Diffusion Anisotropy Predicts Directional Progression After Complete Resection of Frontal Glioblastoma

Background and Objectives: Despite complete resection of contrast-enhancing tumor, glioblastoma frequently progresses due to microscopic invasion beyond surgical margins. In frontal glioblastoma, functional tolerance of anterior and lateral regions enables consideration of supramaximal resection when invasion direction can be anticipated. Imaging biomarkers that predict post-resection progression direction may thus inform surgical planning. Methods: We performed a retrospective analysis of a prospectively recruited multicenter cohort of patients with newly diagnosed IDH-wildtype frontal glioblastoma who underwent complete resection of contrast-enhancing tumor. Eligible patients had preoperative diffusion tensor imaging (DTI) and longitudinal MRI follow-up. Imaging biomarkers included FLAIR abnormality, isotropic diffusion (DTI-p), and diffusion anisotropy (DTI-q). Directional progression was classified on follow-up imaging. Predictive performance was assessed using accuracy and McNemar’s tests, and associations with progression-free survival (PFS) and overall survival (OS) were evaluated. Results: Of 229 screened patients, 44 had frontal glioblastoma, and 29 underwent complete resection(n=29). Medial (52%) and posterior (48%) progression were most common. DTI-q demonstrated the highest predictive accuracy across directions (median 0.83), outperforming FLAIR and DTI-p (median 0.69), with significantly higher paired accuracy for lateral, superior, and inferior progression(p<0.001). Inferior progression was associated with the poorest survival, whereas medial progression conferred the most favorable outcomes. Medial DTI-q abnormality was associated with prolonged PFS and OS. Invasion patterns suggested lobectomy feasibility in 48% of patients. Conclusion: DTI-q more accurately predicts directional progression of frontal glioblastoma than conventional MRI after complete resection and identifies surgically relevant invasion patterns. Visualization of spatial invasion patterns along white-matter tracts provides a practical framework for directionally tailored resection planning within surgical navigation workflows.