基于皮层表面分析的脑结构MRI研究在抑郁症异质性中的研究进展  

Research progress in the application of surface-based morphometry for brain structural MRI study in major depressive disorder

在线阅读下载全文

作  者:杨凡[1,2] 徐莉 刘威[3] 杨建中 YANG Fan;XU Li;LIU Wei;YANG Jianzhong(Department of Psychiatry,Second Affiliated Hospital of Kunming Medical University,Kunming 650000,China;Department of Clinical Medicine,Baoshan College of Traditional Chinese Medicine,Baoshan 678000,China;First Department of Mood Disorder,Second Affiliated Hospital of Xinxiang Medical College,Xinxiang 453002,China;Department of Psychiatry,First Affiliated Hospital,Zhejiang University School of Medicine,Hangzhou 310000,China)

机构地区:[1]昆明医科大学第二附属医院精神科,昆明650000 [2]保山中医药高等专科学校临床医学院,保山678000 [3]新乡医学院第二附属医院心境一科,新乡453002 [4]浙江大学医学院附属第一医院精神卫生科,杭州310000

出  处:《磁共振成像》2025年第3期116-121,132,共7页Chinese Journal of Magnetic Resonance Imaging

摘  要:抑郁症(major depressive disorder,MDD)的临床症状、治疗反应及病理机制表现出显著异质性,传统神经影像技术难以解析其复杂脑结构特征。基于皮层表面的形态学分析(surface-based morphometry,SBM)通过量化皮层厚度(cortical thickness,CT)、表面积(surface area,SA)及局部脑回指数(local gyrification index,LGI)等指标,为揭示MDD的神经生物学异质性提供了全新视角,本文系统综述了SBM在MDD研究中的关键进展,旨在为MDD的精准分型提供关键影像学生物标志。Major depressive disorder(MDD) exhibits significant heterogeneity in its clinical symptoms,treatment responses,and pathological mechanisms,making it challenging for traditional neuroimaging techniques to untangle its complex brain structural characteristics.Surface-based morphometry(SBM),which quantifies indicators such as cortical thickness(CT),surface area(SA),and local gyrification index(LGI),offers a fresh perspective for elucidating the neurobiological heterogeneity of MDD.This article systematically reviews the critical advancements of SBM in MDD research,aiming to provide crucial imaging biomarkers for the precise classification of MDD.

关 键 词:抑郁症 磁共振成像 结构磁共振成像 基于表面的形态学分析 表面积 

分 类 号:R445.2[医药卫生—影像医学与核医学] R749.4[医药卫生—诊断学]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象