Linking connectivity of deep brain stimulation of nucleus accumbens area with clinical depression improvements: a retrospective longitudinal case series.

Treatment-resistant depression is a severe form of major depressive disorder and deep brain stimulation is currently an investigational treatment. The stimulation's therapeutic effect may be explained through the functional and structural connectivities between the stimulated area and other brain regions, or to depression-associated networks. In this longitudinal, retrospective study, four female patients with treatment-resistant depression were implanted for stimulation in the nucleus accumbens area at our center. We analyzed the structural and functional connectivity of the stimulation area: the structural connectivity was investigated with probabilistic tractography; the functional connectivity was estimated by combining patient-specific stimulation volumes and a normative functional connectome. These structural and functional connectivity profiles were then related to four clinical outcome scores. At 1-year follow-up, the remission rate was 66%. We observed a consistent structural connectivity to Brodmann area 25 in the patient with the longest remission phase. The functional connectivity analysis resulted in patient-specific R-maps describing brain areas significantly correlated with symptom improvement in this patient, notably the prefrontal cortex. But the connectivity analysis was mixed across patients, calling for confirmation in a larger cohort and over longer time periods.

Programming of subthalamic nucleus deep brain stimulation with hyperdirect pathway and corticospinal tract-guided parameter suggestions.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for advanced Parkinson's disease. Stimulation of the hyperdirect pathway (HDP) may mediate the beneficial effects, whereas stimulation of the corticospinal tract (CST) mediates capsular side effects. The study's objective was to suggest stimulation parameters based on the activation of the HDP and CST. This retrospective study included 20 Parkinson's disease patients with bilateral STN DBS. Patient-specific whole-brain probabilistic tractography was performed to extract the HDP and CST. Stimulation parameters from monopolar reviews were used to estimate volumes of tissue activated and to determine the streamlines of the pathways inside these volumes. The activated streamlines were related to the clinical observations. Two models were computed, one for the HDP to estimate effect thresholds and one for the CST to estimate capsular side effect thresholds. In a leave-one-subject-out cross-validation, the models were used to suggest stimulation parameters. The models indicated an activation of 50% of the HDP at effect threshold, and 4% of the CST at capsular side effect threshold. The suggestions for best and worst levels were significantly better than random suggestions. Finally, we compared the suggested stimulation thresholds with those from the monopolar reviews. The median suggestion errors for the effect threshold and side effect threshold were 1 and 1.5 mA, respectively. Our stimulation models of the HDP and CST suggested STN DBS settings. Prospective clinical studies are warranted to optimize tract-guided DBS programming. Together with other modalities, these may allow for assisted STN DBS programming.

Probabilistic Mapping Reveals Optimal Stimulation Site in Essential Tremor.

OBJECTIVE: The objective of this study was to obtain individual clinical and neuroimaging data of patients undergoing deep brain stimulation (DBS) for essential tremor (ET) from 5 different European centers to identify predictors of outcome and to identify an optimal stimulation site. METHODS: We analyzed retrospectively baseline covariates, pre- and postoperative clinical tremor scores (for 12 months) as well as individual imaging data from 119 patients to obtain individual electrode positions and stimulation volumes. Individual imaging and clinical data were used to calculate a probabilistic stimulation map in normalized space using voxel-wise statistical analysis. Finally, we used this map to train a classifier to predict tremor improvement. RESULTS: Probabilistic mapping of stimulation effects yielded a statistically significant cluster that was associated with a tremor improvement >50%. This cluster of optimal stimulation extended from the posterior subthalamic area to the ventralis intermedius nucleus and coincided with a normative structural connectivity-based cerebellothalamic tract (CTT). The combined features "distance between the stimulation volume and the significant cluster" and "CTT activation" were used as a predictor of tremor improvement. This correctly classified a >50% tremor improvement with a sensitivity of 89% and a specificity of 57%. INTERPRETATION: Our multicenter ET probabilistic stimulation map identified an area of optimal stimulation along the course of the CTT. The results of this study are mainly descriptive until confirmed in independent datasets, ideally through prospective testing. This target will be made openly available and may be used to guide surgical planning and for computer-assisted programming of DBS in the future. ANN NEUROL 2022;91:602-612.