Uncovering Contributors to Hypertension through Experimental and Computational Simulation (CHECS)

通过实验和计算模拟 (CHECS) 揭示高血压的成因

基本信息

  • 批准号:
    EP/K031546/1
  • 负责人:
  • 金额:
    $ 69.2万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Research Grant
  • 财政年份:
    2013
  • 资助国家:
    英国
  • 起止时间:
    2013 至 无数据
  • 项目状态:
    已结题

项目摘要

High blood pressure, or hypertension, is one of the most important causes of global morbidity and mortality in the developed world [1]. It has been shown that hypertensive people have a high risk of stroke, heart attack, heart failure and renal failure. The Health Survey for England in 2006 demonstrated that the prevalence of hypertension in the UK increased from 17% in the age group 40-49 years to 77% in those aged 70-79 years [2]. Hypertensive patients are usually identified by a threshold diagnosis of their systolic or diastolic pressures exceeding 140 or 90 mmHg respectively. However this diagnosis tends to misdiagnose the individuals in the large population in and around the threshold making the selection for appropriate therapy difficult. For example one important determinant of hypertension is the flexibility of the aorta (the first artery leading from the heart), which becomes stiffer with age and arteriosclerosis. However, such "stiffness" is only one among other geometrical and mechanical factors that influence the pressure pulse and thus hypertension. Therefore, non-invasive measurement of pulse pressure waveforms has been of interest for more than 100 years, and includes tonometry, Ultrasound and Magnetic Resonance Imaging (MRI). Although the non-invasive measurement of waveforms has become fast, the current analysis of the measured waveform data is relatively simplistic. In particular, the analysis of certain waveform features are performed in isolation and are impeded by a lack of understanding of the relative contributions from arterial stiffness/geometry, wave reflection and ventricular/arterial interaction to hypertensive pressure. Over the last two decades, computational modelling has been established as a new discipline to study the interaction of different parameters in the cardiovascular system. These models can help to separate the various contributions to the pressure waveform and elucidate complex interaction of parameters affecting hypertension. More recently, imaging data of the patient's anatomy and physiology has been introduced in numerical simulations to produce patient-specific models. Although, different models have been developed to investigate the influence of geometrical and mechanical factors, a model validation remains challenging since it would require large studies in animals and patients. This proposal aims at the identification of high-risk individuals by determining the mechanical factors which cause their pressure to be pathological. This approach would allow a better selection of appropriate treatments for the individual patient. For this, we propose the construction of a comprehensive experimental arterial model with which to determine and quantify main contributors to hypertensive pressure as well as to validate our existing computational arterial simulation frameworks (1D and 3D). Translation of these technologies towards the clinic will be facilitated with the construction of full-scale silicone arterial model, which will experimentally simulate haemodynamics of a hypertensive patient dataset. This will be followed by a clinical validation of a computational analysis tools in volunteers and a small patient cohort. References:[1] MacMahon, S., et al.: Blood-pressure-related disease is a global healthy priority. Lancet, 2006. 371: p. 1480-1482.[2] NHS, Health survey for england 2006 latest trends. 2008: Leeds.
高血压是发达国家全球发病率和死亡率最重要的原因之一[1]。研究表明,高血压患者中风、心脏病发作、心力衰竭和肾衰竭的风险很高。2006年英格兰健康调查表明,英国40-49岁年龄组的高血压患病率从17%增加到70-79岁年龄组的77%[2]。高血压患者通常通过其收缩压或舒张压分别超过140或90 mmHg的阈值诊断来识别。然而,这种诊断往往会误诊的个体在大量的人口和周围的阈值,使选择适当的治疗困难。例如,高血压的一个重要决定因素是主动脉(从心脏引出的第一条动脉)的柔韧性,随着年龄的增长和动脉硬化,主动脉变得越来越僵硬。然而,这种“刚度”只是影响压力脉冲并因此影响高血压的其他几何和机械因素之一。因此,100多年来,人们一直对脉搏压力波形的无创测量感兴趣,包括眼压测量、超声和磁共振成像(MRI)。虽然波形的非侵入式测量已经变得快速,但是当前对所测量的波形数据的分析相对简单。特别地,某些波形特征的分析是孤立地执行的,并且由于缺乏对动脉硬度/几何形状、波反射和心室/动脉相互作用对高血压的相对贡献的理解而受到阻碍。在过去的二十年里,计算建模已经被建立为一个新的学科,研究心血管系统中不同参数的相互作用。这些模型可以帮助分离压力波形的各种贡献,并阐明影响高血压的参数的复杂相互作用。最近,在数值模拟中引入了患者解剖和生理的成像数据,以产生患者特定的模型。虽然已经开发了不同的模型来研究几何和机械因素的影响,但模型验证仍然具有挑战性,因为它需要在动物和患者中进行大量研究。这项建议的目的是通过确定导致高风险个人的压力成为病理性的机械因素来识别他们。这种方法将允许更好地为个体患者选择适当的治疗。为此,我们提出了一个全面的实验动脉模型的建设,以确定和量化的主要贡献者高血压,以及验证我们现有的计算动脉模拟框架(1D和3D)。通过构建全尺寸硅胶动脉模型,将促进这些技术向临床的转化,该模型将通过实验模拟高血压患者数据集的血液动力学。随后将在志愿者和小型患者队列中对计算分析工具进行临床验证。参考文献:[1] MacMahon,S.,等:血压相关疾病是全球健康的优先事项。Lancet,2006. 371:第1480-1482页。[2]英国国民保健服务,2006年健康调查最新趋势。2008年:利兹。

