Dataset Information

Predicting IDH mutation status in grade II gliomas using amide proton transfer-weighted (APTw) MRI.

ABSTRACT:

Purpose

To assess the amide proton transfer-weighted (APTw) MRI features of isocitrate dehydrogenase (IDH)-wildtype and IDH-mutant grade II gliomas and to test the hypothesis that the APTw signal is a surrogate imaging marker for identifying IDH mutation status preoperatively.

Methods

Twenty-seven patients with pathologically confirmed low-grade glioma, who were previously scanned at 3T, were retrospectively analyzed. The Mann-Whitney test was used to evaluate relationships between APTw intensities for IDH-mutant and IDH-wildtype groups, and receiver operator characteristic (ROC) analysis was used to assess the diagnostic performance of APTw.

Results

Based on histopathology and molecular analysis, seven cases were diagnosed as IDH-wildtype grade II gliomas and 20 cases as IDH-mutant grade II gliomas. The maximum and minimum APTw values, based on multiple regions of interest, as well as the whole-tumor histogram-based mean and 50th percentile APTw values, were significantly higher in the IDH-wildtype gliomas than in the IDH-mutant groups. This corresponded to the areas under the ROC curves of 0.89, 0.76, 0.75, and 0.75, respectively, for the prediction of the IDH mutation status.

Conclusion

IDH-wildtype lesions typically were associated with relatively high APTw signal intensities as compared with IDH-mutant lesions. The APTw signal could be a valuable imaging biomarker by which to identify IDH1 mutation status in grade II gliomas. Magn Reson Med 78:1100-1109, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

SUBMITTER: Jiang S

PROVIDER: S-EPMC5561497 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Publications

Predicting IDH mutation status in grade II gliomas using amide proton transfer-weighted (APTw) MRI.

Jiang Shanshan S Zou Tianyu T Eberhart Charles G CG Villalobos Maria A V MAV Heo Hye-Young HY Zhang Yi Y Wang Yu Y Wang Xianlong X Yu Hao H Du Yongxing Y van Zijl Peter C M PCM Wen Zhibo Z Zhou Jinyuan J

Magnetic resonance in medicine 20170716 3

<h4>Purpose</h4>To assess the amide proton transfer-weighted (APTw) MRI features of isocitrate dehydrogenase (IDH)-wildtype and IDH-mutant grade II gliomas and to test the hypothesis that the APTw signal is a surrogate imaging marker for identifying IDH mutation status preoperatively.<h4>Methods</h4>Twenty-seven patients with pathologically confirmed low-grade glioma, who were previously scanned at 3T, were retrospectively analyzed. The Mann-Whitney test was used to evaluate relationships betwee ...[more]

PMID: 28714279

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Project description:Background1p/19q co-deletion in low-grade gliomas (LGG, World Health Organization grade II and III) is of great significance in clinical decision making. We aim to use radiomics analysis to predict 1p/19q co-deletion in LGG based on amide proton transfer weighted (APTw), diffusion weighted imaging (DWI), and conventional MRI.MethodsThis retrospective study included 90 patients histopathologically diagnosed with LGG. We performed a radiomics analysis by extracting 8454 MRI-based features form APTw, DWI and conventional MR images and applied a least absolute shrinkage and selection operator (LASSO) algorithm to select radiomics signature. A radiomics score (Rad-score) was generated using a linear combination of the values of the selected features weighted for each of the patients. Three neuroradiologists, including one experienced neuroradiologist and two resident physicians, independently evaluated the MR features of LGG and provided predictions on whether the tumor had 1p/19q co-deletion or 1p/19q intact status. A clinical model was then constructed based on the significant variables identified in this analysis. A combined model incorporating both the Rad-score and clinical factors was also constructed. The predictive performance was validated by receiver operating characteristic curve analysis, DeLong analysis and decision curve analysis. P < 0.05 was statistically significant.ResultsThe radiomics model and the combined model both exhibited excellent performance on both the training and test sets, achieving areas under the curve (AUCs) of 0.948 and 0.966, as well as 0.909 and 0.896, respectively. These results surpassed the performance of the clinical model, which achieved AUCs of 0.760 and 0.766 on the training and test sets, respectively. After performing Delong analysis, the clinical model did not significantly differ in predictive performance from three neuroradiologists. In the training set, both the radiomic and combined models performed better than all neuroradiologists. In the test set, the models exhibited higher AUCs than the neuroradiologists, with the radiomics model significantly outperforming resident physicians B and C, but not differing significantly from experienced neuroradiologist.ConclusionsOur results suggest that our algorithm can noninvasively predict the 1p/19q co-deletion status of LGG. The predictive performance of radiomics model was comparable to that of experienced neuroradiologist, significantly outperforming the diagnostic accuracy of resident physicians, thereby offering the potential to facilitate non-invasive 1p/19q co-deletion prediction of LGG.

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.

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Dataset Information

Predicting IDH mutation status in grade II gliomas using amide proton transfer-weighted (APTw) MRI.

Purpose

Methods

Results

Conclusion

Publications

Predicting IDH mutation status in grade II gliomas using amide proton transfer-weighted (APTw) MRI.

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