Identifying Imaging Biomarkers of Deep Brain Stimulation Treatment Outcome in Patients with Movement Disorders

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Deep Brain Stimulation (DBS) is a clinical, neurosurgical procedure, involving the implantation of electrodes to specified target regions in the brain. DBS offers itself as an established treatment option for symptoms across a wide range of disorders, including Parkinson's disease (PD), Essential tremor (ET), Dystonia, Tourette Syndrome, Epilepsy and Obsessive-Compulsive Disorder. An area of clinical application where DBS has seen profound success is in the alleviation of debilitating motor symptoms associated with motor disorders. Specifically, DBS has been used extensively to treat patients with PD, ET, and Dystonia, becoming the primary therapeutic option for pharmacologically refractory patients.Crucially, there is a wide variability in the post-operative efficacy of DBS with relation to the improvement in motor symptoms, resulting in optimal and sub-optimal outcomes. Wide variability of DBS is likely due to a multitude of factors, including the neurosurgically targeted area, heterogeneity of brain structure and function, DBS stimulation parameters, disease phenotype, and disease severity. DBS variability is also critically confounded by the fact that the underlying mechanisms for exactly how DBS works are not fully understood at this current moment in time.One possible avenue being explored to shed light on the variability in post-surgical DBS outcomes is through Neuroimaging. Magnetic Resonance Imaging (MRI) in particular, is a technique that has paved our understanding of the relationship between changes in the brain and a plethora of neurological diseases and disorders. This project is specifically aimed at utilising routinely collected presurgical MRI to ascertain clinically useful, novel preoperative biomarkers to predict DBS efficacy. In particular, the project aims to assess data pertaining to differences in brain morphology and structural connectivity, utilising various advanced neuroimaging and machine learning analysis techniques. Preoperative patient data from a variety of movement disorders will be acquired at the Walton Centre NHS Foundation Trust and from open-access repositories.This project has far-reaching ramifications for improving clinical motor outcomes from DBS. Identifying patients who will be optimally responsive to treatment will aid the future selection of DBS candidates, improving disease management within health care systems. Understanding and improving outcomes for patients who respond sub-optimally is also critical to improve quality of life and inform disease management. Furthermore, identifying imaging modalities that can prove useful for biomarker prediction can be incorporated into clinical scanning protocols. Finally, this project hopes to supplement our understanding of DBS operativity mechanisms across different movement disorders.