Abstract #2951

Stratified Parkinsonism classification based on multi-modality MRI

Yijun Leng^1,2, Xueling Liu², Daoying Geng^1,2,3, Fengtao Liu⁴, Pu-Yeh Wu⁵, Yuxin Li^2,3, and Liqin Yang^2,3

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

Synopsis

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.

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