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根据基线MRI体积数据预测轻度认知障碍患者的认知衰退率

Predicting Mental Decline Rates in Mild Cognitive Impairment From Baseline MRI Volumetric Data.

作者信息

Nguyen Xuan V, Candemir Sema, Erdal Barbaros Selnur, White Richard D, Prevedello Luciano M

机构信息

Department of Radiology, Ohio State University College of Medicine, Columbus, OH.

出版信息

Alzheimer Dis Assoc Disord. 2021;35(1):1-7. doi: 10.1097/WAD.0000000000000406.

Abstract

PURPOSE

In mild cognitive impairment (MCI), identifying individuals at high risk for progressive cognitive deterioration can be useful for prognostication and intervention. This study quantitatively characterizes cognitive decline rates in MCI and tests whether volumetric data from baseline magnetic resonance imaging (MRI) can predict accelerated cognitive decline.

METHODS

The authors retrospectively examined Alzheimer Disease Neuroimaging Initiative data to obtain serial Mini-Mental Status Exam (MMSE) scores, diagnoses, and the following baseline MRI volumes: total intracranial volume, whole-brain and ventricular volumes, and volumes of the hippocampus, entorhinal cortex, fusiform gyrus, and medial temporal lobe. Subjects with <24 months or <4 measurements of MMSE data were excluded. Predictive modeling of fast cognitive decline (defined as >0.6/year) from baseline volumetric data was performed on subjects with MCI using a single hidden layer neural network.

RESULTS

Among 698 baseline MCI subjects, the median annual decline in the MMSE score was 1.3 for converters to dementia versus 0.11 for stable MCI (P<0.001). A 0.6/year threshold captured dementia conversion with 82% accuracy (sensitivity 79%, specificity 85%, area under the receiver operating characteristic curve 0.88). Regional volumes on baseline MRI predicted fast cognitive decline with a test accuracy of 71%.

DISCUSSION

An MMSE score decrease of >0.6/year is associated with MCI-to-dementia conversion and can be predicted from baseline MRI.

摘要

目的

在轻度认知障碍(MCI)中,识别有进行性认知衰退高风险的个体对于预后评估和干预可能有用。本研究定量描述了MCI中的认知衰退率,并测试了来自基线磁共振成像(MRI)的容积数据是否能预测加速的认知衰退。

方法

作者回顾性研究了阿尔茨海默病神经影像学倡议数据,以获取连续的简易精神状态检查表(MMSE)评分、诊断结果以及以下基线MRI容积:总颅内容积、全脑和脑室容积,以及海马体、内嗅皮质、梭状回和内侧颞叶的容积。排除MMSE数据测量时间<24个月或测量次数<4次的受试者。使用单隐藏层神经网络对MCI受试者的基线容积数据进行快速认知衰退(定义为>0.6/年)的预测建模。

结果

在698名基线MCI受试者中,转化为痴呆症的受试者MMSE评分的年中位数下降为1.3,而稳定MCI受试者为0.11(P<0.001)。以0.6/年为阈值,捕捉痴呆症转化的准确率为82%(敏感性79%,特异性85%,受试者工作特征曲线下面积0.88)。基线MRI上的区域容积预测快速认知衰退的测试准确率为71%。

讨论

MMSE评分下降>0.6/年与MCI向痴呆症的转化相关,并且可以从基线MRI预测。

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