| Project/Area Number |
15591273
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Radiation science
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| Research Institution | Osaka University |
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Principal Investigator |
MURASE Kenya Osaka University, Graduate School of Medicine, Professor, 大学院・医学系研究科, 教授 (50157773)
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| Co-Investigator(Kenkyū-buntansha) |
HATAZAWA Jun Osaka University, Graduate School of Medicine, professor, 大学院・医学系研究科, 教授 (70198745)
OKU Naohiko Osaka University, Hospital, Lecturer, 医学部附属病院, 講師 (40346193)
INOUE Osamu Osaka University, Graduate School of Medicine, Professor, 大学院・医学系研究科, 教授 (50159969)
TAMURA Shinichi Osaka University, Graduate School of Medicine, Professor, 大学院・医学系研究科, 教授 (30029540)
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| Project Period (FY) |
2003 – 2004
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| Project Status |
Completed (Fiscal Year 2004)
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| Budget Amount *help |
¥3,200,000 (Direct Cost: ¥3,200,000)
Fiscal Year 2004: ¥1,300,000 (Direct Cost: ¥1,300,000)
Fiscal Year 2003: ¥1,900,000 (Direct Cost: ¥1,900,000)
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| Keywords | SPECT / PET / partial volume effect / anatomical information / Bayesian image reconstruction method / MRI / fuzzy clustering / Tc-99m HMPAO / ^<99m>Tc HMPAO |
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| Research Abstract |
To accurately and quantitatively measure the distribution of radioisotope in the body using single photon emission computed tomography (SPECT) or positron emission tomography (PET), it is important to accurately correct for the partial volume effect (PVE). However, the correction of PVE is more difficult than that of attenuation and/or scattering in the body. On the other hand, it is possible to extract the anatomical information of the body from magnetic resonance imaging (MRI) using the segmentation method such as fuzzy clustering. Then, it is expected that if the anatomical information extracted from MRI can be introduced as a prior knowledge in the Bayesian image reconstruction method, it becomes possible to correct for PVE in SPECT or PET. Therefore, the purpose of this study was to develop a method for correcting for PVE in SPECT or PET by introducing the anatomical information extracted from MRI in the Bayesian image reconstruction method.
In 2003, we developed a software that introduces the anatomical information extracted from MRI as a prior knowledge in the Bayesian image reconstruction method. In 2004, we continued to develop the above software, and simultaneously started to evaluate the usefulness of this method using phantom experiments and clinical data. We obtained the preliminary results that encouraged the possibility of correcting for PVE using the above method.
In conclusion, this method appears to be useful for correcting for PVE in SPECT or PET. However, further studies are necessary to establish the usefulness of this method, and these studies are currently in progress.
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