Clinical Investigation
Application of combining 18F-FDG PET imaging and radiomics in the diagnosis of Parkinson′s disease and atypical parkinsonian syndromes
Sun Xiaoming, Wang Min, Li Ling, Lu Jiaying, Ge Jingjie, Wu Ping, Zhang Huiwei, Zuo Chuantao, Jiang Jiehui
Published 2022-10-25
Cite as Chin J Nucl Med Mol Imaging, 2022, 42(10): 583-587. DOI: 10.3760/cma.j.cn321828-20210420-00130
Abstract
ObjectiveTo 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).
MethodsA 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.
ResultsThere 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.
Conclusion18F-FDG imaging combined with radiomics has potential in the diagnosis of PD and APS.
Key words:
Parkinson disease; Parkinsonian disorders; Positron-emission tomography; Fluorodeoxyglucose F18; Radiomics
Contributor Information
Sun Xiaoming
Shanghai Institute of Advanced Communication and Data Science, Shanghai University, Shanghai 200444, China
Wang Min
Shanghai Institute of Advanced Communication and Data Science, Shanghai University, Shanghai 200444, China
Li Ling
PET Center, Huashan Hospital, Fudan University, Shanghai 200235, China
Lu Jiaying
PET Center, Huashan Hospital, Fudan University, Shanghai 200235, China
Ge Jingjie
PET Center, Huashan Hospital, Fudan University, Shanghai 200235, China
Wu Ping
PET Center, Huashan Hospital, Fudan University, Shanghai 200235, China
Zhang Huiwei
PET Center, Huashan Hospital, Fudan University, Shanghai 200235, China
Zuo Chuantao
PET Center, Huashan Hospital, Fudan University, Shanghai 200235, China
Jiang Jiehui
Shanghai Institute of Advanced Communication and Data Science, Shanghai University, Shanghai 200444, China
