Subcallosal cingulate (SCC) deep brain stimulation (DBS) is a promising therapy for treatment-resistant depression (TRD), but response rates in open-label studies were not replicated in a large multicenter trial. Identifying biomarkers of response could improve patient selection and outcomes. We examined SCC metabolic activity as both a predictor and marker of SCC DBS treatment response. Brain glucose metabolism (CMRGlu) was measured with [18F] FDG-PET at baseline and 6 months post DBS in 20 TRD patients in a double-blind randomized controlled trial where two stimulation types (long pulse width (LPW) n = 9 and short pulse width (SPW) n = 11) were used. Responders (n = 10) were defined by a ≥48% reduction in Hamilton Depression Rating Scale scores after 6 months. The response rates were similar with five responders in each stimulation group: LPW (55.6%) and SPW (44.5%). First, differences in SCC CMRGlu in responders and non-responders were compared at baseline. Then machine learning analysis was performed with a leave-one-out cross-validation using a Gaussian naive Bayes classifier to test whether baseline CMRGlu in SCC could categorize responders. Finally, we compared 6-month change in metabolic activity with change in depression severity. All analyses were controlled for age. Baseline SCC CMRGlu was significantly higher in responders than non-responders. The machine learning analysis predicted response with 80% accuracy. Furthermore, reduction in SCC CMRGlu 6 months post DBS correlated with symptom improvement (r(17) = 0.509; p = 0.031). This is the first evidence of an image-based treatment selection biomarker that predicts SCC DBS response. Future studies could utilize SCC metabolic activity for prospective patient selection.
ASJC Scopus subject areas
- Psychiatry and Mental health