White matter tracts contribute selectively to cognitive functioning in patients with glioma - Andreoli, Mia; Mackie, Melissa-Ann; Aaby, David; Tate, Matthew C. (Frontiers in Oncology, 2023)
Objective The functional organization of white matter (WM) tracts is not well characterized, especially in patients with intrinsic brain tumors where complex patterns of tissue injury, compression, and neuroplasticity may be present. This study uses diffusion tensor imaging (DTI) to investigate the relationships between WM tract disruption and cognitive deficits in glioma patients. Methods Seventy-nine patients with glioma underwent preoperative DTI and neuropsychological testing. Thirteen WM tracts were reconstructed bilaterally. Fractional anisotropy and streamline number were obtained for each tract as indices of connectivity. Univariate regression models were used to model the association between WM tract connectivity and neuropsychological outcomes. Results Glioma patients exhibited variable injury to WM tracts and variable cognitive deficits on validated neuropsychological tests. We identified 16 age-adjusted associations between WM tract integrity and neuropsychological function. The left inferior frontal-occipital fasciculus (IFOF) predicted list learning and dominant-hand fine motor dexterity. The right IFOF predicted non-dominant-hand fine motor dexterity and visuospatial index scores. The left inferior longitudinal fasciculus (ILF) predicted immediate memory list learning and index scores. The right ILF predicted non-dominant-hand fine motor dexterity and backward digit span scores. The left superior longitudinal fasciculus (SLF) I predicted processing speed. The left SLF III predicted list learning, immediate memory index scores, phonemic fluency, and verbal abstract reasoning. The left cingulum predicted processing speed. The right anterior AF predicted verbal abstract reasoning. Conclusion WM tract disruption predicts cognitive dysfunction in glioma patients. By improving knowledge of WM tract organization, this analysis may guide maximum surgical resection and functional preservation in glioma patients.