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老年抑郁症的结构性神经影像学研究方法

Structural neuroimaging research methods in geriatric depression.

作者信息

Hoptman Matthew J, Gunning-Dixon Faith M, Murphy Christopher F, Lim Kelvin O, Alexopoulos George S

机构信息

Division of Clinical Research, Nathan Kline Institute, Orangeburg, New York 10962, USA.

出版信息

Am J Geriatr Psychiatry. 2006 Oct;14(10):812-22. doi: 10.1097/01.JGP.0000238588.34205.bd.

DOI:10.1097/01.JGP.0000238588.34205.bd
PMID:17001021
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC1945049/
Abstract

Geriatric depression consists of complex and heterogeneous behaviors unlikely to be caused by a single brain lesion. However, there is evidence that abnormalities in specific brain structures and their interconnections confer vulnerability to the development of late-life depression. Structural magnetic resonance imaging methods can be used to identify and quantify brain abnormalities predisposing to geriatric depression and in prediction of treatment response. This article reviews several techniques, including morphometric approaches, study of white matter hyperintensities, diffusion tensor imaging, magnetization transfer imaging, t2 relaxography, and spectroscopy, that have been used to examine these brain abnormalities with a focus on the type of information obtained by each method as well as each method's limitations. The authors argue that the available methods provide complementary information and that, when combined judiciously, can increase the knowledge gained from neuroimaging findings and conceptually advance the field of geriatric depression.

摘要

老年抑郁症表现为复杂多样的行为,不太可能由单一脑损伤引起。然而,有证据表明特定脑结构及其相互连接的异常会使人易患晚年抑郁症。结构磁共振成像方法可用于识别和量化易导致老年抑郁症的脑异常,并预测治疗反应。本文综述了几种技术,包括形态测量方法、白质高信号研究、扩散张量成像、磁化传递成像、T2弛豫成像和光谱学,这些技术已被用于检查这些脑异常,重点关注每种方法获得的信息类型及其局限性。作者认为,现有方法提供了互补信息,若明智地结合使用,可增加从神经影像学发现中获得的知识,并在概念上推动老年抑郁症领域的发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f878/1945049/1c6848e34437/nihms23482f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f878/1945049/1c6848e34437/nihms23482f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f878/1945049/1c6848e34437/nihms23482f1.jpg

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