Deep brain stimulation (DBS) is a proven treatment for movement disorders like Parkinson’s disease, dystonia, and essential tremor. However, outcomes vary, and researchers are exploring artificial intelligence (AI) to improve DBS procedures. AI applications focus on target localization and electrical stimulation parameter selection, crucial factors for optimal results.
DBS has been used for over 20 years, benefiting many patients with movement disorders, though outcomes differ. AI shows promise in enhancing DBS protocols, utilizing advanced analysis techniques like machine learning. It can assist in accurately identifying and segmenting target volumes, improving electrode positioning and post-operative programming. AI also has potential in image enhancement and denoising of MRI data, facilitating visualization of DBS targets. Furthermore, algorithms are being developed to guide or automate DBS programming, paving the way for more personalized and efficient treatment.