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Precision Medical Diagnosis for Parkinson's Disease - The Quantitative Analysis System for PET/MRI Images in Patients

NCT03909828 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 100

Last updated 2019-04-10

No results posted yet for this study

Summary

In nuclear medicine PET examinations, labeled radiopharmaceuticals are possible to enter the putamen and caudate nucleus regions of the striatum in the brain by intravenous injection. The severity of Parkinson's disease is assessed and diagnosed by quantitative analysis of the defect in the image of the radiopharmaceuticals. Clinical studies often use manual selection of regions of interest (ROIs) for quantitative analysis. However, this method causes human error and low reproducibility due to subjective factors, and also considerable time consuming. Therefore, in order to solve the above problems, this research project plans to build an automated quantitative analysis system for PET/MRI images. The quantitative analysis of the PET images is performed automatically by using the putamen and caudate ROI segmented by the MRI images. This automated quantitative analysis system is expected to improve the time-consuming, low reproducibility, and subjectivity problems of traditional manual ROI selection method, and provide a useful tool for the diagnosis of early PD. In the first year, this sub-project is expected to perform MRI T1 and 18F-FDOPA PET scanning of before and after acupuncture-treated PD patients provided by sub-project 3. In the second year, the correlation analysis will be made with the results of tremor test provided by sub-project 1 and that of the 99mTc-TRODAT SPECT image quantification provided by sub-project 4.

Conditions

  • Parkinson Disease
  • PET
  • MRI

Sponsors & Collaborators

  • Taipei Veterans General Hospital, Taiwan

    lead OTHER_GOV

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2019-04-30
Primary Completion
2021-12-31
Completion
2021-12-31

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Read the full study record

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View NCT03909828 on ClinicalTrials.gov