Brain metabolic changes and clinical response to superolateral medial forebrain bundle deep brain stimulation for treatment-resistant depression

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作者
Christopher R. Conner
Joao Quevedo
Jair C. Soares
Albert J. Fenoy
机构
[1] The University of Texas Health Science Center at Houston (UT Health),Department of Neurosurgery, McGovern Medical School
[2] McGovern Medical School,Center of Excellence on Mood Disorders, Faillace Department of Psychiatry and Behavioral Sciences
[3] The University of Texas Health Science Center at Houston (UT Health),undefined
来源
Molecular Psychiatry | 2022年 / 27卷
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摘要
Deep brain stimulation (DBS) to the superolateral branch of the medial forebrain bundle is an efficacious therapy for treatment-resistant depression, providing rapid antidepressant effects. In this study, we use 18F-fluorodeoxyglucose-positron emission tomography (PET) to identify brain metabolic changes over 12 months post-DBS implantation in ten of our patients, compared to baseline. The primary outcome measure was a 50% reduction in Montgomery–Åsberg Depression Rating Scale (MADRS) score, which was interpreted as a response. Deterministic fiber tracking was used to individually map the target area; probabilistic tractography was used to identify modulated fiber tracts modeled using the cathodal contacts. Eight of the ten patients included in this study were responders. PET imaging revealed significant decreases in bilateral caudate, mediodorsal thalamus, and dorsal anterior cingulate cortex metabolism that was evident at 6 months and continued to 12 months post surgery. At 12 months post-surgery, significant left ventral prefrontal cortical metabolic decreases were also observed. Right caudate metabolic decrease at 12 months was significantly correlated with mean MADRS reduction. Probabilistic tractography modeling revealed that such metabolic changes lay along cortico-limbic nodes structurally connected to the DBS target site. Such observed metabolic changes following DBS correlated with clinical response provide insights into how future studies can elaborate such data to create biomarkers to predict response, the development of which likely will require multimodal imaging analysis.
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页码:4561 / 4567
页数:6
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