Validation of Presurgical Simulation of White Matter Damage Using Diffusion Tensor Imaging

Area of Science:

• Neurosurgery
• Medical Imaging
• Computational Neuroscience

Background:

• Diffusion tensor imaging (DTI) and tractography revolutionized white matter (WM) understanding.
• DTI simulations are used in preoperative planning but their reliability in predicting surgical injury is questioned.
• Previous studies focused on correlating DTI parameters with neurological performance, not surgical injury prediction.

Purpose of the Study:

• To assess the reliability of preoperatively simulated white matter (WM) injuries for conventional neurosurgical procedures.
• To evaluate the consistency of DTI-based WM simulations with actual postoperative surgical damage.
• To determine if preoperative WM simulations can accurately predict surgical-induced injuries.

Main Methods:

• White matter (WM) surgical damage was simulated by creating 3D volumes of surgical trajectories.
• Simulated injured fascicles were compared to postoperative DTI studies in terms of fiber count and volume.
• Reliability was assessed using intraclass correlation coefficient, Lin's Concordance correlation coefficient (CCC), and Bland-Altman plots.

Main Results:

• High correlation was found between simulated and postoperative DTI studies for both fiber count (CCC = 0.989) and volume (ICC = 0.95).
• Bland-Altman plots indicated that most cases fell within the mean ± 2 standard deviations, showing good agreement.
• The study included 30 patients undergoing various neurosurgical approaches.

Conclusions:

• Presurgical simulation of white matter (WM) fascicles using DTI is consistent with postoperative findings.
• These findings suggest that DTI-based simulations are reliable for predicting surgical injuries.
• Further validation through neurophysiological and clinical correlation is recommended.