Dataset Information

Addition of Amide Proton Transfer Imaging to FDG-PET/CT Improves Diagnostic Accuracy in Glioma Grading: A Preliminary Study Using the Continuous Net Reclassification Analysis.

ABSTRACT: BACKGROUND AND PURPOSE:Amide proton transfer imaging has been successfully applied to brain tumors, however, the relationships between amide proton transfer and other quantitative imaging values have yet to be investigated. The aim was to examine the additive value of amide proton transfer imaging alongside [18F] FDG-PET and DWI for preoperative grading of gliomas. MATERIALS AND METHODS:Forty-nine patients with newly diagnosed gliomas were included in this retrospective study. All patients had undergone MR imaging, including DWI and amide proton transfer imaging on 3T scanners, and [18F] FDG-PET. Logistic regression analyses were conducted to examine the relationship between each imaging parameter and the presence of high-grade (grade III and/or IV) glioma. These parameters included the tumor-to-normal ratio of FDG uptake, minimum ADC, mean amide proton transfer value, and their combinations. In each model, the overall discriminative power for the detection of high-grade glioma was assessed with receiver operating characteristic curve analysis. Additive information from minimum ADC and mean amide proton transfer was also evaluated by continuous net reclassification improvement. P < .05 was considered significant. RESULTS:Tumor-to-normal ratio, minimum ADC, and mean amide proton transfer demonstrated comparable diagnostic accuracy in differentiating high-grade from low-grade gliomas. When mean amide proton transfer was combined with the tumor-to-normal ratio, the continuous net reclassification improvement was 0.64 (95% CI, 0.036-1.24; P = .04) for diagnosing high-grade glioma and 0.95 (95% CI, 0.39-1.52; P = .001) for diagnosing glioblastoma. When minimum ADC was combined with the tumor-to-normal ratio, the continuous net reclassification improvement was 0.43 (95% CI, -0.17-1.04; P = .16) for diagnosing high-grade glioma, and 1.36 (95% CI, 0.79-1.92; P < .001) for diagnosing glioblastoma. CONCLUSIONS:Addition of amide proton transfer imaging to FDG-PET/CT may improve the ability to differentiate high-grade from low-grade gliomas.

SUBMITTER: Sakata A

PROVIDER: S-EPMC7410581 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Addition of Amide Proton Transfer Imaging to FDG-PET/CT Improves Diagnostic Accuracy in Glioma Grading: A Preliminary Study Using the Continuous Net Reclassification Analysis.

Sakata A A Okada T T Yamamoto Y Y Fushimi Y Y Dodo T T Arakawa Y Y Mineharu Y Y Schmitt B B Miyamoto S S Togashi K K

AJNR. American journal of neuroradiology 20180104 2

<h4>Background and purpose</h4>Amide proton transfer imaging has been successfully applied to brain tumors, however, the relationships between amide proton transfer and other quantitative imaging values have yet to be investigated. The aim was to examine the additive value of amide proton transfer imaging alongside [<sup>18</sup>F] FDG-PET and DWI for preoperative grading of gliomas.<h4>Materials and methods</h4>Forty-nine patients with newly diagnosed gliomas were included in this retrospective ...[more]

PMID: 29301781

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Project description:Background and purposePrognosis in glioma depends strongly on tumor grade and proliferation. In this prospective study of patients with untreated primary cerebral gliomas, we investigated whether amide proton transfer-weighted imaging could reveal tumor proliferation and reliably distinguish low-grade from high-grade gliomas compared with Ki-67 expression and proton MR spectroscopy imaging.Materials and methodsThis study included 42 patients with low-grade (n = 28) or high-grade (n = 14) glioma, all of whom underwent conventional MR imaging, proton MR spectroscopy imaging, and amide proton transfer-weighted imaging on the same 3T scanner within 2 weeks before surgery. We assessed metabolites of choline and N-acetylaspartate from proton MR spectroscopy imaging and the asymmetric magnetization transfer ratio at 3.5 ppm from amide proton transfer-weighted imaging and compared them with histopathologic grade and immunohistochemical expression of the proliferation marker Ki-67 in the resected specimens.ResultsThe asymmetric magnetization transfer ratio at 3.5 ppm values measured by different readers showed good concordance and were significantly higher in high-grade gliomas than in low-grade gliomas (3.61% ± 0.155 versus 2.64% ± 0.185, P = .0016), with sensitivity and specificity values of 92.9% and 71.4%, respectively, at a cutoff value of 2.93%. The asymmetric magnetization transfer ratio at 3.5 ppm values correlated with tumor grade (r = 0.506, P = .0006) and Ki-67 labeling index (r = 0.502, P = .002). For all patients, the asymmetric magnetization transfer ratio at 3.5 ppm correlated positively with choline (r = 0.43, P = .009) and choline/N-acetylaspartate ratio (r = 0.42, P = .01) and negatively with N-acetylaspartate (r = -0.455, P = .005). These correlations held for patients with low-grade gliomas versus those with high-grade gliomas, but the correlation coefficients were higher in high-grade gliomas (choline: r = 0.547, P = .053; N-acetylaspartate: r = -0.644, P = .017; choline/N-acetylaspartate: r = 0.583, P = .036).ConclusionsThe asymmetric magnetization transfer ratio at 3.5 ppm may serve as a potential biomarker not only for assessing proliferation, but also for predicting histopathologic grades in gliomas.

