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Non-invasive assessment of bone strength

Non-invasive assessment of bone strength
无创评估骨强度
批准号:
261693-2013
负责人:
Boyd, Steven
金额:
$2.7万
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:
2015
资助国家:
加拿大
项目状态:
已结题
起止时间:
2015-01-01 至 2016-12-31

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中文摘要
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英文摘要
The long-term goal of this research is to develop methods for non-invasive assessment of bone quality and strength in patients suffering from bone and joint diseases. The core of this proposal uses newly established human micro-computed tomography (µCT) and clinical CT to generate patient-specific finite element (FE) models that can determine bone strength. There are four specific aims of the research program working towards the goal of improving care for patients with osteoporosis, and these are based on a decade of work. First, work will advance our custom FE code designed to solve extremely large models (10's of millions of elements) in a fast, efficient manner using standard desktop workstations. This is a major departure from the previous necessity of using 'super computers' and makes the technology significantly more accessible. Important modeling advances will include sophisticated non-linear material models for an improved estimate of bone strength. Second, the ability to analyse a human femur and/or vertebrae that is contained in complex 3D CT images will be developed, and form the core of an automated process to enable bone strength estimation from CT. In the third aim, enriching CT data with underlying material fabric information will be based on the development of a novel bone atlas that contains detailed microarchitectural patterns to enhance the FE prediction of bone strength. This approach will be a major advancement over the currently simplistic approach of using CT density values to assume material properties. Finally, machine-learning tools will be developed to utilize the image-based FE model predictions of bone strength so that a subject-specific estimate of bone strength can be calculated. This research focus is important, as it will establish a new approach for early detection and monitoring of bone strength by combining state-of-the-art imaging with specialized FE modeling. This approach will provide a basis for better understanding of the relationship between bone quality and fracture load, and provide a much-needed engineering contribution to better management of devastating diseases such as osteoporosis.
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Non-invasive assessment of bone strength
  • 批准号:
    RGPIN-2019-04135
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.66万
  • 财政年份:
    2022
  • 负责人:
    Boyd, Steven
  • 依托单位:
Non-invasive assessment of bone strength
  • 批准号:
    RGPIN-2019-04135
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.66万
  • 财政年份:
    2021
  • 负责人:
    Boyd, Steven
  • 依托单位:
Non-invasive assessment of bone strength
  • 批准号:
    RGPIN-2019-04135
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.66万
  • 财政年份:
    2020
  • 负责人:
    Boyd, Steven
  • 依托单位:
Non-invasive assessment of bone strength
  • 批准号:
    RGPIN-2019-04135
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.66万
  • 财政年份:
    2019
  • 负责人:
    Boyd, Steven
  • 依托单位:
国内基金
海外基金
基于深穿透拉曼光谱的安全光照剂量的深层病灶无创检测与深度预测
  • 批准号:
    82372016
  • 项目类别:
    面上项目
  • 资助金额:
    48.00万元
  • 批准年份:
    2023
  • 负责人:
    林俐
  • 依托单位: