功能性MRI在精神疾病分型中的应用
Functional MRI applications for psychiatric disease subtyping: a review
摘要：
历史上，精神疾病仅使用症状信息进行分类。随着新技术的出现，使研究人员能够更直接地研究大脑机制，对定义的病理学和病因学重新定义背后的机械原理的兴趣大大增加。这对个性化医疗领域尤其有吸引力，该领域寻求数据驱动的方法来改善个体诊断，预后和治疗选择。在这里，我们打算系统地分析功能性MRI在精神疾病生物型的阐明和通过应用于症状或生物标志物数据的无监督学习获得的亚型的解释上的使用。我们检索了现有文献中功能性MRI在获得或解释精神疾病亚型方面的应用。应用PRISMA指南筛选检索到的研究，并应用主动学习框架ASReviews进行文章优先级排序。在符合纳入标准的20项研究中，5项使用功能性MRI数据来解释脑源性疾病簇，4项使用功能性MRI数据来解释来自生物标志物数据而不是fMRI本身的簇，11项直接将聚类应用于fMRI。重度抑郁症和精神分裂症是研究最多的两种疾病，其次是多动症、精神病、自闭症和早期暴力。未检索到跨诊断研究。虽然对个性化医疗和数据驱动的疾病亚型的兴趣正在上升，精神病学也不例外，但迄今为止，功能性MRI数据的无监督分析并不一致，在收集和集中数据，标准化管道和模型验证以及方法改进方面还有很多工作要做。功能性磁共振成像在跨诊断精神病学领域的应用仍有待探索。
英文摘要：
Psychiatric disorders have historically been classified using symptom information alone. With the advent of new technologies that allowed researchers to investigate brain mechanisms more directly, interest in the mechanistic rationale behind defined pathologies and aetiology redefinition has greatly increased. This is particularly appealing for the field of personalised medicine, which searches for data-driven approaches to improve individual diagnosis, prognosis and treatment selection. Here we intend to systematically analyse the usage of functional MRI on both the elucidation of psychiatric disease biotypes and the interpretation of subtypes obtained via unsupervised learning applied to symptom or biomarker data. We searched the existing literature for functional MRI applications to the obtention or interpretation of psychiatric disease subtypes. The PRISMA guidelines were applied to filter the retrieved studies, and the active learning framework ASReviews was applied for article prioritization. From the 20 studies that met the inclusion criteria, 5 used functional MRI data to interpret symptom-derived disease clusters, 4 used it for the interpretation of clusters derived from biomarker data other than fMRI itself, and 11 applied clustering to fMRI directly. Major depression disorder and schizophrenia were the two most studied pathologies, followed by ADHD, psychosis, autism disorder, and early violence. No trans-diagnostic studies were retrieved. While interest in personalised medicine and data-driven disease subtyping is on the rise and psychiatry is not the exception, unsupervised analyses of functional MRI data are inconsistent to date, and much remains to be done in terms of gathering and centralising data, standardising pipelines and model validation, and method refinement. The usage of fMRI in the field of trans-diagnostic psychiatry remains vastly unexplored.
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