| Project/Area Number |
17K09066
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Medical Physics and Radiological Technology
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| Research Institution | Kagawa University |
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Principal Investigator |
Maeda Yukito 香川大学, 医学部附属病院, 技術職員 (10763336)
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| Project Period (FY) |
2017-04-01 – 2022-03-31
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| Project Status |
Completed (Fiscal Year 2021)
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| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2019: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2018: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2017: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | フラクタル解析 / 神経膠腫 / PET / メチオニン / 画像再構成アルゴリズム / グリオーマ / 11C-メチオニンPET / 濃度フラクタル / フラクタル次元 / 画像再構成 / 脳腫瘍 / 悪性度 / ピクセルカウンティング法 / 放射線 |
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| Outline of Final Research Achievements |
The purpose of this study was to clarify the effects of four image reconstruction algorithms OSEM, OSEM + PSF, OSEM + TOF and OSEM + PSF + TOF on fractal analysis in brain tumor PET examination. In all algorithms the higher the malignancy of brain tumors, the smaller the fractal dimension in brain methionine PET. This result suggests the usefulness of classification using fractal analysis in brain methionine PET. Next, we also evaluated the usefulness of fractal analysis in comparison with conventionally quantitative values such as SUVs for the differentiation of IDH1 mutation glioma. Fractal analysis may be able to differentiate gliomas for IDH1 mutations that were not possible with conventional quantitative parameters.
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| Academic Significance and Societal Importance of the Research Achievements |
画像解析の一つであるフラクタル解析と従来からPET検査で使用されている評価値を組み合わせることにより，脳腫瘍の治療方針決定や予後予測などをより高い精度で行う可能性が示唆された．本研究により，フラクタル解析は脳腫瘍患者およびその家族に対し，有用な情報を提供できる指標になりうる可能性があると考えている．
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