Personalized prediction of transcranial magnetic stimulation clinical response in patients with treatment-refractory depression using neuroimaging biomarkers and machine learning.

Autor: Hopman HJ; The Chinese University of Hong Kong, Unit L, 19/F, Kings Wing Plaza 1, 3 On Kwan Street, Shatin, Shek Mun, New Territories, Hong Kong, SAR, China. Electronic address: hjhopman@cuhk.edu.hk., Chan SMS; The Chinese University of Hong Kong, G30, G/F, Multicentre, Tai Po Hospital. 9 Chuen On Road, Tai Po, New Territories, Hong Kong, SAR, China. Electronic address: schan@cuhk.edu.hk., Chu WCW; Prince of Wales Hospital, Rm 27023, G/F, Shatin, New Territories, Hong Kong, SAR, China. Electronic address: winnie@med.cuhk.edu.hk., Lu H; The Chinese University of Hong Kong, Unit L, 19/F, Kings Wing Plaza 1, 3 On Kwan Street, Shatin, Shek Mun, New Territories, Hong Kong, SAR, China. Electronic address: hannalu@cuhk.edu.hk., Tse CY; The Chinese University of Hong Kong, Sino Building, Rm 352, Chung Chi road, Shatin, New Territories, Hong Kong, SAR, China; Department of Social and Behavioural Sciences, City University of Hong Kong, Hong Kong, Hong Kong SAR China. Electronic address: chunyu.tse@cityu.edu.hk., Chau SWH; Prince of Wales Hospital the Chinese University of Hong Kong Jockey Club School of Public Health, 3/F, rm 327, 30 Ngan Shing Street, Shatin, New Territories, Hong Kong, SAR, China. Electronic address: stevenwaihochau@cuhk.edu.hk., Lam LCW; The Chinese University of Hong Kong, Unit L, 19/F, Kings Wing Plaza 1, 3 On Kwan Street, Shatin, Shek Mun, New Territories, Hong Kong, SAR, China. Electronic address: cwlam@cuhk.edu.hk., Mak ADP; The Chinese University of Hong Kong, Unit L, 19/F, Kings Wing Plaza 1, 3 On Kwan Street, Shatin, Shek Mun, New Territories, Hong Kong, SAR, China. Electronic address: arthurdpmak@cuhk.edu.hk., Neggers SFW; Brain Center Rudolf Magnus, University Medical Center Utrecht, Heidelberglaan 100. 3584 CX, Utrecht, the Netherlands. Electronic address: b.neggers@umcutrecht.nl.
Jazyk: angličtina
Zdroj: Journal of affective disorders [J Affect Disord] 2021 Jul 01; Vol. 290, pp. 261-271. Date of Electronic Publication: 2021 May 16.
DOI: 10.1016/j.jad.2021.04.081
Abstrakt: Background: Functional connectivity between the left dorsolateral prefrontal cortex (DLPFC) and subgenual cingulate (sgACC) may serve as a biomarker for transcranial magnetic stimulation (rTMS) treatment response. The first aim was to establish whether this finding is veridical or artifactually induced by the pre-processing method. Furthermore, alternative biomarkers were identified and the clinical utility for personalized medicine was examined.
Methods: Resting-state fMRI data were collected in medication-refractory depressed patients (n = 70, 16 males) before undergoing neuronavigated left DLPFC rTMS. Seed-based analyses were performed with and without global signal regression pre-processing to identify biomarkers of short-term and long-term treatment response. Receiver Operating Characteristic curve and supervised machine learning analyses were applied to assess the clinical utility of these biomarkers for the classification of categorical rTMS response.
Results: Regardless of the pre-processing method, DLPFC-sgACC connectivity was not associated with treatment outcome. Instead, poorer connectivity between the sgACC and three clusters (peak locations: frontal pole, superior parietal lobule, occipital cortex) and DLPFC-central opercular cortex were observed in long-term nonresponders. The identified connections could serve as acceptable to excellent markers. Combining the features using supervised machine learning reached accuracy rates of 95.35% (CI=82.94-100.00) and 88.89% (CI=63.96-100.00) in the cross-validation and test dataset, respectively.
Limitations: The sample size was moderate, and features for machine learning were based on group differences.
Conclusions: Long-term nonresponders showed greater disrupted connectivity in regions involving the central executive network. Our findings may aid the development of personalized medicine for medication-refractory depression.
(Copyright © 2021 Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
Externí odkaz: