{"doi":"10.1093/brain/awab284","title":"Structuro-functional surrogates of response to subcallosal cingulate deep brain stimulation for depression","abstract":"<jats:title>Abstract</jats:title><jats:p>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.</jats:p><jats:p>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).</jats:p><jats:p>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.</jats:p>","journal":"Brain","year":2022,"id":631938,"datarank":0.9516373339759482,"base_score":3.8501476017100584,"endowment":3.8501476017100584,"self_citation_contribution":0.5775221402565088,"citation_network_contribution":0.37411519371943935,"self_endowment_contribution":0.5775221402565088,"citer_contribution":0.37411519371943935,"corpus_percentile":null,"corpus_rank":null,"citation_count":46,"citer_count":26,"citers_with_citation_signal":18,"citers_with_endowment":18,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":550195,"name":"Jürgen Germann","orcid":"0000-0003-0995-8226","position":1,"is_corresponding":false},{"id":232899,"name":"Alexandre Boutet","orcid":"0000-0001-6942-5195","position":2,"is_corresponding":false},{"id":673409,"name":"Aditya Pancholi","orcid":null,"position":3,"is_corresponding":false},{"id":672920,"name":"Michelle E. Beyn","orcid":"0000-0002-4111-8692","position":4,"is_corresponding":false},{"id":1637830,"name":"Kartik Bhatia","orcid":null,"position":5,"is_corresponding":false},{"id":550194,"name":"Clemens Neudorfer","orcid":"0000-0002-3153-1045","position":6,"is_corresponding":false},{"id":672917,"name":"Aaron Loh","orcid":"0000-0001-5297-6775","position":7,"is_corresponding":false},{"id":1637834,"name":"Sakina J Rizvi","orcid":null,"position":8,"is_corresponding":false},{"id":672921,"name":"Venkat Bhat","orcid":"0000-0002-8768-1173","position":9,"is_corresponding":false},{"id":438140,"name":"Peter Giacobbe","orcid":"0000-0001-6642-6221","position":10,"is_corresponding":false},{"id":1637835,"name":"D Blake Woodside","orcid":null,"position":11,"is_corresponding":false},{"id":1637836,"name":"Sidney H Kennedy","orcid":null,"position":12,"is_corresponding":false},{"id":1637837,"name":"Andres M Lozano","orcid":null,"position":13,"is_corresponding":false},{"id":232898,"name":"Gavin J.B. Elias","orcid":"0000-0002-7495-550X","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Structuro-functional surrogates of response to subcallosal cingulate deep brain stimulation for depression","abstract":"<jats:title>Abstract</jats:title><jats:p>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.</jats:p><jats:p>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).</jats:p><jats:p>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. 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