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Adaptive, Multi-scale, Data-Infused Biomechanical Models for Cardiac Diagnostic and Prognostic Assessment

Adaptive, Multi-scale, Data-Infused Biomechanical Models for Cardiac Diagnostic and Prognostic Assessment
用于心脏诊断和预后评估的自适应、多尺度、数据注入生物力学模型
批准号:
EP/R003866/1
负责人:
David Nordsletten
金额:
$143.16万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2018
资助国家:
英国
项目状态:
已结题
起止时间:
2018 至 --

项目摘要

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中文摘要
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英文摘要
Driven by structural and functional abnormalities in the muscle of the heart, Heart Failure (HF) is a complex syndrome affecting around 900,000 people in the UK. HF results in a fundamental reduction in the ability of heart muscle to effectively pump and deliver blood to the body. While this deficiency in pump function is easily observed using medical imaging, dissecting the underlying cause of this reduced performance in terms of its implications for muscle structure and function remain open challenges. Further, predicting how disease will progress or respond to therapy remains an unmet need that would substantially improve patient care.Using state-of-the art biomechanical modelling, the "Adaptive, Multi-scale, Data-Infused Biomechanical Models for Cardiac Diagnostic and Prognostic Assessment" project will address these challenges by providing a modelling framework for assessment of the heart. Uniting measurements from microscopy, rheology, and medical imaging, this project aims to create biomechanical models that provide detailed information on the structure and function of the heart aiding diagnosis. Further, the platform will provide infrastructure for predictive modelling, simulating the response and adaptation of the heart over time. Biomechanical models will be systematically validated using animal heart models, providing rich data for understanding the biomechanics in vivo and ex vivo. The framework will, further, be directly translated through a novel study in patients with hypertrophic cardiomyopathy, providing a test bed for validation of predictive models of disease progression and response to therapy through virtual surgery.
期刊论文(10)
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科研奖励(0)
会议论文
DOI: 10.1007/s10237-018-1072-1
发表时间: 2019-03
期刊: Biomechanics and modeling in mechanobiology
影响因子: 3.5
作者: [Capilnasiu A, Hadjicharalambous M, Fovargue D, Patel D, Holub O, Bilston L, Screen H, Sinkus R, Nordsletten D]
通讯作者: Nordsletten D
DOI: 10.1007/s10237-020-01297-5
发表时间: 2020-10
期刊: Biomechanics and modeling in mechanobiology
影响因子: 3.5
作者: [Capilnasiu A, Bilston L, Sinkus R, Nordsletten D]
通讯作者: Nordsletten D
A stabilized multidomain partition of unity approach to solving incompressible viscous flow
求解不可压缩粘性流的稳定多域统一方法划分
DOI: 10.1016/j.cma.2022.114656
发表时间: 2022
期刊: Computer Methods in Applied Mechanics and Engineering
影响因子: 7.2
作者: [Balmus M]
通讯作者: Balmus M
Hemodynamic Modeling for Mitral Regurgitation
二尖瓣反流的血流动力学建模
DOI: 10.1016/j.healun.2022.01.1685
发表时间: 2022
期刊: The Journal of Heart and Lung Transplantation
影响因子: --
作者: [Bonini M]
通讯作者: Bonini M
Imaging Cardio-Mechanical Health
  • 批准号:
    EP/N011554/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $85.48万
  • 财政年份:
    2016
  • 负责人:
    David Nordsletten
  • 依托单位:
国内基金
海外基金
基于Multi-Pass Cell的高功率皮秒激光脉冲非线性压缩关键技术研究
Multi-decadeurbansubsidencemonitoringwithmulti-temporaryPStechnique
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    80万元
  • 批准年份:
    2022
  • 负责人:
    Timo Balz
  • 依托单位:
High-precision force-reflected bilateral teleoperation of multi-DOF hydraulic robotic manipulators
  • 批准号:
    52111530069
  • 项目类别:
    国际(地区)合作与交流项目
  • 资助金额:
    10万元
  • 批准年份:
    2021
  • 负责人:
    徐兵
  • 依托单位:
大地电磁强噪音压制的Multi-RRMC技术及其在青藏高原东南缘-印支块体地壳流追踪中的应用