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Grand Challenge: Translating Biomedical Modelling into the Heart of the Clinic

重大挑战：将生物医学模型转化为诊所的核心

基本信息

批准号：
EP/F059175/1
负责人：
Reza Sarvghad Razavi
金额：
$ 14.1万
依托单位：
King's College London
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2008
资助国家：
英国
起止时间：
2008 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FF059175%2F1
关键词：
Grand Challenge Translating Biomedical Modelling

项目摘要

Heart disease is the most common cause of illness and death in the western world. Each year it causes over 208,000 deaths in the UK including nearly half of all non-accidental deaths. Improving the treatment of heart disease is one of the main priorities of the NHS. The aim of this project is to work out the best way we can improve the diagnosis and treatment of heart disease by using state of the art computer models that have been built and personalised for each patient using information such as scans of their heart. These computer models can predict what goes on in the heart by using detailed mathematical formulae which copy they way the heart behaves all the way down to the millions of cells that make up the heart. This works is now possible because of the rapid increases in computer power which means they can quickly do the large number of calculations needed to make the models work. Also because we can do very detailed three-dimensional scans of the heart in patients at the same time as measure the electrical patterns and blood pressure inside the heart we are putting in very accurate information into the models and so can get accurate answers out. These answers have the potential of telling us which patients are going to be at risk of a heart attack or what's the best ways to treat patients whose hearts are not working well. By getting this research to work and implemented in hospital we should be able to substantially improve the treatment of patients with heart disease and even reduce the costs to the NHS.

心脏病是西方世界最常见的疾病和死亡原因。在英国，每年有超过20.8万人死于吸烟，其中包括近一半的非意外死亡。改善心脏病的治疗是国民保健制度的主要优先事项之一。这个项目的目的是通过使用最先进的计算机模型，我们可以找到最好的方法来改善心脏病的诊断和治疗，这些模型是为每个病人建立的，并根据他们的心脏扫描等信息进行个性化设置。这些计算机模型可以通过使用详细的数学公式来预测心脏的情况，这些公式将心脏的行为一直复制到组成心脏的数百万个细胞中。这是可行的，因为计算机能力的快速增长，这意味着他们可以快速地进行大量的计算，使模型工作。因为我们可以对病人的心脏进行非常详细的三维扫描同时测量心脏内的电模式和血压我们将非常准确的信息输入到模型中，因此可以得到准确的答案。这些答案有可能告诉我们哪些病人会有心脏病发作的风险，或者治疗心脏不正常的病人的最佳方法是什么。通过让这项研究发挥作用并在医院实施，我们应该能够大大改善心脏病患者的治疗，甚至降低NHS的成本。