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September 17, 2025

Towards Data-Driven Tractography for Surgical Planning

MMMatthew MuirThe University of Texas MD Anderson Cancer Center KNKyle R. NollThe University of Texas MD Anderson Cancer Center VKVinodh A. KumarThe University of Texas MD Anderson Cancer Center

Key Points

Resecting tracts indicated by TMS at specific thresholds predicts aphasic deficits in brain tumor patients.
Analysis of preoperative DTI and functional MRI data shows promise for individualized surgical planning.
Patient-specific tractography enables targeted identification of essential language regions around tumors.
Findings emphasize the value of data-driven approaches in minimizing neurological morbidity during surgeries.

Abstract

Motivation: For brain tumor patients, surgeons must identify essential language regions surrounding the tumor to minimize neurological morbidity. Goal(s): We aim to develop data-driven approaches for preoperatively identifying the peritumoral regions that are essential for sustaining language function. Approach: This study included 71 surgical glioma patients who underwent preoperative DTI, preoperative cortical language mappings by transcranial magnetic stimulation (TMS) and functional MRI (fMRI), and perioperative language evaluations. Tractography was performed using cortical functional data and normalized diffusion metrics. Results: Resecting tracts localized by TMS cortical language sites at a particular normalized fractional anisotropic threshold strongly predicted aphasic deficits. Impact: These findings outline a data-driven, patient-specific approach for using tractography to localize the language-essential regions surrounding the tumor.

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