mutated form of isocitrate dehydrogenase &#40;A&#41; and for the loss of ATRX protein expression &#40;B&#41;&#46;</p>"
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        "etiqueta" => "Fig&#46; 2"
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          "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Receiver operating characteristic curves depicting the true positive rate &#40;specificity&#41; and the false positive rate &#40;sensitivity&#41; of DSC and DCE-MRI perfusion permeability parameters in classifying low- and high-grade gliomas&#46;</p>"
        ]
      ]
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        "identificador" => "fig0015"
        "etiqueta" => "Fig&#46; 3"
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          "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Overall survival calculated by using Kaplan&#8211;Meier curves for all patients stratified by the leakage threshold value of 1&#46;2&#46; Leakage values had a significant influence on overall survival&#46; In our series&#44; the median survival for diffuse gliomas with leakage values higher than 1&#46;2 was 12 months&#46; At the end of the follow-up&#44; patients with leakage values lower than 1&#46;2 had no reached median overall survival&#46;</p>"
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        "etiqueta" => "Fig&#46; 4"
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          "en" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Kaplan&#8211;Meier survival curves of 49 patients with diffuse gliomas&#46; Progression-free survival curves are plotted according to classification based on the cut off value of 1&#46;2 for leakage parameter&#46; Leakage values had also a significant influence on progression-free survival&#44; with a median survival of 15 months for patients with leakage values &#60;1&#46;2 and 6 months for patients with leakage values &#62;1&#46;2&#46;</p>"
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                  <table border="0" frame="\n
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                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head  " align="" valign="top" scope="col">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col">Leakage and Ktrans&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col">Leakage and Vp&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Pearson correlation coefficient&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;310 &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;030&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;727 &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;670 &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;388 &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;006&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
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          "en" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Results of the correlation study performed between DSC and DCE perfusion parameters&#46;</p>"
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                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Leakage&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;13&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;642&#8211;0&#46;919&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">K2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;814&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;005&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;065&#8211;0&#46;307&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Ktrans&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;838&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;003&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;710&#8211;0&#46;967&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Ve&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;878&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;768&#8211;0&#46;988&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Vp&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;741&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;033&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;550&#8211;0&#46;931&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
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          "en" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">ROC curve analysis of permeability parameters for differentiation between high- and low-grade gliomas&#46;</p>"
        ]
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    ]
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      "titulo" => "References"
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        0 => array:2 [
          "identificador" => "bibs0015"
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                  "host" => array:1 [
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