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Predicting IDH Mutation Status of Grade 2-4 Gliomas with DTI Parameters Derived from Model-based DTI and Model-free Q-Sampling Imaging Reconstructions.

Sabahattin Yuzkan,Samet Mutlu,Mehmet Han,Tuce Soylemez Akkurt,F. Şencan,F. Kuşku Çabuk,O. Gunaldi,B. Tugcu,B. Koçak

Published 2023 in World Neurosurgery

ABSTRACT

OBJECTIVE To determine if diffusion tensor imaging (DTI) parameters acquired with model-based DTI and model-free Q-sampling imaging (GQI) reconstructions may noninvasively predict isocitrate dehydrogenase (IDH) mutational status in patients with grade 2-4 gliomas. METHODS Forty patients with known IDH genotype (28 IDH wild-type; 12 IDH mutant) who underwent preoperative DTI evaluation on a 3 Tesla MRI scanner were retrospectively analyzed. Absolute values obtained from model-based and model-free reconstructions were compared. Using the intraclass correlation coefficient, interobserver agreement was assessed for various sampling techniques. Variables having statistically significant distributions between IDH groups were subjected to a receiver operating characteristic (ROC) analysis. Using multivariable logistic regression analysis, independent predictors, if present, were identified and a model was developed. RESULTS Six imaging parameters (3 from model-based DTI and 3 from model-free GQI reconstructions) showed statistically significant differences between groups (p <0.001, power >0.97), with very high correlation to each other (p <0.001). Age difference between the groups was statistically significant (p <0.001). Optimal logistic regression model comprised a GQI-based parameter and age, which were independent predictors as well, producing an area under the ROC curve, accuracy, sensitivity, and specificity of 0.926, 85%, 75%, and 89%, respectively. Using the GQI reconstruction feature alone with a cut-off of 1.60, an 85% of accuracy was also achieved with ROC analysis. CONCLUSIONS The imaging parameters acquired from model-based DTI and model-free GQI reconstructions, combined with the clinical variable age, may have the ability to non-invasively predict the IDH genotype in gliomas, either alone or in particular combinations.

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