基于人工智能的运动评估对帕金森病及多系统萎缩P型的诊断价值  

Diagnostic value of AI-based motion assessment in differentiation of Parkinson's disease and multiple system atrophy-Parkinsonian type

作　　者：王茜尧 任娜 陈纪霖 李华[2] 李敏[2] 张舒凤 于瑾[2] 钱海蓉[1] Wang Qianyao;Ren Na;Chen Jilin;Li Hua;Li Min;Zhang Shufeng;Yu Jin;Qian Hairong(Navy Clinical College,Fifth School of Clinical Medicine,Anhui Medical University,Hefei 230032,Anhui Province,China)

机构地区：[1]安徽医科大学第五临床医学院海军临床学院,合肥230032 [2]解放军总医院第一医学中心神经内科医学部 [3]解放军73021部队

出　　处：《中华老年心脑血管病杂志》2025年第4期482-487,共6页Chinese Journal of Geriatric Heart,Brain and Vessel Diseases

基　　金：首都卫生发展科研专项(首发2020-2-5115)。

摘　　要：目的应用人工智能辅助下的运动障碍评估法对帕金森病(Parkinson's disease,PD)及多系统萎缩P型(multiple system atrophy-Parkinson,MSA-P)进行运动量化评估以期精准鉴别诊断。方法连续纳入2024年1~9月在解放军总医院第一和第三医学中心神经内科就诊的年龄≥60岁患者105例,根据诊断情况分为PD组48例,MSA-P组31例及对照组26例。收集一般资料,采用运动功能辅助评估系统进行运动评定,评估该方法在PD及MSA-P中的鉴别诊断价值。结果3组面部表情指标、左右侧对指频率、左右侧手部运动频率、右侧手部运动的幅度变化率、左右侧连续翻掌频率、左右侧脚趾拍地频率、左右侧脚趾拍地冻结负荷、左右侧腿部灵活度频率、右侧腿部灵活度幅度变化率、左右侧腿部灵活度的冻结负荷、直立伸展角速度、转身耗时、前进步频、返回步频、前进平均步幅、返回平均步幅、前进平均步速、返回平均步速、前进平均步宽、返回平均步宽、左右手姿势性震颤频率、左右手姿势性震颤最大幅度、左右手动作性震颤频率、左右手动作性震颤最大幅度、左右手静止性震颤频率比较,差异有统计学意义(P<0.05,P<0.01)。MSA-P组左右侧瞬目频率、面部震颤最大幅度、面部震颤频率、直立伸展角速度、前进步频、返回步频明显低于PD组,张嘴时长占比及转身耗时明显高于PD组,差异有统计学意义(P<0.05,P<0.01)。联合9项运动功能指标或5项面部表情指标鉴别诊断PD与MSA-P的ROC曲线下面积分别为0.943(95%CI:0.895~0.991,P=0.000),0.925(95%CI:0.870~0.981,P=0.000),大于各单项指标。结论联合面部表情、姿势、步态等人工智能辅助的运动评估有助于PD及MSA-P的鉴别诊断。Objective To use AI-assisted motor dysfunction assessment for quantitative evaluation of motor function in Parkinson's disease(PD)and multiple system atrophy-Parkinsonian type(MSA-P)in order to achieve accurate differential diagnosis.Methods A total of 105 participants aged≥60 years were consecutively enrolled from the First and Third Medical Centers of Chinese PLA General Hospital between January and September 2024.Based on diagnostic criteria,they were divided into a PD group(48 cases),a MSA-P group(31 cases),and a control group(26 cases).The general information was collected,and the motor function was evaluated with Movement Dysfunction Assessment Software in order to assess the diagnostic value of the AI-assisted assessment in differentiating between PD and MSA-P.Results Significantly differences were observed among the three groups in terms of facial expression indicators,bilateral finger tapping frequency,bilateral hand movement frequency,right hand movement amplitude change rate,bilateral palm flipping frequency,bilateral toe tapping frequency,freezing load of bilateral toe tapping,bilateral leg flexibility frequency,right leg flexibility amplitude change rate,freezing load of bilateral leg flexibility,upright extension angular velocity,turnaround time,forward step frequency,backward step frequency,forward average stride length,backward average stride length,forward average walking speed,backward average walking speed,forward average step width,backward average step width,bilateral postural tremor frequency,bilateral postural tremor maximum amplitude,bilateral action tremor frequency,bilateral action tremor maximum amplitude,and comparison of bilateral resting tremor frequency(P<0.05,P<0.01).The MSA-P group exhibited significantly lower blink frequency,maximum amplitude and frequency of facial tremors,upright extension angular velocity,and step frequency,while higher ratio of mouth opening duration and longer turnaround time when compared with the PD group(P<0.05,P<0.01).The AUC value of the combined nin

关 键 词：帕金森病 多系统萎缩 人工智能 诊断 鉴别 

分 类 号：R74[医药卫生—神经病学与精神病学]