项目成果

期刊论文数量(9)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
On the impact of modelling assumptions in multi-scale, subject-specific models of aortic haemodynamics.
关于在多尺度,主体血流动力学特定主题模型中建模假设的影响。
  • DOI:
    10.1098/rsif.2016.0073
  • 发表时间:
    2016-06
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Alastruey J;Xiao N;Fok H;Schaeffter T;Figueroa CA
  • 通讯作者:
    Figueroa CA
P52 ESTIMATING CENTRAL BLOOD PRESSURE FROM MRI DATA USING REDUCED-ORDER COMPUTATIONAL MODELS
P52 使用降阶计算模型根据 MRI 数据估计中心血压
  • DOI:
    10.1016/j.artres.2018.10.105
  • 发表时间:
    2018
  • 期刊:
  • 影响因子:
    0.6
  • 作者:
    Alastruey J
  • 通讯作者:
    Alastruey J
Novel wave intensity analysis of arterial pulse wave propagation accounting for peripheral reflections.
3.6 NON-INVASIVE, MRI-BASED ESTIMATION OF PATIENT-SPECIFIC AORTIC BLOOD PRESSURE USING ONE-DIMENSIONAL BLOOD FLOW MODELLING
3.6 使用一维血流模型对患者特异性主动脉血压进行无创、基于 MRI 的估计
  • DOI:
    10.1016/j.artres.2017.10.036
  • 发表时间:
    2017
  • 期刊:
  • 影响因子:
    0.6
  • 作者:
    Alastruey J
  • 通讯作者:
    Alastruey J
Comment on 'Numerical assessment and comparison of pulse wave velocity methods aiming at measuring aortic stiffness'.
  • DOI:
    10.1088/1361-6579/aaca80
  • 发表时间:
    2018-07-06
  • 期刊:
  • 影响因子:
    3.2
  • 作者:
    Charlton PH;Willemet M;Chowienczyk P;Alastruey J
  • 通讯作者:
    Alastruey J
{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Tobias Richard Schaeffter其他文献

Tobias Richard Schaeffter的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Tobias Richard Schaeffter', 18)}}的其他基金

Atherosclerosis stratification using advanced imaging and computer-based models
使用先进成像和计算机模型进行动脉粥样硬化分层
  • 批准号:
    EP/L505304/1
  • 财政年份:
    2014
  • 资助金额:
    $ 69.2万
  • 项目类别:
    Research Grant
Magnetic Resonance Guided Therapy of Cardiac Arhythmia ( MaRGiTA)
磁共振引导心律失常治疗 (MaRGiTA)
  • 批准号:
    TS/G002142/1
  • 财政年份:
    2009
  • 资助金额:
    $ 69.2万
  • 项目类别:
    Research Grant

相似海外基金

An Integrated Model of Contextual Safety, Social Safety, and Social Vigilance as Psychosocial Contributors to Cardiovascular Disease
情境安全、社会安全和社会警惕作为心血管疾病社会心理因素的综合模型
  • 批准号:
    10749134
  • 财政年份:
    2024
  • 资助金额:
    $ 69.2万
  • 项目类别:
Investigation of Endocrine-Disrupting Chemicals as Contributors to Progression of Metabolic Dysfunction Associated Steatotic Liver Disease (EDC-MASLD)
内分泌干​​扰化学物质对代谢功能障碍相关脂肪性肝病 (EDC-MASLD) 进展的影响的调查
  • 批准号:
    10092670
  • 财政年份:
    2024
  • 资助金额:
    $ 69.2万
  • 项目类别:
    EU-Funded
Antecedents and consequences of cruise travel experience: Identifying contributors to well-being of cruise tourists.
邮轮旅行体验的前因和后果:确定邮轮游客福祉的贡献者。
  • 批准号:
    24K15536
  • 财政年份:
    2024
  • 资助金额:
    $ 69.2万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Pan-ancestry approaches to understand the genetic and environmental contributors to mental health in children and youth
通过泛祖方法了解儿童和青少年心理健康的遗传和环境因素
  • 批准号:
    498293
  • 财政年份:
    2023
  • 资助金额:
    $ 69.2万
  • 项目类别:
    Operating Grants
Genetic Contributors to the Impact of Sex on Heterogeneity in Flu Infection
性别对流感感染异质性影响的遗传因素
  • 批准号:
    10869787
  • 财政年份:
    2023
  • 资助金额:
    $ 69.2万
  • 项目类别:
Arterial Stiffness and Wave Reflection: Physiological Contributors to CVD after Adverse Pregnancy Outcomes
动脉僵硬度和波反射:不良妊娠结果后 CVD 的生理因素
  • 批准号:
    10632908
  • 财政年份:
    2023
  • 资助金额:
    $ 69.2万
  • 项目类别:
A Multimethod Examination of Individual and Environment Contributors to Racial Inequities in Cannabis Use
对大麻使用中种族不平等的个人和环境因素的多方法检验
  • 批准号:
    10732346
  • 财政年份:
    2023
  • 资助金额:
    $ 69.2万
  • 项目类别:
Screen Lives: What the experiences of documentary contributors tell us about the media
银幕生活:纪录片撰稿人的经历告诉我们关于媒体的什么
  • 批准号:
    ES/Y007808/1
  • 财政年份:
    2023
  • 资助金额:
    $ 69.2万
  • 项目类别:
    Fellowship
Evaluating Contributors to Relapse in Comorbid Major Depressive Disorder and Cannabis Use Disorder
评估共病重度抑郁症和大麻使用障碍复发的因素
  • 批准号:
    10640111
  • 财政年份:
    2022
  • 资助金额:
    $ 69.2万
  • 项目类别:
Identifying contributors to racial and ethnic disparities in child occupant safety
确定儿童乘员安全方面种族和民族差异的影响因素
  • 批准号:
    10685521
  • 财政年份:
    2022
  • 资助金额:
    $ 69.2万
  • 项目类别:
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了