Automatic Trajectory Planning for Deep Brain Stimulation: A Feasibility Study

Abstract

Abstract. DBS for Parkinson's disease involves an extensive planning to find a suitable electrode implantation path to the selected target. We have investigated the feasibility of improving the conventional planning with an automatic calculation of possible paths in 3D. This requires the segmentation of anatomical structures. Subsequently, the paths are calculated and visualized. After selection of a suitable path, the settings for the stereotactic frame are determined. A qualitative evaluation has shown that automatic avoidance of critical structures is feasible. The participating neurosurgeons estimate the time gain to be around 30 minutes.

Guiding Deep Brain Stimulation interventions by fusing multimodal uncertainty regions

“…The entry point is varied while, for each trajectory, a cost function is evaluated and the system operator selects the best trajectory. Bruneberg et al facilitated a segmentation of the STN and determined the optimal trajectory by avoiding ventricles, gyri, and blood vessels, which need to be segmented beforehand [5]. Khlebnikov et al suggested a system to find optimal access paths by interpreting tumors as light sources and determining the cost-function based on light transport [15].…”

Automatic Trajectory Planning of DBS Neurosurgery from Multi-modal MRI Datasets

“…In other related work [6,[8][9][10], trajectory optimization is based on a pre-calculated distance map that encodes the minimal distance of a voxel from a critical structure. This method is computationally efficient because the distance map is computed only once and applied to every trajectory.…”

“…The weights are chosen by the neurosurgeons to represent the relative importance of each constraint. A greater weight is usually given to the risk max criterion because almost hitting a critical structure once is more severe than approaching the same critical structure multiple times at a safer distance [8]. On the other hand, the sum criterion is useful because it distinguishes among cases where a trajectory approaches a critical structure once or multiple times along the path [9].…”

“…Many methods encode critical structures once in an atlas [5][6][7] although recent methods favor direct segmentation in the native patient datasets to better account for inter-subject variability, especially for important structures such as sulci and blood vessels. Very relevant to our work, the method of Brunenberg et al [8] returns many valid trajectories with no further ranking. In the work of Shamir et al [9], trajectories are ranked separately according to either a maximal risk or a sum or risks criteria with no further aggregation.…”

GPU-Accelerated Interactive Visualization and Planning of Neurosurgical Interventions

“…A common practice is manual selection and assessment of the suitability of different entrance positions on the scalp surface of the patient in order to select an appropriate insertion path. To process, visualize and manipulate large volumes of 3D imaging datasets, automated surgical planning methods have been proposed in recent years [1], [2], [3], [4], [5], [6]. The current trend is to move as much of the planning tasks as possible into the operating room to avoid errors that can appear because of the discrepancies between pre-operative images and intra-operative images.…”