Structuro-functional surrogates of response to subcallosal cingulate deep brain stimulation for depression
© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissionsoup.com..
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.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:145 |
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| Enthalten in: |
Brain : a journal of neurology - 145(2022), 1 vom: 29. März, Seite 362-377 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Elias, Gavin J B [VerfasserIn] |
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| Links: |
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| Themen: |
Deep brain stimulation |
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| Anmerkungen: |
Date Completed 01.04.2022 Date Revised 27.06.2022 published: Print Citation Status MEDLINE |
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| doi: |
10.1093/brain/awab284 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM32869262X |
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| 245 | 1 | 0 | |a Structuro-functional surrogates of response to subcallosal cingulate deep brain stimulation for depression |
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| 520 | |a © The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissionsoup.com. | ||
| 520 | |a 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 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a deep brain stimulation | |
| 650 | 4 | |a depression | |
| 650 | 4 | |a magnetic resonance imaging | |
| 650 | 4 | |a positron emission tomography | |
| 650 | 4 | |a subcallosal cingulate | |
| 700 | 1 | |a Germann, Jürgen |e verfasserin |4 aut | |
| 700 | 1 | |a Boutet, Alexandre |e verfasserin |4 aut | |
| 700 | 1 | |a Pancholi, Aditya |e verfasserin |4 aut | |
| 700 | 1 | |a Beyn, Michelle E |e verfasserin |4 aut | |
| 700 | 1 | |a Bhatia, Kartik |e verfasserin |4 aut | |
| 700 | 1 | |a Neudorfer, Clemens |e verfasserin |4 aut | |
| 700 | 1 | |a Loh, Aaron |e verfasserin |4 aut | |
| 700 | 1 | |a Rizvi, Sakina J |e verfasserin |4 aut | |
| 700 | 1 | |a Bhat, Venkat |e verfasserin |4 aut | |
| 700 | 1 | |a Giacobbe, Peter |e verfasserin |4 aut | |
| 700 | 1 | |a Woodside, D Blake |e verfasserin |4 aut | |
| 700 | 1 | |a Kennedy, Sidney H |e verfasserin |4 aut | |
| 700 | 1 | |a Lozano, Andres M |e verfasserin |4 aut | |
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