Diagnosis of Parkinson$S Disease Using Diffusion Magnetic Resonance Imaging( I )

  • Wang, Jiun-Jie (PI)
  • Chen, Wey-Yil (CoPI)
  • Cheng, Jur-Shan (CoPI)
  • Lin, Gloria (CoPI)
  • Lu, Chin-Song (CoPI)
  • Wai, Yau-Yau (CoPI)
  • Weng, Yi-Hsin (CoPI)
  • Yang, Fan Pei (CoPI)
  • Yen, Tzue-Chen (CoPI)

Project: National Science and Technology CouncilNational Science and Technology Council Academic Grants

Project Details


Currently there existed no specific diagnostic test of Parkinson’s Disease. Accurate diagnosis is of great interest because of the reduction in health cost and disease co-morbidity, improvement in effective treatment course and avoidance of un-necessary intervention. Our preliminary result showed superior performance from diffusion kurtosis imaging, a new development in MRI since 2007, on the diagnosis of Parkinson’s Disease when compared to conventional diffusion MRI. The study proposes to validate the diagnostic value of diffusion kurtosis in major basal ganglia regions using a cross-sectional study and to assess the prognostic value through 3-year longitudinal follow-up. Furthermore, the iron content as well as global white matter involvement in both PD and PD plus syndrome patients will be assessed. The difference in MRI information between PD and PD plus syndrome patients will then be addressed in a comprehensive manner. One hundred and twelve patients with Parkinson’s Disease will be recruited in the first year and followed up for 3 years. Another 112 healthy controls will be included. This is to validate the diagnosis and assess the prognosis. Another 30 patients with Parkinson’s Disease, 15 patients with progressive supranuclear palsy and 15 patients with multiple system atrophy will be recruited in the 2nd year for differential diagnosis. The imaging protocol will include both diffusion tensor and diffusion kurtosis imaging. Susceptibility weighted imaging will be included for iron content estimation. The targeted anatomy will include regional changes in basal ganglia, midbrain as well as thalamus, and global white matter changes using tract based spatial statistics. The statistical analysis will use receiver operative characteristics to assess the diagnostic performance, Spearman’s ranked correlation for correlation with disease severity and net reclassification improvement for differential diagnosis. The prognostic value will be determined by the decline rate and the quality of life. The end points of the project are to differentiate patients of PD from PD plus syndrome, and to predict the clinical outcomes using diffusion MRI. Patent application will be filed in the first year. The analysis of medical device software and software life cycle processes and the evaluation of risk management to medical devices will be filed at the end of the third year.

Project IDs

Project ID:PC10104-0006
External Project ID:NSC101-2325-B182-008
Effective start/end date01/03/1203/03/13


  • Parkinson's disease
  • diffusion kurtosis imaging
  • magnetic resonance imaging
  • Parkinson Plus Syndrome


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