Obsessive-compulsive disorder (OCD) is a chronic mental illness affecting 4-7 million people in the US. Patients are impaired in multiple Research Domain constructs. Medication and behavioral therapies yield inadequate symptom relief in 50-70% of patients. As a result, OCD remains a leading worldwide cause of disability, equivalent to more visible disorders such as schizophrenia. Roughly 1/3 of patients are unable to work due to their symptoms and their caregivers report profound, life-impairing stress. More recently, the field has focused on deep brain stimulation (DBS). However, about a third of the patients who undergo DBS receive no meaningful benefit. We propose a primarily retrospective investigation of imaging-based targeting for Deep Brain Stimulation (DBS) for severe obsessive-compulsive disorder (OCD).
We aim to increase response rates while testing imaging biomarkers that could guide therapeutic intervention. Our hospital is the highest-volume site in the US using DBS at the ventral capsule/ventral striatum (VC/VS) for the treatment of intractable OCD. A major contributor to imperfect response is that DBS is implanted at standard coordinates across patients, without accounting for variation in VC/VS anatomy. Our investigation will study imaging markers that may target ventral capsule/ventral striatum (VC/VS) for DBS to patient-specific brain circuitry. We hypothesize that clinical response will be related to the degree that the DBS electrical field influences orbitofronto-thalamic fibers and the nucleus accumbens grey matter. If we are successful in identifying a biomarker during this three-year retrospective study, a future prospective clinical trial will target DBS implants to the newly identified structures in a patient-specific fashion.
We propose a retrospective investigation of imaging-based targeting for Deep Brain Stimulation (DBS) for severe obsessive-compulsive disorder (OCD). We will use anatomic and functional connectivity analyses, plus electrical modeling, to identify white and grey matter zones that must be captured by the electrical stimulation to yield clinical response. We expect that this will identify biomarkers that will enable more precise targeting of future implants, improving response rates over the current 30-50% non-response.
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