An Integrative Nomogram for Identifying Early-Stage Parkinson's Disease Using Non-motor Symptoms and White Matter-Based Radiomics Biomarkers From Whole-Brain MRI

ABSTRACT: Purpose: To develop and validate an integrative nomogram based on white matter (WM) radiomics biomarkers and nonmotor symptoms for the identification of early-stage Parkinson's disease (PD). Methods: The brain magnetic resonance imaging (MRI) and clinical characteristics of 336 subjects, including 168 patients with PD, were collected from the Parkinson's Progress Markers Initiative (PPMI) database. All subjects were randomly divided into training and test sets. According to the baseline MRI scans of patients in the training set, the WM was segmented to extract the radiomic features of each patient and develop radiomics biomarkers, which were then combined with nonmotor symptoms to build an integrative nomogram using machine learning. Finally, the diagnostic accuracy and reliability of the

SUBMITTER: Shu Z 

PROVIDER: S-EPMC7773758 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature