S-Space College of Medicine/School of Medicine (의과대학/대학원) Dept. of Medicine (의학과) Theses (Ph.D. / Sc.D._의학과)
Predicting Response for Pharmacotherapy Using Neuroanatomical Single-Subject Pattern Recognition in Obsessive-Compulsive Disorder
강박증 환자에서 대뇌 피질 두께를 이용한 약물 치료반응 예측모델의 구축
- 의과대학 의학과
- Issue Date
- 서울대학교 대학원
- obsessive-compulsive disorder; pharmacotherapy; treatment response; structural covariance network; support vector machine
- 학위논문 (박사)-- 서울대학교 대학원 : 의과대학 의학과 정신과학전공, 2016. 2. 권준수.
- Background: Primary pharmacotherapy regimen for obsessive-compulsive disorder (OCD) named Serotonin reuptake inhibitors (SRIs) does not attain sufficient symptom improvement in 40-60% of OCD. We aimed to decode the differential profile of OCD-related brain pathology per subject in the context of cortical surface area (CSA) or thickness (CT)-based individualized structural covariance (ISC) and to demonstrate the potential of which as a biomarker of treatment response to SRI-based pharmacotherapy in OCD using the support vector machine (SVM).
Methods: T1-weighted magnetic resonance imaging was obtained at 3T from 56 unmedicated OCD subjects and 75 healthy controls (HCs) at baseline. After 4 months of SRI-based pharmacotherapy, the OCD subjects were classified as responders (OCD-R, N=25
≥35% improvement) or nonresponders (OCD-NR, N=31
<35% improvement) according to the percentage change in the Yale-Brown Obsessive Compulsive Scale total score. Cortical ISCs sustaining between-group difference (p < .001) for every run of leave-one-out group-comparison were packaged as feature set for group classification using the SVM.
Results: An optimal feature set of the top 12 ISCs including a CT-ISC between the dorsolateral prefrontal cortex versus precuneus, a CSA-ISC between the anterior insula versus intraparietal sulcus, as well as perisylvian area-related ISCs predicted the initial prognosis of OCD as OCD-R or OCD-NR with an accuracy of 89.0% (sensitivity 88.4%, specificity 90.1%). Extended sets of ISCs distinguished the OCD subjects from the HCs with 90.7-95.6% accuracy (sensitivity 90.8-96.2%, specificity 91.1-95.0%).
Conclusion: We showed the potential of cortical morphology-based ISCs, which reflect dysfunctional cortical maturation process, as a possible biomarker that predicts the clinical treatment response to SRI-based pharmacotherapy in OCD.