| Project/Area Number |
18K18394
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 90130:Medical systems-related
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| Research Institution | Hokkaido University |
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Principal Investigator |
Wang Jeffrey 北海道大学, 国際連携研究教育局, 博士研究員 (80754829)
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| Project Period (FY) |
2018-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2019: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2018: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Keywords | CT reconstruction / Machine learning / Radiotherapy / Dosimetry / Acoustic imaging / Acoustic Imaging / Radiation therapy / Computed tomography |
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| Outline of Final Research Achievements |
A framework for simulation of radiotherapy dose deposition and induced acoustic wave production was developed. X-ray beam parameter dependency of induced acoustics was reviewed. Standard clinical radiotherapy system setups are not ideal given beam length is long. Significant reconstruction artifacts exist proportional to distance from transducer elements as well to completeness in coverage by distribution of sensor arrays, though physically obstructing the irradiating beam's path also an issue.
Knowledge of exact tissue properties is critical for quantitative acoustic imaging and accurate dosimetry, especially in real-time as the body moves during treatment. Efforts were focused on investigation of advanced image reconstruction and artifact reduction methods. On-board and body surface depth imaging were used as motion surrogates to render higher quality planning CT. Performance competitive, if not superior, to state-of-the-art techniques were apparent in accuracy and inference speed.
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| Academic Significance and Societal Importance of the Research Achievements |
X-ray-induced acoustics could be realized for absolute dosimetry in radiotherapy, if clinical systems are setup with shorter beam lengths and sensor array designs are balanced between anatomy coverage and beam obstruction. To do so in real-time could be facilitated by neural image reconstruction.
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