Automatic segmentation and quantification of nigrosome-1 neuromelanin and iron in MRI: a candidate biomarker for Parkinson’s disease

Abstract

AbstractThe dopaminergic neuronal loss in the substantia nigra pars compacta (SNc) has been related to a reduction of neuromelanin (NM) and accumulation of iron in the nigrosome-1 (N1) in Parkinson’s disease (PD). This suggests that N1 degeneration could be a promising early biomarker of PD. To date, only qualitative visual scales have been used to assess its degeneration in iron-sensitive images. Here we present the first fully-automatic method for the quantification of NM and iron content in the N1. Our method uses a multi-image atlas populated with healthy N1 structures that implements a customised label fusion strategy to segment the N1. NM-MRI and susceptibility-weighted images (SWI) of 71 PD patients and 30 healthy controls (HCs) were used in the study. Our quantification showed that N1’s NM content was reduced and the iron content increased in PD patients compared with HCs. ROC analyses showed the high diagnostic potential of N1, and revealed that the N1 alone was more sensitive than the entire SNc to detect abnormal iron accumulations in PD patients. Multi-parametric binary logistic regression showed that computer-assisted diagnosis methods could benefit from the segmentation of the N1 to boost their performance. A significant correlation was also found between most N1 image parameters and both disease duration and the motor status scored with the Unified Parkinson’s disease rating scale part III (UDPRS-III), suggesting a NM reduction along with an iron accumulation in N1 as the disease progresses. In addition, voxel-wise analyses revealed that this association was stronger for the N1 than for the entire SNc, highlighting the benefits of an accurate segmentation of the N1 to monitor disease course.