2022 Fiscal Year Final Research Report
Development of intratumor state prediction technology combining MR measurement and simulation and its application to treatment strategy
| Project/Area Number |
18K12032
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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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| Review Section |
Basic Section 90110:Biomedical engineering-related
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| Research Institution | Kobe University |
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Principal Investigator |
Kokuryo Daisuke 神戸大学, システム情報学研究科, 准教授 (20508543)
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| Project Period (FY) |
2018-04-01 – 2023-03-31
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| Keywords | MRI / 領域抽出 / 多目的最適化 / 定量値推定 / 状態予測 |
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| Outline of Final Research Achievements |
We investigated feature quantities and mathematical models to capture the temporal changes in the intratumoral state based on measured multi-parametric Magnetic Resonance (MR) images and tissue staining information. In addition, we developed a technology to predict the shape of the tumor and changes in the state of the tumor by combining it with computer simulation technology. We developed a method for extracting tumor regions from multi-parametric MR images, investigated feature values that capture temporal changes in tumor conditions, and developed temporal change prediction technology that combines MR images and computer simulation technology. Based on the obtained results, we were able to present a method for predicting feature values and state changes for capturing the state of tumors.
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| Free Research Field |
医用システム
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| Academic Significance and Societal Importance of the Research Achievements |
本研究で開発した手法ならびに得られた知見により，様々な指標を確認しながら腫瘍領域を適切に抽出可能になることが期待できるとともに，抽出領域から腫瘍状態の変化を捉えるための特徴量を検討・評価できることで，腫瘍の特徴を捉える新たな方法につながる可能性があるという点において，学術的意義があると考えられる．さらにシミュレーション技術を組合わせることで今後の予後予測に寄与することができるという点で社会的な意義もあると考えられる．
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