中国临床医学影像杂志2026，Vol.37Issue(8)：538-541,4.DOI:10.12117/jccmi.2026.08.002
多模态头颅MRI参数联合随机森林算法构建老年衰弱的早期预测模型
Construction of an early prediction model for frailty in older adults using on multimodal cranial MRI parameters combined with a random forest algorithm
摘要
Abstract
Objective:To construct an early prediction model for frailty in older adults using multimodal cranial MRI parameters combined with a random forest algorithm.Methods:A total of 500 elderly hospitalized patients who received treatment from January to December 2023 were selected as the research subjects.According to the frailty assessment scale,there were 140 patients in the frailty group,210 patients in the pre-frailty stage,and 150 patients in the non-frailty group.The differences between high white matter signals and deep white matter signals in patients were studied,and the differ-ences in lifestyle,multi-drug use,daily living ability,anxiety,and other factors among the three groups of patients were compared.Results:There were statistically significant differences(P＜0.05)in age,comorbidities,living conditions,marital sta-tus,education level,age,mini nutritional assessment short form,mini mental state examination,global deterioration scale 1,activities of daily living,types of chronic disease comorbidities,medication types,white matter hyperintensities,deep white matter hyperintensities,hippocampal volume,left hippocampal volume,and right hippocampal volume among patients in the frailty group,pre-frailty group,and non-frailty group.Multivariate analysis showed that the above factors were the contribut-ing factors to the patient's frailty.The model formed by the study was used in the construction of a random forest model.The validation set(30%data)evaluation has good predictive ability.Conclusion:The early prediction model for frailty in older adults,constructed using multimodal cranial MRI parameters combined with a random forest algorithm,effectively pre-dicts frailty and provides an important reference for early clinical intervention and frailty identification.关键词
衰弱/老年人/磁共振成像Key words
Frailty/Aged/Magnetic Resonance Imaging分类
医药卫生引用本文复制引用
吕品,岳玮,闫宇涛,张海宇..多模态头颅MRI参数联合随机森林算法构建老年衰弱的早期预测模型[J].中国临床医学影像杂志,2026,37(8):538-541,4.基金项目
河南省自然科学基金面上项目(242300420124) （242300420124）
2025年度河南省医学科技攻关计划项目(LHGJ20250639). （LHGJ20250639）
