Keywords: Parkinson's Disease, Parkinson's Disease, atypical Parkinson syndrome, substantia nigra, susceptibility weighted imaging，radiomics
Motivation: The ‘swallow tail’ sign (STS) of substantia nigra (SN) on SWI can distinguish PD from healthy subjects. However, it’s difficult to differentiate PD from APS by visually inspect the STS.
Goal(s): Discriminating PD from APS using the radiomic features of SN extracted from multi-echo SWI susceptibility map.
Approach: 63 PD, 38 APS and 89 healthy controls were enrolled. Five classification models using radiomic features of SN were used and compared.
Results: The size, shape, and texture characteristics of SN are the most important features, and
the light gradient-boosting machine model (LGBM) had the best performance in identifying PD, APS, and healthy subjects.
Impact: PD and APS have similar clinical syndrome but were treated differently. Our finding suggested LGBM based on radiomic features of SN can differentiate PD from APS with high accuracy. It would help the treatment selection for PD and APS patients.
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