Application of combining 18F-FDG PET imaging and radiomics in the diagnosis of Parkinson′s disease and atypical parkinsonian syndromes
10.3760/cma.j.cn321828-20210420-00130
- VernacularTitle:18F－FDG PET图像结合影像组学在帕金森病与非典型性帕金森综合征鉴别诊断中的应用价值
- Author:
Xiaoming SUN
1
;
Min WANG
;
Ling LI
;
Jiaying LU
;
Jingjie GE
;
Ping WU
;
Huiwei ZHANG
;
Chuantao ZUO
;
Jiehui JIANG
Author Information
1. 上海大学先进通信与数据科学研究院，上海 200444
- Keywords:
Parkinson disease;
Parkinsonian disorders;
Positron-emission tomography;
Fluorodeoxyglucose F18;
Radiomics
- From:
Chinese Journal of Nuclear Medicine and Molecular Imaging
2022;42(10):583-587
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the potential application of combining 18F-FDG PET imaging and radiomics in the diagnosis of Parkinson′s disease (PD) and atypical parkinsonian syndromes (APS). Methods:A total of 154 subjects of two cohorts (training set and validation set) were enrolled from Huashan Hospital, Fudan University from March 2015 to August 2020 in this cross-sectional study, including 40 normal controls (NC; 23 males and 17 females, age: (60.2±10.5) years), 40 PD patients (20 males and 20 females, age: (64.7±6.3) years), 40 progressive supranuclear palsy (PSP) patients (20 males and 20 females, age: (64.1±5.9) years), and 34 multiple system atrophy (MSA) patients (19 males and 15 females, age: (65.0±9.2) years). 18F-FDG PET images and clinical scale were selected, and one-way analysis of variance was used to compare differences of clinical scale among groups. Radiomic features extraction and feature selection were carried out. Two and three classification models were constructed based on logistic regression, and the ROC curves of clinical model, radiomics model and combined model were calculated. Independent classification tests were conducted 100 times with 5-fold cross validation in two cohorts. Results:There were significant differences in the scores of unified PD Rating Scale (UPDRS) and Hoehn-Yahr rating scale (H&Y) among different groups in cohort 1 and cohort 2 respectively ( F values: 4.83-17.95, all P<0.05). A total of 2 444 imaging features were extracted from each subject, and after features selection, 15 features for classification were obtained. In the two classification experiment, the AUCs of the three models in binary classification of PD/MSA/PSP/NC group were 0.56-0.68, 0.74-0.93 and 0.72-0.93, respectively. The classification effects of the radiomics model were significantly better than those of the clinical model ( z values: 1.71-2.85, all P<0.05). In the three classification experiment, the sensitivity of the radiomics model reached 80%, 80% and 77% for PD, MSA and PSP, respectively. Conclusion:18F-FDG imaging combined with radiomics has potential in the diagnosis of PD and APS.
