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

Overview

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.

Parkinson's disease (PD) is a neurodegenerative disease whose pathogenic mechanism is the degeneration of substantia nigra of the midbrain, causing the degeneration of dopaminergic neurons in the putamen and caudate nucleus of the striatum, and the dopamine content in the synapses decreases and gradually loses the ability to act. Most of the clinical symptoms are motor function defects. The most obvious symptoms are tremor, limb stiffness, motor dysfunction and gait abnormality, and cognitive and behavioral problems may occur. 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. In this study, patients will perform MRI T1 and 18F-FDOPA PET scanning of before and after acupuncture-treated PD patients in VGHTPE PET/MRI scanner. Every patient will be administered 185 MBq (5 mCi) of 18F-FDOPA by IV injection. The MRI image is used to extract the target and background ROIs (region of interests), and is coregistered to the PET image. The ROIs generated by MRI image will be applied to its corresponding PET image. Then, specific uptake ratio (SUR) will be calculated for each patient. The calculation of SUR is the difference between the average image pixel value of the target ROI (left and right striatum) and the average image pixel value of the background ROI (occipital lobe) divided by the average value of the background ROI. After calculated each patients' standard uptake ration, Asymmetry index (ASI) can be calculated based on the absolute difference of SUR value of both sides (left and right) of striatum, divided by average SUR value of both sides of striatum. 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.