Research progress of multimodal MRI and complex network analysis based on graph theory in Parkinson's disease

Abstract

Parkinson's disease (PD) is a common progressive neurodegenerative disease and is mainly caused by dopamine neuron degeneration in the substantia nigra pars compacta of the human brain. It has become "the third killer" after tumor and cardio-cerebrovascular disease in middle-aged and elderly people at present. In recent years, the development of multimodal MRI [including structural MRI (sMRI), functional MRI (fMRI), diffusion tension imaging (DTI), etc.] and the introduction of complex network analysis based on graph theory provide a new and effective method for researchers to explore the changes of brain structure and function in PD patients. The article mainly reviews the research progress of structural and functional brain networks in PD patients that are established based on multimodal MRI and complex network analysis based on graph theory, so as to provide new imaging markers for the early diagnosis of PD.

DOI: 10.3969/j.issn.1672-6731.2017.01.004