Parkinson's disease (PD) is a common progressive neurodegenerative disorder characterized by resting tremor, bradykinesia, restricted mobility, and postural instability. Early diagnosis of PD would be paramount for further treatment and prognosis. The most common neurodegenerative parkinsonian syndrome is known as Parkinson's disease (PD) or idiopathic Parkinson syndrome, if it occurs sporadically (not familial) and its lead clinical symptom is a movement disorder after brainstem-predominant α-synuclein deposition. To distinguish them from Parkinson's disease, other sporadic entities have been named atypical parkinsonian syndromes or atypical parkinsonism. The present review article describes current standards for the diagnosis and treatment of the most important disease entities in this latter group: dementia with Lewy bodies (DLB), multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and corticobasal degeneration (CBD).~PD is diagnosed mainly by neurologists, based on clinical symptoms. However, there are no objective criteria available for their diagnosis. Although magnetic resonance imaging (MRI) is often employed in conjunction with clinical judgment, the images are mostly used to eliminate other diseases, rather than to confirm the diagnosis. Other imaging methods, such as Positron Emission Tomography or Computed Tomography, may help in the diagnosis of PD but have harmful effects on the human body. MRI image of patients with Parkinson's disease is usually normal. Previous studies have also indicated that brain-related areas, such as the atrophy of basal ganglia, are not observed until a period of disease progression. However, the shrinkage of brain tissue cannot be used as a criterion for the diagnosis of Parkinson's disease, because many other diseases are accompanied by atrophy of brain tissue as well. Furthermore, because human brain cells cannot regenerate, It is too late to diagnose or treat when a large number of nerve cells are apoptotic. Since we expect the function of the diseased cells to change first, therefore, if you can detect changes in the patient's brain microenvironment, it is possible to achieve early detection of Parkinson's disease. Magnetic resonance imaging can detect functional images and display functional changes, thus providing an opportunity to detect abnormalities and diagnose diseases early. One of the key technologies in the measurement of functional images is diffusion magnetic resonance imaging.~Diffusion MRI has been widely utilized to investigate the patterns of neural connectivity. Mean diffusivity (MD) and the directionality (fractional anisotropy (FA)) have been studied in epilepsy, multiple sclerosis, and noticeably in Parkinson's Disease. Owing to their paramount pathogenetic role in Parkinson's disease, the basal ganglia in general and the substantia nigra pars compacta, in particular, have been the subject of intense MRI investigation.~The plan uses standard anatomic labeling (AAL) to perform whole-brain diffusion MRI to obtain diffusion data for the whole brain parcellation. We will use statistical methods to identify the areas affected by each PD's subtype, we will also identify areas that are likely to be related to the severity of the disease, and then combine these areas for linear regression analysis. We anticipate that diffusion magnetic resonance imaging can be used as a differential diagnosis, as well as to define areas of high correlation with clinical severity, and to be used for accurate disease prediction and future development, and to provide physicians and patients with clinically important information.~The program uses diffusion magnetic resonance imaging to assess clinical status and prognosis for Parkinson's disease. Our research goal is~Establish objective and clear imaging diagnostic criteria of diffusion MRI for idiopathic and atypical Parkinson's disease.~Establish objective and clear clinical severity and the prognosis prediction mode of diffusion MRI for idiopathic and atypical Parkinson's disease.
The hypothesis is that the differential extent of microstructural damages in the affected brain regions can be specific to the disease of interest and could reflect the clinical severity. Therefore, we propose that the whole brain parcellation of diffusion MRI can be used to improve the diagnosis and prediction of clinical outcomes in Parkinson's Disease.~A regression model between clinical severity and two-year clinical outcomes and diffusion properties from multiple parcellated regions will be developed.~Blind validation will be performed.