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Abstract #2648

Diagnosing Parkinson’s disease by Combining Neuromelanin and Iron Image Features Using Automatic SN Subregions Detection Approach

Zhijia Jin1, Mojtaba Jokar2, Ying Wang2,3, Yan Li1, Zenghui Cheng1, Yu Liu1, Rongbiao Tang1, Xiaofeng Shi1, Youmin Zhang1, Jihua Min1, Fangtao Liu1, Naying He1, E. Mark Haacke1,2,3,4, and Fuhua Yan1
1Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, 2Magnetic Resonance Innovations, Inc., Bingham Farms, MI, United States, 3Radiology, Wayne State University, Detroit, MI, United States, 4Biomedical Engineering, Wayne State University, Detroit, MI, United States


A total of 100 Parkinson’s disease (PD) patients and 100 age- and sex-matched healthy controls (HCs) were scanned using a single 3D gradient echo magnetization transfer sequence. We developed an automatic substantia nigra (SN) subregions segmentation approach to get neuromelanin (NM) and iron measurements in the SN. These measures along with their overlap region volume and the nigrosome-1 (N1) sign showed reliable results indicative of promising diagnostic biomarkers to differentiate PD patients from HCs.

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