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Abstract #3509

Parkinson’s Disease Subtype Identification Using Radiomics Based on Iron Deposition in Substantia Nigra

Zhijia Jin1, Ruiqi Yu2, Chenglong Wang2, Naying He1, Yan Li1, Zenghui Cheng1, Yida Wang2, Mark E. Haacke1,3,4,5, Guang Yang2, and Fuhua Yan1
1Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, 2Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China, 3Magnetic Resonance Innovations, Inc., Bingham Farms, MI, United States, 4Department of Radiology, Wayne State University, Detroit, MI, United States, 5Department of Biomedical Engineering, Wayne State University, Detroit, MI, United States

A total of 104 Parkinson’s disease (PD) patients and 269 age- and sex-matched healthy controls (HCs) were scanned using 3D multi-echo gradient echo MTC sequence. In this work, a data-driven clustering approach based on iron deposition in the substantia nigra (SN) measured by quantitative susceptibility mapping (QSM) was performed to classify the PD patients into different subtypes. The clinical assessments were compared between subtype groups. Two subtypes were found by using this clustering approach. Furthermore, there are significant differences (p-values < 0.05) on MDS-UPDRS scores between these two subtype groups.

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