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Deep brain stimulation targeting the subcallosal cingulate area, a hub with multiple axonal projections, has shown therapeutic potential for treatment-resistant mood disorders. While subcallosal cingulate deep brain stimulation drives long-term metabolic changes in corticolimbic circuits, the brain areas that are directly modulated by electrical stimulation of this region are not known. We used 3.0 T functional MRI to map the topography of acute brain changes produced by stimulation in an initial cohort of 12 patients with fully implanted deep brain stimulation devices targeting the subcallosal cingulate area. Four additional subcallosal cingulate deep brain stimulation patients were also scanned and employed as a validation cohort. Participants underwent resting state scans (n = 78 acquisitions overall) during (i) inactive deep brain stimulation; (ii) clinically optimal active deep brain stimulation; and (iii) suboptimal active deep brain stimulation. All scans were acquired within a single MRI session, each separated by a 5-min washout period. Analysis of the amplitude of low-frequency fluctuations in each sequence indicated that clinically optimal deep brain stimulation reduced spontaneous brain activity in several areas, including the bilateral dorsal anterior cingulate cortex, the bilateral posterior cingulate cortex, the bilateral precuneus and the left inferior parietal lobule (PBonferroni These results provide insight into the network-level mechanisms of subcallosal cingulate deep brain stimulation and point towards potential acute biomarkers of clinical response that could help to optimize and personalize this therapy.

Subcallosal cingulate deep brain stimulation produces long-term clinical improvement in approximately half of patients with severe treatment-resistant depression. We hypothesized that both structural and functional brain attributes may be important in determining responsiveness to this therapy.In a treatment-resistant depression subcallosal cingulate deep brain stimulation cohort, we retrospectively examined baseline and longitudinal differences in MRI-derived brain volume (n = 65) and 18F-fluorodeoxyglucose-PET glucose metabolism (n = 21) between responders and non-responders. Support vector machines were subsequently trained to classify patients’ response status based on extracted baseline imaging features. A machine learning model incorporating preoperative frontopolar, precentral/frontal opercular and orbitofrontal local volume values classified binary response status (12 months) with 83% accuracy [leave-one-out cross-validation (LOOCV): 80% accuracy] and explained 32% of the variance in continuous clinical improvement. It was also predictive in an out-of-sample subcallosal cingulate deep brain stimulation cohort (n = 21) with differing primary indications (bipolar disorder/anorexia nervosa; 76% accuracy). Adding preoperative glucose metabolism information from rostral anterior cingulate cortex and temporal pole improved model performance, enabling it to predict response status in the treatment-resistant depression cohort with 86% accuracy (LOOCV: 81% accuracy) and explain 67% of clinical variance. Response-related patterns of metabolic and structural post-deep brain stimulation change were also observed, especially in anterior cingulate cortex and neighbouring white matter. Areas where responders differed from non-responders—both at baseline and longitudinally—largely overlapped with depression-implicated white matter tracts, namely uncinate fasciculus, cingulum bundle and forceps minor/rostrum of corpus callosum. The extent of patient-specific engagement of these same tracts (according to electrode location and stimulation parameters) also served as an independent predictor of treatment-resistant depression response status (72% accuracy; LOOCV: 70% accuracy) and augmented performance of the volume-based (88% accuracy; LOOCV: 82% accuracy) and combined volume/metabolism-based support vector machines (100% accuracy; LOOCV: 94% accuracy).Taken together, these results indicate that responders and non-responders to subcallosal cingulate deep brain stimulation exhibit differences in brain volume and metabolism, both pre- and post-surgery. Moreover, baseline imaging features predict response to treatment (particularly when combined with information about local tract engagement) and could inform future patient selection and other clinical decisions.

Obsessive-compulsive disorder is a debilitating and often refractory psychiatric disorder. Magnetic resonance-guided focused ultrasound is a novel, minimally invasive neuromodulatory technique that has shown promise in treating this condition. We investigated the relationship between lesion location and long-term outcome in patients with obsessive-compulsive disorder treated with focused ultrasound to discern the optimal lesion location and elucidate the efficacious network underlying symptom alleviation. Postoperative images of 11 patients who underwent focused ultrasound capsulotomy were used to correlate lesion characteristics with symptom improvement at 1-year follow-up. Normative resting-state functional MRI and normative diffusion MRI-based tractography analyses were used to determine the networks associated with successful lesions. Patients with obsessive-compulsive disorder treated with inferior thalamic peduncle deep brain stimulation (n = 5) and lesions from the literature implicated in obsessive-compulsive disorder (n = 18) were used for external validation. Successful long-term relief of obsessive-compulsive disorder was associated with lesions that included a specific area in the dorsal anterior limb of the internal capsule. Normative resting-state functional MRI analysis showed that lesion engagement of areas 24 and 46 was significantly associated with clinical outcomes (R = 0.79, P = 0.004). The key role of areas 24 and 46 was confirmed by (i) normative diffusion MRI-based tractography analysis, showing that streamlines associated with better outcome projected to these areas; (ii) association of these areas with outcomes in patients receiving inferior thalamic peduncle deep brain stimulation (R = 0.83, P = 0.003); and (iii) the connectedness of these areas to obsessive-compulsive disorder-causing lesions, as identified using literature-based lesion network mapping. These results provide considerations for target improvement, outlining the specific area of the internal capsule critical for successful magnetic resonance-guided focused ultrasound outcome and demonstrating that discrete frontal areas are involved in symptom relief. This could help refine focused ultrasound treatment for obsessive-compulsive disorder and provide a network-based rationale for potential alternative targets.