中国临床药理学杂志

MRI特征预测老年中风后认知障碍的临床研究

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王衍颜 ¹ , 逄宗欣 ¹ , 陈文健 ² , 陈晶 ¹ , 王刚 ³

中国临床药理学杂志 | 读者园地 2025,41(19): 2827-2832

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中国临床药理学杂志 |读者园地 2025 , 41 (19) : 2827 -2832

MRI特征预测老年中风后认知障碍的临床研究

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王衍颜¹, 逄宗欣¹, 陈文健², 陈晶¹, 王刚³

作者信息

^1.康复大学青岛中心医院全科医学科，山东青岛 266000

^2.康复大学青岛中心医院口腔科，山东青岛 266000

^3.鲁东大学生命科学学院，山东烟台 264025

通讯作者:

陈晶，副主任医师 MP: 18561857667 E-mail: 19078975120@163.com

作者简介:

王衍颜（1984-），女，主治医师，主要从事全科医学研究及临床工作

Study on predicting post-stroke cognitive impairment using MRI image texture features

Yan-yan WANG¹, Zong-xin PANG¹, Wen-jian CHEN², Jing CHEN¹, Gang WANG³

Affiliations

^1.Department of General Medicine, Qingdao Central Hospital of Rehabilitation University, Qingdao 266000, Shandong Province, China

^2.Department of Stomatology, Qingdao Central Hospital of Rehabilitation University, Qingdao 266000, Shandong Province, China

^3.School of Life Sciences, Ludong University, Yantai 264025, Shandong Province, China

出版时间: 2025-10-17 doi: 10.13699/j.cnki.1001-6821.2025.19.020

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摘要

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目的

探讨磁共振（MRI）图像纹理特征预测老年中风后认知障碍（PSCI）的价值，并分析其与PSCI药物治疗疗效的关联性，为临床药物干预时机选择及方案优化提供依据。

方法

回顾性分析2020年1月～2024年1月收治的中风患者资料，按数据来源分为训练集（n=160）与验证集（n=56）。收集所有患者基线至认知评估期间的PSCI规范药物治疗数据（包括胆碱酯酶抑制剂、美金刚及联合用药方案）。T1加权成像（T1w）图像经预处理后，在海马体和内嗅皮层测量纹理特征，分组分析高海马体峰度患者组（≥2.5）和低海马体峰度患者组，结合药物治疗信息构建PSCI预测及疗效预判模型并验证。

结果

本研究共纳入327名患者，其中男性211例，女性116例。预测模型在训练集及验证集的准确率分别为90%和77%；协方差分析显示，PSCI患者与非PSCI患者在海马体峰度、内嗅皮层峰度及内嗅皮层逆差异矩（IDM）中在统计学上差异均有统计学意见（均P<0.05）。多奈哌齐治疗有效率显示，高海马体峰度患者组显著高于低峰度患者组（76.31% vs. 41.22%，P<0.01）；内嗅皮层IDM≥0.4的患者，联合用药（多奈哌齐+美金刚）有效率优于单药治疗（82.13% vs. 58.28%，P<0.05）。优化模型纳入药物治疗因素后，验证集AUC提升至0.82。

结论

常规临床MRI纹理特征是PSCI的可靠早期预测因子，且与PSCI药物治疗疗效存在显著关联，可结合药物治疗信息构建更精准的预测及疗效评估模型，为PSCI个体化药物干预提供影像学支撑。

关键词

药物治疗 / MRI图像 / 纹理特征 / 中风后认知障碍 / T1w图像

Abstract

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Objective

To explore the value of texture features in magnetic resonance imaging (MRI) for predicting post-stroke cognitive impairment (PSCI) in elderly patients, and to analyze its correlation with the efficacy of PSCI drug therapy, providing a basis for selecting the timing and optimizing clinical drug intervention plans.

Method

A retrospective analysis was conducted on the data of stroke patients admitted from January 2020 to January 2024. The data was divided into a training set (n=160) and a validation set (n=56) according to the data source. Collect PSCI standardized medication treatment data (including cholinesterase inhibitors, memantine, and combination therapy regimens) for all patients from baseline to cognitive assessment. After preprocessing of T1 weighted imaging (T1w) images, texture features were measured in the hippocampus and entorhinal cortex. Patients with high hippocampal kurtosis (≥ 2.5) and low hippocampal kurtosis were grouped and analyzed. A PSCI prediction and efficacy prediction model was constructed and validated based on drug treatment information. As a result, a total of 327 patients were included in this study, including 211 males and 116 females. The accuracy of the prediction model in the training set and validation set is 90% and 77%, respectively; Covariance analysis showed that there were differences (P<0.05) in hippocampal kurtosis, entorhinal cortex kurtosis, and entorhinal cortex deficit anomaly (IDM) between PSCI patients and non PSCI patients. The effective rate of donepezil treatment showed that the group with high hippocampal kurtosis was significantly higher than the group with low kurtosis (76.31% vs. 41.22%, P<0.01); Patients with IDM ≥ 0.4 in the entorhinal cortex showed better efficacy with combination therapy (donepezil+memantine) compared to monotherapy (82.13% vs. 58.28%, P<0.05). After optimizing the model and incorporating drug treatment factors, the validation set AUC increased to 0.82.

Conclusion

Conventional clinical MRI texture features are reliable early predictors of PSCI and are significantly associated with the efficacy of PSCI drug therapy. They can be combined with drug therapy information to construct more accurate prediction and efficacy evaluation models, providing imaging support for individualized drug intervention in PSCI.

Key words

MRI image / texture features / post-stroke cognitive impairment / T1-weighted imaging / pharmacotherapy

引用本文

王衍颜, 逄宗欣, 陈文健, 陈晶, 王刚. MRI特征预测老年中风后认知障碍的临床研究. 中国临床药理学杂志, 2025 , 41 (19) : 2827 -2832 . DOI: 10.13699/j.cnki.1001-6821.2025.19.020

Yan-yan WANG, Zong-xin PANG, Wen-jian CHEN, Jing CHEN, Gang WANG. Study on predicting post-stroke cognitive impairment using MRI image texture features[J]. Chinese Journal of Clinical Pharmacology, 2025 , 41 (19) : 2827 -2832 . DOI: 10.13699/j.cnki.1001-6821.2025.19.020

基金

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国家自然科学基金面上基金资助项目(62171209)

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2025年第41卷第19期

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文章信息

doi: 10.13699/j.cnki.1001-6821.2025.19.020

接收时间：2025-07-15
首发时间：2026-08-05
出版时间：2025-10-17

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出版历史

收稿日期：2025-07-15

基金

国家自然科学基金面上基金资助项目(62171209)

作者信息

^1.康复大学青岛中心医院全科医学科，山东青岛 266000

^2.康复大学青岛中心医院口腔科，山东青岛 266000

^3.鲁东大学生命科学学院，山东烟台 264025

通讯作者:

陈晶，副主任医师 MP: 18561857667 E-mail: 19078975120@163.com

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https://castjournals.cast.org.cn/joweb/zglcylxzz/CN/10.13699/j.cnki.1001-6821.2025.19.020

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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