Neuronavigation Based on Track Density Image Extracted from Deterministic High-Definition Fiber Tractography

BACKGROUND: Diffusion tensor imaging-based navigation is unable to resolve crossing fibers or to determine with accuracy the fanning, origin, and termination of fibers. It is important to improve the accuracy of localizing white matter fibers for improved surgical approaches. We propose a solution to this problem using navigation based on track density imaging extracted from high definition fiber tractography (HDFT). CASE DESCRIPTION: A 28-year-old asymptomatic female patient with a leftlateral ventricle meningioma was enrolled in the present study. Language and visual tests, magnetic resonance imaging findings, both preoperative and postoperative HDFT, and the intraoperative navigation and surgery process are presented. Track density images were extracted from tracts derived using full q-space (514 directions) diffusion spectrum imaging (DSI) and integrated into a neuronavigation system. Navigation accuracy was verified via intraoperative records and postoperative DSI tractography, as well as a functional examination. DSI successfully represented the shape and range of the Meyer loop and arcuate fasciculus. Extracted track density images from the DSI were successfully integrated into the navigation system. The relationship between the operation channel and surrounding tracts was consistent with the postoperative findings, and the patient was functionally intact after the surgery. CONCLUSIONS: DSI-based TDI navigation allows for the visualization of anatomic features such as fanning and angling and helps to identify the range of a given tract. Moreover, our results show that our HDFT navigation method is a promising technique that preserves neural function.