Department of Psychiatry, Krembil Research Centre, University Health Network, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada.
Department of Psychiatry, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, Calgary, AB, Canada; Mathison Centre for Mental Health Research and Education, Calgary, AB, Canada.
J Affect Disord. 2018 Jun;233:21-35. doi: 10.1016/j.jad.2017.10.049. Epub 2017 Oct 31.
Current practice for selecting pharmacological and non-pharmacological antidepressant treatments has yielded low response and remission rates in Major Depressive Disorder (MDD). Neuroimaging biomarkers of brain structure and function may be useful in guiding treatment selection by predicting response vs. non-response outcomes.
In this review, we summarize data from studies examining predictors of treatment response using structural and functional neuroimaging modalities, as they pertain to pharmacotherapy, psychotherapy, and stimulation treatment strategies. A literature search was conducted in OVID Medline, EMBASE, and PsycINFO databases with coverage from January 1990 to January 2017.
Several imaging biomarkers of therapeutic response in MDD emerged: frontolimbic regions, including the prefrontal cortex, anterior cingulate cortex, hippocampus, amygdala, and insula were regions of interest. Since these sub-regions are implicated in the etiology of MDD, their association with response outcomes may be the result of treatments having a normalizing effect on structural or activation abnormalities.
The direction of findings is inconsistent in studies examining these biomarkers, and variation across 'biotypes' within MDD may account for this. Limitations in sample size and differences in methodology likely also contribute.
The identification of accurate, reliable neuroimaging biomarkers of treatment response holds promise toward improving treatment outcomes and reducing burden of illness for patients with MDD. However, before these biomarkers can be translated into clinical practice, they will need to be replicated and validated in large, independent samples, and integrated with data from other biological systems.
目前，在选择抗抑郁药物和非药物治疗方面，尽管取得了一些进展，但在重度抑郁症（MDD）患者中，反应率和缓解率仍然较低。脑结构和功能的神经影像学生物标志物可能有助于通过预测反应与非反应结局来指导治疗选择。
在这篇综述中，我们总结了使用结构和功能神经影像学模式来研究预测治疗反应的研究数据，这些模式与药物治疗、心理治疗和刺激治疗策略有关。我们在 OVID Medline、EMBASE 和 PsycINFO 数据库中进行了文献检索，检索时间为 1990 年 1 月至 2017 年 1 月。
在 MDD 中出现了几种治疗反应的影像学生物标志物：额-边缘区域，包括前额叶皮层、前扣带皮层、海马体、杏仁核和岛叶，是研究的重点区域。由于这些亚区域与 MDD 的病因有关，它们与反应结局的关系可能是由于治疗对结构或激活异常具有正常化作用。
在研究这些生物标志物的研究中，发现的方向不一致，并且 MDD 内的“生物型”差异也可能导致这种情况。样本量的限制和方法学的差异也可能起到一定作用。
准确、可靠的治疗反应神经影像学生物标志物的识别有望改善治疗结果，并减轻 MDD 患者的疾病负担。然而，在这些生物标志物能够转化为临床实践之前，需要在大型独立样本中进行复制和验证，并与来自其他生物系统的数据相结合。
