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Updated: May 9, 2026
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
Optimized Time-Dependent Diffusion MRI for Preoperative Molecular Subtyping of Adult Diffuse Gliomas
Xin Ge1, Ying Shen1, Guangyao Liu1
1From the Department of Radiology (X.G., W.W.), Rehabilitation (Y.S.), Tangdu Hospital, Fourth Military Medical University, Xi'an 710038, Shaanxi, China; Department of Magnetic Resonance (G.L., T.G., W.H., Y.H., J.Z.), Lanzhou University Second Hospital, Gansu Province Clinical Research Center for Functional and Molecular Imaging (G.L., T.G., W.H., Y.H., J.Z.), Gansu Province Medical MRI Equipment Application Industry Technology Center (G.L., T.G., W.H., Y.H., J.Z.), Lanzhou 730030, Gansu, China; MR Research (Y.X.), MR Enhancement Application (M.L.), GE Healthcare, Beijing 100004, China.
Background And Purpose:
Isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion guide preoperative management in adult diffuse gliomas but are usually unknown before tissue sampling, and conventional ADC-based surrogates lack specificity. We evaluated whether an optimized time-dependent diffusion MRI (TDD-MRI) protocol integrating oscillating-gradient spin-echo (OGSE) and pulsed-gradient spin-echo (PGSE) acquisitions with Bayesian IMPULSED mapping can predict these markers preoperatively and validated imaging indices against digital histopathology.
Materials And Methods:
In this study (February 2023-December 2024), adults with suspected intracranial tumors underwent preoperative 3.0-T MRI with high-performance gradients. TDD-MRI included OGSE (20 and 40-Hz) and PGSE acquisitions. Bayesian IMPULSED generated voxelwise extracellular diffusivity (Dex), intracellular volume fraction (fin ), cell diameter (Diameter), and Cellularity; multi-time ADC and ADCratio were also computed. Diagnostic performance was evaluated using logistic regression and receiver-operating-characteristic analysis. Imaging-pathology associations were evaluated using digital hematoxylin-and-eosin metrics.
Results:
Among 119 adult diffuse gliomas (mean age, 51.9±9.1 years), tumors were classified as IDH-wildtype glioblastoma (IDHwt; n=53), IDH-mutant oligodendroglioma with 1p/19q codeletion (IDHmut-codel; n=33), or IDH-mutant astrocytoma with intact 1p/19q (IDHmut-intact; n=33). The intra- and inter-observer reproducibility of ROI measurements by the radiologists was excellent (intraclass correlation coefficients, 0.89-0.97). All microstructural parameters showed significant group differences on overall analysis (P<0.05). In Bonferroni-adjusted post hoc comparisons, IDHwt exhibited higher ADCratio, fin , and Cellularity and lower Dex than other groups, whereas IDHmut-codel had the lowest Cellularity. Among single parameters, ADCratio and Cellularity performed best. Multivariable models achieved AUC 0.95 (95% CI: 0.91-0.99) for identifying IDHmut-codel and 0.95 (95% CI: 0.92-0.99) for IDHwt, each outperforming single-time ADC (P<0.05); performance for IDHmut-intact was moderate (AUC 0.68; 95% CI: 0.59-0.78). Bayesian fitting yielded higher AUCs and more stable maps than nonlinear least squares. Imaging-derived fin , Diameter, and Cellularity correlated with pathology (r = 0.684-0.769, all P<0.001).
Conclusions:
Optimized TDD-MRI with Bayesian IMPULSED provided quantitative microstructural mapping with strong histopathologic concordance and showed promise for the preoperative molecular subtyping of adult diffuse gliomas.
