Visualization of Multimodal Brain Connectivity for Neurosurgical Planning Using Handheld Device Augmented Reality

Abstract

In neurosurgical procedures, precise preoperative planning requires extensive knowledge of the patients' anatomy as well as critical structures for brain functionality. Recently, there has been an increase in the use of minimally invasive approaches, owing in part to advancements in multimodal medical imaging techniques such as structural (SC), and functional-based brain mapping (FC), which have been shown to be useful metrics for surgical trajectory planning. The main challenges associated with their use is the lack of intuitive visualization and interactive methods available to neurosurgeons and trainees. AR systems represent a pivotal advancement towards augmenting the training of trainees as well as providing a platform for senior surgeons to maintain their skills in a low-risk training environment. Advanced image processing was performed on multimodal neuroimaging data (T1-weighted image, diffusion weighted image, resting-state functional magnetic resonance imaging) to characterize the SC and FC of the brain. An AR application, NeuroAR, was designed to take these as inputs and allow the user to visualize and interact with the neuroanatomy in the context of its associated SC and FC. The performances of 10 users on 24 targets were evaluated using an extension of Fitts' methodology. The users were able to use an interactive tool to select and visualize brain regions and their associated fibers. The fibers could be visualized based on their FC scores. As expected, the data showed that task difficulty increased as the volume of the fibers decreased. Movement time also increased as task difficulty increased. We introduced a new mobile device AR application based on data derived from advanced image processing of neuroimaging data. Evaluation of the 3D pointing tasks showed consistency in user performance indicating its utility.