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. Haacke^1,3,4,5, 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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