Abstract

Background: Deep brain stimulation (DBS) is a new treatment option for patients with therapy-resistant obsessive–compulsive disorder (OCD). Approximately 60% of patients benefit from DBS, which might be improved if a biomarker could identify patients who are likely to respond. Therefore, we evaluated the use of preoperative structural magnetic resonance imaging (MRI) in predicting treatment outcome for OCD patients on the group- and individual-level. Methods: In this retrospective study, we analyzed preoperative MRI data of a large cohort of patients who received DBS for OCD (n = 57). We used voxel-based morphometry to investigate whether grey matter (GM) or white matter (WM) volume surrounding the DBS electrode (nucleus accumbens (NAc), anterior thalamic radiation), and whole-brain GM/WM volume were associated with OCD severity and response status at 12-month follow-up. In addition, we performed machine learning analyses to predict treatment outcome at an individual-level and evaluated its performance using cross-validation. Results: Larger preoperative left NAc volume was associated with lower OCD severity at 12-month follow-up (p FWE < 0.05). None of the individual-level regression/classification analyses exceeded chance-level performance. Conclusions: These results provide evidence that patients with larger NAc volumes show a better response to DBS, indicating that DBS success is partly determined by individual differences in brain anatomy. However, the results also indicate that structural MRI data alone does not provide sufficient information to guide clinical decision making at an individual level yet.

Original languageEnglish
Article number102640
JournalNeuroImage: Clinical
Volume30
DOIs
Publication statusPublished - 1 Jan 2021

Keywords

  • Anterior limb of the internal capsule
  • Deep brain stimulation
  • Machine learning
  • Nucleus accumbens
  • Obsessive–compulsive disorder
  • Treatment outcome prediction

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