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Combining quantitative susceptibility mapping to radiomics in diagnosing Parkinson’s disease and assessing cognitive impairment

医学 致密部 帕金森病 蒙特利尔认知评估 神经组阅片室 逻辑回归 黑质 壳核 无线电技术 内科学 认知障碍 病理 疾病 放射科 神经学 精神科
作者
Jin Juan Kang,Yue Chen,Guo Dong Xu,Shan Lei Bao,Jie Wang,Min Ge,Lihua Shen,Zhong Zheng Jia
出处
期刊:European Radiology [Springer Science+Business Media]
卷期号:32 (10): 6992-7003 被引量:27
标识
DOI:10.1007/s00330-022-08790-8
摘要

To explore whether magnetic susceptibility value (MSV) and radiomics features of the nigrostriatal system could be used as imaging markers for diagnosing Parkinson's disease (PD) and its related cognitive impairment (CI).A total of 104 PD patients and 45 age-sex-matched healthy controls (HCs) underwent quantitative susceptibility mapping (QSM). The former completed Hoehn-Yahr Stage and Montreal Cognitive Assessment (MoCA). The patients were divided into several subgroups according to disease stages, courses, and MoCA scores. The ROI was subdivided into the substantia nigra (SN), head of caudate nucleus (HCN), and putamen. The MSVs and radiomics features were obtained from QSM. The multivariable logistic regression (MLR) and support vector machine (SVM) models were constructed to diagnose PD. The correlations between MSVs, radiomics features, and MoCA scores were evaluated.The MSVs in bilateral SN pars compacta (SNc) of PD patients were higher than those of the HCs (p < 0.001). There were differences in some radiomics features between the two groups (p < 0.05). The MSVs of the right SNc and the radiomics features of the right SN had the highest area under the curve (AUC), respectively. The comprehensive MLR model (0.90) and SVM model (0.95) revealed better classification performance than MSVs (p < 0.05) in diagnosing PD. The MSVs from the HCN were negatively correlated with MoCA scores in PD subgroups. There were correlations between radiomics features and MoCA scores in PD patients.Radiomics features and MSVs of the nigrostriatal system from QSM could have crucial role in diagnosing PD and assessing CI.• The MLR and the SVM models have excellent diagnostic performance in the diagnosis of PD. • A PD diagnostic nomogram, created based on MSV and the radiomics scores of SVM model, is very convenient for clinical use. • The radiomics features of the nigrostriatal system based on QSM help to evaluate the cognitive impairment in PD patients.
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