Research

This project focusses on standardization of DBS-surgery in a way that all patient-specific data that can be recorded in a pre-operative setting (e.g. disease characteristics, structural brain information, brain connectivity) will be used to optimize the surgical planning tailored to the individual patient. The algorithm will automatically provide the optimal surgical plan and verify the accuracy of lead placement, once fed the correct input data. This project will lead to more uniformity in how DBS-surgery is performed worldwide with better therapy efficacy, less side-effects and less long-term revision surgery due to inaccurate lead placement.

The development of algorithms that accurately predict and visualize activation of favorable and unfavorable pathways is an essential ingredient for MRI-guided programming of DBS. With this algorithm, the conventional trial-and-error-based programming of DBS can get replaced by patient-specific MRI-guided and computer-assisted programming.

Our lab is working on developing tools to automate the process of programming DBS. Programming DBS is usually a long-lasting process with and a huge burden for both patients and clinicians. With the step-by-step development of reliable biomarkers and algorithms that can integrate all available information and are able to adjust stimulation parameters in an automated and closed-loop fashion, we tend to move the field towards automated programming of DBS-systems.