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基线神经影像学生物标志物预测抑郁症患者电休克治疗的总体临床反应:一项系统评价

Neuroimaging Biomarkers at Baseline Predict Electroconvulsive Therapy Overall Clinical Response in Depression: A Systematic Review.

作者信息

Levy Anna, Taib Simon, Arbus Christophe, Péran Patrice, Sauvaget Anne, Schmitt Laurent, Yrondi Antoine

机构信息

ToNIC Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS.

Service de Psychiatrie et Psychologie Médicale, CHU Toulouse, ToNIC Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, France.

出版信息

J ECT. 2019 Jun;35(2):77-83. doi: 10.1097/YCT.0000000000000570.

Abstract

OBJECTIVE

Major depressive disorder is a frequent and disabling disease and can be treated with antidepressant drugs. When faced with severe or resistant major depressive disorder, however, psychiatrists may resort to electroconvulsive therapy (ECT). Although very effective, the response falls short of 100%. A recent meta-analysis established clinical and biological predictive factors of the response to ECT. We decided to explore neuroimaging biomarkers that could be predictors of the ECT response.

METHODS

We performed a systematic literature review up to January 1, 2018, using a Boolean combination of MeSH terms. We included 19 studies matching our inclusion criteria.

RESULTS

Lower hippocampal, increased amygdala, and subgenual cingulate gyrus volumes were predictive for a better ECT response. Functional magnetic resonance imaging also found that the connectivity between the dorsolateral prefrontal cortex and posterior default-mode network is predictive of increased efficacy. Conversely, deep white matter hyperintensities in basal ganglia and Virchow-Robin spaces, medial temporal atrophy, ratio of left superior frontal to left rostral middle frontal cortical thickness, cingulate isthmus thickness asymmetry, and a wide range of gray and white matter anomalies were predictive for a poorer response.

CONCLUSIONS

Our review addresses the positive or negative predictive value of neuroimaging biomarkers for the ECT response, indispensable in a personalized medicine dynamic. These data could reduce the risk of nonresponders or resistance with earlier effective management. It might also help researchers elucidate the complex pathophysiology of depressive disorders and the functioning of ECT.

摘要

目的

重度抑郁症是一种常见且使人致残的疾病,可用抗抑郁药物治疗。然而,面对重度或难治性重度抑郁症时,精神科医生可能会采用电休克疗法(ECT)。尽管该疗法非常有效,但有效率仍未达到100%。最近的一项荟萃分析确定了ECT反应的临床和生物学预测因素。我们决定探索可作为ECT反应预测指标的神经影像学生物标志物。

方法

我们使用医学主题词(MeSH)的布尔组合,对截至2018年1月1日的文献进行了系统综述。我们纳入了19项符合纳入标准的研究。

结果

海马体积减小、杏仁核体积增大以及膝下扣带回体积减小可预测ECT反应更好。功能磁共振成像还发现,背外侧前额叶皮质与后默认模式网络之间的连接性可预测疗效提高。相反,基底节和血管周围间隙的深部白质高信号、内侧颞叶萎缩、左上额叶与左喙状中额叶皮质厚度之比、扣带回峡部厚度不对称以及广泛的灰质和白质异常可预测反应较差。

结论

我们的综述探讨了神经影像学生物标志物对ECT反应的阳性或阴性预测价值,这在个性化医疗动态中不可或缺。这些数据可以通过早期有效的管理降低无反应者或耐药的风险。它还可能有助于研究人员阐明抑郁症的复杂病理生理学以及ECT的作用机制。

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