Predicting Outcome in a Cohort of Isolated and Combined Dystonia within Probabilistic Brain Mapping

BACKGROUND: Probabilistic brain mapping is a promising tool to estimate the expected benefit of pallidal deep brain stimulation (GPi‐DBS) in patients with isolated dystonia (IsoD). OBJECTIVES: To investigate the role of probabilistic mapping in combined dystonia (ComD). METHODS: We rendered the pallidal atlas and the volume of tissue activated (VTA) for a cohort of patients with IsoD (n = 20) and ComD (n = 10) that underwent GPi‐DBS. The VTA was correlated with clinical improvement. Afterwards, each VTA was applied on the previously published probabilistic model (Reich et al., 2019). The correlation between predicted and observed clinical benefit was studied in a linear regression model. RESULTS: A good correlation between observed and predicted outcome was found for both patients with IsoD (n = 14) and ComD (n = 7) (r(2) = 0.32; P < 0.05). In ComD, 42% of the variance in DBS response is explained by VTA‐based outcome map. CONCLUSION: A probabilistic model would be helpful in clinical practice to circumvent unpredictable and less impressive motor results often found in ComD.