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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.
Optimized time-dependent diffusion MRI (TDD-MRI) accurately predicts molecular subtypes of adult diffuse gliomas, outperforming conventional methods. This non-invasive approach shows strong correlation with digital histopathology, aiding preoperative management.
Area of Science:
- Neuroimaging
- Oncology
- Radiology
Background:
- Isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion are crucial for guiding adult diffuse glioma management but are typically unknown preoperatively.
- Conventional diffusion MRI (dMRI) surrogates lack the specificity to accurately predict these molecular markers.
Purpose of the Study:
- To evaluate an optimized time-dependent diffusion MRI (TDD-MRI) protocol using oscillating-gradient spin-echo (OGSE) and pulsed-gradient spin-echo (PGSE) acquisitions with Bayesian IMPULSED mapping.
- To predict IDH mutation and 1p/19q codeletion status preoperatively in adult diffuse gliomas.
- To validate imaging-derived indices against digital histopathology.
Main Methods:
- Adults with suspected intracranial tumors underwent preoperative 3.0-T MRI with a TDD-MRI protocol (OGSE and PGSE).
- Bayesian IMPULSED mapping generated voxelwise microstructural parameters (extracellular diffusivity, intracellular volume fraction, cell diameter, cellularity).
- Diagnostic performance was assessed using logistic regression and receiver-operating-characteristic analysis; imaging-pathology associations were evaluated using digital histopathology metrics.
Main Results:
- The study included 119 adult diffuse gliomas classified into IDH-wildtype glioblastoma (IDHwt), IDH-mutant oligodendroglioma with 1p/19q codeletion (IDHmut-codel), and IDH-mutant astrocytoma with intact 1p/19q (IDHmut-intact).
- Multivariable models achieved high AUCs (0.95) for identifying IDHmut-codel and IDHwt, outperforming single-time ADC.
- Imaging-derived microstructural parameters demonstrated strong correlations with digital histopathology findings (r = 0.684-0.769, P<0.001).
Conclusions:
- Optimized TDD-MRI with Bayesian IMPULSED mapping provides quantitative microstructural information with significant histopathologic concordance.
- This advanced MRI technique shows considerable promise for the non-invasive preoperative molecular subtyping of adult diffuse gliomas.
