Brain imaging quantitative analysis applied to study of serotonin transporter in nuclear medicine

• Main Authors: Bang-Hung Yang, 楊邦宏
• Other Authors: Jyh-Cheng Chen
• Format: Others
• Language: en_US
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/30567108144264701890

博士 === 國立陽明大學 === 生物醫學影像暨放射科學系暨研究所 === 99 === The purpose of the dissertation is to utilize different process in nuclear medicine images to explore cerebral central nerve system. In recent years, it is becoming more and more important research in serotonin transporter (SERT) of cerebral central nerve system such as sleep, appetite, body temperature, aggression, body weight, mood, and so on. Even studies of psychiatric disease and pharmacological treatment effect regulate concentration of serotonin transporter. In current years, domestic and foreign research institutes begin to develop I-123 ADAM radiopharmaceutical to provide good images of cerebral SERT using single photon emission computed tomography (SPECT). However, they lack accuracy of quantitative analysis for SERT images of cerebral neuroreceptor. Therefore, the dissertation study hopes to establish standard procedure of quantitative imaging analysis, to study concentrations of SERT using I-123 ADAM SPECT, and to improve simultaneous dual-isotope imaging technology in order to provide two cerebral information of physiology at the same time and decrease patients’ repeat times. The research methods focus on pharmacokinetic model, in the first instance we compared binding potential (BP) derived from traditional semiquantification approach of manual drawing of region of interest (ROI) with BP derived from noninvasive quantification of reference tissue model (RTM). We explored BP correlation between ROI and RTM method to validate noninvasive quantification suited for I-123 ADAM imaging analysis. Then, we used statistical parametric mapping (SPM) to analyze cerebral SERT images voxel by voxel and we also performed test-retest analysis of I-123 ADAM images. Thus it can provide voxel based statistical comparison and shows the cortex areas with statistical significance. Finally, we proposed wavelet transformation and independent component analysis with multiple energy windows (W_eICA) to correct imaging artifact resulting from simultaneous dual-isotope imaging cross-talk effect. The simultaneous dual-isotope imaging not only reduces acquisition time but also obtain two cerebral functions at the same physiological state. According to our results, I-123 ADAM SERT images not only suit RTM quantification analysis without arterial blood sampling, but also obtain significant BP correlation between RTM and specific uptake ratio (SUR) method. The average of SUR (reference area was cerebellum) of 123I-ADAM binding to SERT in midbrain was 1.78 ± 0.27, pons was 1.21 ± 0.53, and striatum was 0.79 ± 0.13. ICC was presented by cronbach’s α to evaluate reliability of test-retest in I-123 ADAM SPECT imaging. The overall cronbach’s α of ICC was 0.92 in target which showed good reliabilty in each reference region. Besides, there was also no significant statistical finding in cerebral area using SPM2 analysis. This finding might help us to understand reliability of I-123 ADAM SPECT imaging and further develop new strategy for the treatment of psychiatric disorders. In addition, we utilized physical phantom to validate that W_eICA method is more accurate than conventional asymmetric energy window (AEW) approach. The recovery rate (RC) of Tc-99m was 1.03 and I-123 was 1.07 from W_eICA method. On the other hand, the RC of Tc-99m was 0.84 and I-123 was 1.05 from AEW approach. This dissertation not only provides researcher, who is versed in cerebral neuroreceptor images, to thoroughly understand SERT in clinic study, but also helps them to have practical reference to our image processing techniques in nuclear medicine.