Project description:Net reclassification indices have recently become popular statistics for measuring the prediction increment of new biomarkers. We review the various types of net reclassification indices and their correct interpretations. We evaluate the advantages and disadvantages of quantifying the prediction increment with these indices. For predefined risk categories, we relate net reclassification indices to existing measures of the prediction increment. We also consider statistical methodology for constructing confidence intervals for net reclassification indices and evaluate the merits of hypothesis testing based on such indices. We recommend that investigators using net reclassification indices should report them separately for events (cases) and nonevents (controls). When there are two risk categories, the components of net reclassification indices are the same as the changes in the true- and false-positive rates. We advocate the use of true- and false-positive rates and suggest it is more useful for investigators to retain the existing, descriptive terms. When there are three or more risk categories, we recommend against net reclassification indices because they do not adequately account for clinically important differences in shifts among risk categories. The category-free net reclassification index is a new descriptive device designed to avoid predefined risk categories. However, it experiences many of the same problems as other measures such as the area under the receiver operating characteristic curve. In addition, the category-free index can mislead investigators by overstating the incremental value of a biomarker, even in independent validation data. When investigators want to test a null hypothesis of no prediction increment, the well-established tests for coefficients in the regression model are superior to the net reclassification index. If investigators want to use net reclassification indices, confidence intervals should be calculated using bootstrap methods rather than published variance formulas. The preferred single-number summary of the prediction increment is the improvement in net benefit.

Project description:BackgroundThe focus of neuro-oncology research has changed from histopathologic grading to molecular characteristics, and medical imaging routinely follows this change.PurposeTo compare the diagnostic performance of amide proton transfer (APT) and four diffusion models in gliomas grading and isocitrate dehydrogenase (IDH) genotype.Study typeProspective.PopulationA total of 62 participants (37 males, 25 females; mean age, 52 ± 13 years) whose IDH genotypes were mutant in 6 of 14 grade II gliomas, 8 of 20 of grade III gliomas, and 4 of 28 grade IV gliomas.Field strength/sequenceAPT imaging using sampling perfection with application optimized contrasts by using different flip angle evolutions (SPACE) and DWI with q-space Cartesian grid sampling were acquired at 3 T.AssessmentThe ability of diffusion kurtosis imaging, diffusion kurtosis imaging, neurite orientation dispersion and density imaging (NODDI), mean apparent propagator (MAP), and APT imaging for glioma grade and IDH status were assessed, with histopathological grade and genetic testing used as a reference standard. Regions of interest (ROIs) were drawn by two neuroradiologists after consensus.Statistical testsT-test and Mann-Whitney U test; one-way analysis of variance (ANOVA); receiver operating curve (ROC) and area under the curve (AUC); DeLong test. P value < 0.05 was considered statistically significant.ResultsCompared with IDH-mutant gliomas, IDH-wildtype gliomas showed a significantly higher mean, 5th-percentile (APT5 ), and 95th-percentile from APTw, the 95th-percentile value of axial, mean, and radial diffusivity from DKI, and 95th-percentile value of isotropic volume fraction from NODDI, and no significantly different parameters from DTI and MAP (P = 0.075-0.998). The combined APT model showed a significantly wider area under the curve (AUC 0.870) for IDH status, when compared with DKI and NODDI. APT5 was significantly different between two of the three groups (glioma II vs. glioma III vs. glioma IV: 1.35 ± 0.75 vs. 2.09 ± 0.93 vs. 2.71 ± 0.81).Data conclusionAPT has higher diagnostic accuracy than DTI, DKI, MAP, and NODDI in glioma IDH genotype. APT5 can effectively identify both tumor grading and IDH genotyping, making it a promising biomarker for glioma classification.Evidence level1 TECHNICAL EFFICACY: Stage 2.

Dataset Information

Addition of Amide Proton Transfer Imaging to FDG-PET/CT Improves Diagnostic Accuracy in Glioma Grading: A Preliminary Study Using the Continuous Net Reclassification Analysis.

Publications

Addition of Amide Proton Transfer Imaging to FDG-PET/CT Improves Diagnostic Accuracy in Glioma Grading: A Preliminary Study Using the Continuous Net Reclassification Analysis.

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