Real‐Time Tractography‐Assisted Neuronavigation for Transcranial Magnetic Stimulation

• Published in: Human brain mapping 2025-01, Vol.46 (1), p.e70122-n/a
• Main Authors: Aydogan, Dogu Baran, Souza, Victor H., Matsuda, Renan H., Lioumis, Pantelis, Ilmoniemi, Risto J.
• Format: Article
• Language: English
• Subjects: Adult; Angular resolution; Axonal transport; Brain; Brain - diagnostic imaging; Brain - physiology; brain stimulation; Broca's area; Computer Systems; connectivity; Cortex (motor); diffusion MRI; Diffusion Tensor Imaging - methods; Electric fields; Feasibility Studies; Female; Frontal lobe; Humans; Image Processing, Computer-Assisted - methods; Interactive systems; Magnetic fields; Magnetic resonance imaging; Male; Mental depression; Modular systems; Neural networks; Neuroimaging; neuronavigation; Neuronavigation - methods; Open source software; Parameter uncertainty; Synthetic data; TMS; tractography; Transcranial magnetic stimulation; Transcranial Magnetic Stimulation - methods; Tuning; Uncertainty analysis; Visual cortex; Visual observation; Visualization; Young Adult
• ISSN: 1065-9471; 1097-0193; 1097-0193
• DOI: 10.1002/hbm.70122

ABSTRACT State‐of‐the‐art navigated transcranial magnetic stimulation (nTMS) systems can display the TMS coil position relative to the structural magnetic resonance image (MRI) of the subject's brain and calculate the induced electric field. However, the local effect of TMS propagates via the white‐matter network to different areas of the brain, and currently there is no commercial or research neuronavigation system that can highlight in real time the brain's structural connections during TMS. This lack of real‐time visualization may overlook critical inter‐individual differences in brain connectivity and does not provide the opportunity to target brain networks. In contrast, real‐time tractography enables on‐the‐fly parameter tuning and detailed exploration of connections, which is computationally inefficient and limited with offline methods. To target structural brain connections, particularly in network‐based treatments like major depressive disorder, a real‐time tractography‐based neuronavigation solution is needed to account for each individual's unique brain connectivity. The objective of this work is to develop a real‐time tractography‐assisted TMS neuronavigation system and investigate its feasibility. We propose a modular framework that seamlessly integrates offline (preparatory) analysis of diffusion MRI data with online (real‐time) probabilistic tractography using the parallel transport approach. For tractography and neuronavigation, we combine our open source software Trekker and InVesalius, respectively. We evaluate our system using synthetic data and MRI scans of four healthy volunteers obtained using a multi‐shell high‐angular resolution diffusion imaging protocol. The feasibility of our online approach is assessed by studying four major TMS targets via comparing streamline count and overlap against offline tractography results based on filtering of one hundred million streamlines. Our development of a real‐time tractography‐assisted TMS neuronavigation system showcases advanced tractography techniques, with interactive parameter tuning and real‐time visualization of thousands of streamlines via an innovative uncertainty visualization method. Our analysis reveals considerable variability among subjects and TMS targets in the streamline count, for example, while 15,000 streamlines were observed for the TMS target on the visual cortex (V1) of subject #4, in the case of subject #3's V1, no streamlines were obtained. Overlap analysis against off