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Computational Modeling for Dialysis Access Surgical Planning

Computational Modeling for Dialysis Access Surgical Planning
透析通路手术规划的计算模型
批准号:
7511676
负责人:
DANIEL F LEOTTA
金额:
$19.11万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-09-11 至 2010-08-31

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中文摘要
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DESCRIPTION (provided by applicant): The long term goal of this work is to develop a surgical planning package to aid in the pre-operative and post-operative management of dialysis access sites. The package will consist of an ultrasound imaging system that provides 3D anatomical and flow velocity information, and a Fluid Structure Interaction model. The computational model will utilize the anatomical and flow velocity information for pre-treatment planning, prediction of post-treatment outcome, and correlation of post-treatment response with the computationally-derived hemodynamic parameters. In the long-term, the imaging and analysis package will allow a surgeon to virtually test dialysis access configurations prior to the surgical procedure. This surgical planning package is expected to increase the lifetime of access sites and reduce the number of dialysis access surgery cases that require secondary intervention, thereby improving patient outcomes and reducing costs. Since this package is ultrasound based, it is non-invasive and can safely and cost-effectively follow patients over time. We have already developed the ultrasound imaging capabilities to support this project; therefore this grant is focused on the development of the Fluid Structure Interaction simulation. PUBLIC HEALTH RELEVANCE: The long term goal of this work is to develop a surgical planning package to aid in the pre-operative and post-operative management of dialysis access sites. Since this planning package will be entirely based on ultrasound imaging, it is non-invasive, safe and cost-effective. This surgical planning package is expected to increase the lifetime of access sites and reduce the number of dialysis access surgery cases that require secondary intervention, thereby improving patient outcomes and reducing costs.
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