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Substantia Nigra Abnormalities in Early Parkinson’s Disease Patients using Convolutional Neural Networks in Neuromelanin MRI
Rahul Gaurav1,2,3, Romain Valabregue1,2, Nadya Pyatigorskaya1,2,3,4, Lydia Yahia-Cherif1,2, Emma Biondetti1,2,3, Graziella Mangone2,5, R. Matthew Hutchison6, Jean-Christophe Corvol2,5,7, Marie Vidailhet2,3,7, and Stephane Lehericy1,2,3,4
1CENIR, ICM Paris, Paris, France, 2Paris Brain Institute (ICM), Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMR 7225, Paris, France, 3ICM Team “Movement Investigations and Therapeutics” (MOV’IT), Paris, France, 4Department of Neuroradiology, Pitié-Salpêtrière Hospital, AP-HP, Paris, France, 5INSERM, Clinical Investigation Center for Neurosciences, Pitié-Salpêtrière Hospital, Paris, France, 6Biogen Inc., Cambridge, MA, United States, 7Department of Neurology, APHP, Pitié-Salpêtrière Hospital, Paris, France
Using our proposed automated segmentation, we found a highly significant difference in substantia nigra pars compacta volume and signal between Parkinson’s disease patients and healthy volunteers on the basis of neuromelanin-sensitive MRI.
Figure 1: Substantia Nigra Pars Compacta (SNc) regions of interest (ROI) using ConvNet and manual segmentations for a representative Parkinson's disease patient and a healthy volunteer.
Table 1: Demographic and clinical characteristics of early Parkinson's Disease patients and healthy volunteers.