Abstract
OBJECTIVE
The objective of this study was to investigate the mechanisms of motor compensation in glioma patients by quantifying both the structural decoupling index (SDI) value and the integrity of transcallosal white matter tracts. The authors aimed to evaluate their individual and combined utility in predicting long-term postoperative motor outcomes.
METHODS
Seventy patients with motor area gliomas and 23 healthy controls were retrospectively included. All participants underwent preoperative 3T resting-state fMRI and diffusion MRI. The SDI value was computed using a graph signal processing approach to quantify the decoupling between functional activity and structural connectivity. White matter integrity and disconnection severity of the corpus callosum were assessed using TractSeg and tractography. Motor function was evaluated using the Medical Research Council scale preoperatively and at the 3-month follow-up. Statistical analyses included group comparisons, correlation analyses, and multivariate logistic regression to identify predictors of severe motor impairment (SMI).
RESULTS
Glioma patients exhibited altered SDI values in motor-related regions, including the precentral gyrus and thalamus. A higher SDI value in the contralateral precentral gyrus was associated with better motor recovery (p = 0.00025), while greater disconnection severity in the anterior midbody of the corpus callosum (CC4) correlated with poorer motor function (p = 0.00041). Multivariate analysis identified IDH-wildtype status, higher CC4 disconnection severity, and lower contralateral precentral gyrus SDI value as independent predictors of SMI. A nomogram integrating these factors showed excellent predictive accuracy (C-index = 0.914).
CONCLUSIONS
The SDI captures adaptive functional decoupling in the contralateral motor cortex, which may be associated with compensatory mechanisms in glioma patients. Combined with callosal integrity, the SDI enhances the prediction of postoperative motor outcomes, offering a novel biomarker for preoperative risk stratification and personalized rehabilitation planning.