Stratified Parkinsonism classification based on multi-modality MRI
Yijun Leng1,2, Xueling Liu2, Daoying Geng1,2,3, Fengtao Liu4, Pu-Yeh Wu5, Yuxin Li2,3, and Liqin Yang2,3
1Academy for Engineering & Technology, Fudan University, Shanghai, China, 2Department of Radiology, Huashan Hospital, Shanghai, China, 3Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai, China, 4Department of Neurology, Huashan Hospital, Shanghai, China, 5GE Healthcare, Beijing, China
For differential diagnosis between PD and atypical parkinsonisms, we designed a stratified automated method based on SVM and multi-modality MRI, including T1WI, QSM and DTI. 163 patients (96 PD, 27 MSA, 40 PSP) and 65 healthy controls were recruited. Features including volume, cortical thickness, magnetic susceptibility, FA and MD of 124 ROIs were calculated for SVM classification. The result showed that SVM classification based on susceptibility enabled accurate differentiation of patients with parkinsonian disorders and controls, and classification of PD, MSA and PSP was allowed by using T1 and DTI.
This abstract and the presentation materials are available to members only;
a login is required.