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Computational techniques for studying the interactions of radiation with matter and applications in radiotherapy physics

Computational techniques for studying the interactions of radiation with matter and applications in radiotherapy physics
研究辐射与物质相互作用的计算技术及其在放射治疗物理中的应用
批准号:
RGPIN-2016-06267
负责人:
Thomson, Rowan
金额:
$2.4万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2020
资助国家:
加拿大
项目状态:
已结题
起止时间:
2020-01-01 至 2021-12-31

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中文摘要
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英文摘要
Radiotherapy is commonly used as a treatment for cancer. All forms of radiotherapy aim to maximize tumour cell kill while limiting healthy tissue radiation exposure. Despite the widespread application of radiotherapy to treat cancer, fundamental questions relating to the interactions of radiation with matter remain. Further, potential future treatment methods prompt new areas of investigation. This research program involves the development and application of sophisticated computer codes which employ the so-called 'Monte Carlo' (MC) method to model the passage of radiation through matter. These MC simulations can be used to compute dose, the energy deposited by radiation in tissue, as well as to study a wide array of questions relevant for radiotherapy treatments. An existing treatment to be considered is brachytherapy, in which radioactive sources are placed next to or inside a tumour (in, e.g., the prostate, breast, or eye). Widely-used dose calculation algorithms are inaccurate; a fast, accurate, and comprehensive MC dose calculation program is under development and will be used to study brachytherapy physics. There is increasing interest in simulating radiation interactions and radiation-induced damage at the level of cellular constituents and DNA to understand the biological effects of radiation. Simulations of microscopic tissue structure including cells and their components present computational challenges; furthermore, new approaches consistent with modern quantum physics may be required at very low energies and short distance scales. New methods for performing simulations of radiation transport on multiple scales, from patient-level down to cells and cell components in tissue, will be developed. These techniques will be applied to understand patterns of energy deposition within tissue for different radiation sources, towards developing an understanding of the biological effects of radiation. These new computational approaches will also be applied to study potential future treatment techniques such as delivery of radiotherapy involving nanometre-sized devices and other targeted therapies. This research will advance our knowledge of the interactions of radiation with matter and radiation dosimetry. It will yield new computational techniques to simulate radiation transport from macroscopic to microscopic length scales. Computer codes developed will be disseminated to the international research community to foster further research. The results of this research program will find application in many fields involving radiation physics including diagnostic imaging, radiation protection, radiobiology, and radiation therapy. This research will contribute to the development of new treatment techniques, as well as yielding new insights into past and current treatments.
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Radiotherapy Physics
  • 批准号:
    CRC-2018-00277
  • 项目类别:
    Canada Research Chairs
  • 资助金额:
    $7.29万
  • 财政年份:
    2022
  • 负责人:
    Thomson, Rowan
  • 依托单位:
Computational techniques for studying the interactions of radiation with matter and applications in radiotherapy physics
  • 批准号:
    RGPIN-2016-06267
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.81万
  • 财政年份:
    2022
  • 负责人:
    Thomson, Rowan
  • 依托单位:
Radiotherapy Physics
  • 批准号:
    CRC-2018-00277
  • 项目类别:
    Canada Research Chairs
  • 资助金额:
    $7.29万
  • 财政年份:
    2021
  • 负责人:
    Thomson, Rowan
  • 依托单位:
Computational techniques for studying the interactions of radiation with matter and applications in radiotherapy physics
  • 批准号:
    RGPIN-2016-06267
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.4万
  • 财政年份:
    2021
  • 负责人:
    Thomson, Rowan
  • 依托单位:
国内基金
海外基金
EstimatingLarge Demand Systems with MachineLearning Techniques
  • 批准号:
    --
  • 项目类别:
    外国学者研究基金
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    IoshuaAlex
  • 依托单位:
计算电磁学高稳定度辛算法研究
  • 批准号:
    60931002
  • 项目类别:
    重点项目
  • 资助金额:
    200.0万元
  • 批准年份:
    2009
  • 负责人:
    吴先良
  • 依托单位: