Diagnostic performance of gliomas grading and IDH status decoding A comparison between 3D amide proton transfer APT and four diffusion‐weighted MRI models

Abstract

Background: The focus of neuro-oncology research has changed from histopathologic grading to molecular characteristics, and medical imaging routinely follows this change. Purpose: To compare the diagnostic performance of amide proton transfer (APT) and four diffusion models in gliomas grading and isocitrate dehydrogenase (IDH) genotype. Study Type: Prospective. Population: A total of 62 participants (37 males, 25 females; mean age, 52 AE 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/Sequence: APT 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. Assessment: The 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 Tests: T-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. Results: Compared with IDH-mutant gliomas, IDH-wildtype gliomas showed a significantly higher mean, 5th-percentile (APT 5 ), and 95th-percentile from APTw, the 95th-percentile value of axial, mean, and radial diffusivity from DKI, and 95thpercentile 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. APT 5 was significantly different between two of the three groups (glioma II vs. glioma III vs. glioma IV: 1.35 AE 0.75 vs. 2.09 AE 0.93 vs. 2.71 AE 0.81). Data conclusion: APT has higher diagnostic accuracy than DTI, DKI, MAP, and NODDI in glioma IDH genotype. APT 5 can effectively identify both tumor grading and IDH genotyping, making it a promising biomarker for glioma classification.

Predicting Isocitrate Dehydrogenase Status in Non-Contrast-Enhanced Adult-Type Astrocytic Tumors Using Diffusion Tensor Imaging and 11C-Methionine, 11C-Choline, and 18F-Fluorodeoxyglucose PET

“…Although several studies have referred to IDH mutation using M.R. spectroscopy, perfusion, permeability, or chemical exchange saturation transfer imaging, using solely one factor may not suffice for non-contrast-enhanced gliomas [32][33][34][35][36][37]. As molecular diagnosis is becoming greatly important in glioma treatment, a versatile and simple method for predicting genetic differences remains warranted.…”

The combination of radiomics features and VASARI standard to predict glioma grade

“…Therefore, we utilized nested cross-validation to confirm the validity of the predictive model. Second, our study lacked the molecular subtype for the samples, while the molecular phenotype is crucial for the prognosis of glioma ( 49 , 50 ). Future medical imaging research should focus on the molecular characteristics of glioma, which could aid in more accurate subtype prediction and the development of individual treatment strategies.…”

The role of MR diffusion kurtosis and neurite orientation dispersion and density imaging in evaluating gliomas

“…11 According to a previous study, ICVF was found to be surprisingly increased in ischemic areas. 33 .91 for ODI). 14 In the study by Guo et al, mean ICVF and ODI were not statistically different in HGG areas compared to LGG, while ISO increased.…”

“…However, the fact that NODDI was developed for healthy brain tissue is a major limitation 11 . According to a previous study, ICVF was found to be surprisingly increased in ischemic areas 33 . Findings in glioma grading studies related to NODDI are also contradictory.…”