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.
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.
J Affect Disord. 2021 Jul 1;290:261-271. doi: 10.1016/j.jad.2021.04.081. Epub 2021 May 16.
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.
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.
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.
The sample size was moderate, and features for machine learning were based on group differences.
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.
左侧背外侧前额叶皮层(DLPFC)和扣带回下前部(sgACC)之间的功能连接可能是经颅磁刺激(rTMS)治疗反应的生物标志物。第一个目的是确定这一发现是真实的,还是预处理方法人为诱导的。此外,还确定了替代生物标志物,并检查了其在个性化医学中的临床应用。
对 70 名接受经颅导航左侧 DLPFC rTMS 治疗的药物难治性抑郁症患者(16 名男性)进行了静息态 fMRI 数据采集。使用和不使用全局信号回归预处理进行基于种子的分析,以确定短期和长期治疗反应的生物标志物。应用受试者工作特征曲线和监督机器学习分析来评估这些生物标志物对分类 rTMS 反应的临床应用价值。
无论使用哪种预处理方法,DLPFC-sgACC 连接都与治疗结果无关。相反,在长期无反应者中,sgACC 与三个簇(峰位置:额极、上顶叶、枕叶)和 DLPFC-中央脑岛皮质之间的连接较差。所确定的连接可以作为可接受的至优秀的标志物。使用监督机器学习对这些特征进行组合,在交叉验证和测试数据集的准确率分别达到 95.35%(CI=82.94-100.00)和 88.89%(CI=63.96-100.00)。
样本量中等,机器学习的特征基于组间差异。
长期无反应者在涉及中央执行网络的区域表现出更大的连接中断。我们的发现可能有助于开发针对药物难治性抑郁症的个性化医学。