Investigating Myocardial Infarct Scars as a Focal Arrhythmogenic Substrate Using Advanced Computational Modelling Based-On High-Resolution Imaging
使用基于高分辨率成像的高级计算模型研究心肌梗死疤痕作为局灶性心律失常的基质
基本信息
- 批准号:EP/K034367/1
- 负责人:
- 金额:$ 12.62万
- 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
- 来源:
- 关键词:
项目摘要
Although an increasing number of people survive heart attacks, the scar left in their heart muscle leaves them at an increased risk of developing lethal cardiac 'arrhythmias' (abnormal beating of the heart) following the initial attack. Little is known about the underlying processes linking the presence of scars to increased death from cardiac arrhythmias. Specifically, it is not well understood whether the scar is involved in the actual generation of the arrhythmia, or whether it just helps to stabilise an arrhythmic episode generated by another mechanism, unrelated to the scar itself. As a result, diagnosis and therapy planning is non-optimal for these patients, and the rate of sudden death due to arrhythmic events is still high within this population.Current clinical tools can provide useful information regarding scars within patients who have suffered prior heart attacks. Clinical magnetic resonance (MR) imaging gives an important non-invasive means of analysing the location and shape of scars in patients. In addition, analysis of clinical electrocardiogram (ECG) recordings during arrhythmia can suggest not only the type of arrhythmia, but also the role the scar may play in such episodes. In particular, careful analysis of the shape of the ECG trace in the first few arrhythmic beats has suggested that, in many cases, the scar itself is highly likely to be the actual source of the ectopic activity responsible for generating the arrhythmia.Basic science investigations have shown that the structure of the tissue in and around the scar is highly diverse, and that the functional electrical properties are also changed from that of the normal, healthy cardiac tissue. As such, how the scar may act to generate lethal arrhythmia is thought to involve highly complex processes, which are not yet well understood.Our goal is to use computer modelling alongside high-resolution animal and clinical images to gain an in-depth understanding of the underlying processes involved in the generation of lethal arrhythmias directly from within cardiac scars.By using high-resolution animal images of scars, we will generate exceptionally-detailed computational models to investigate how the interaction between structural and functional diversity within a scar may encourage the generation of arrhythmia. This will allow us to understand how the fine-scaled properties of the scar and surrounding tissue make it susceptible to arrhythmias, identifying key 'hot spot' regions which represent the most dangerous potential sources of arrhythmic activity.We will then use this knowledge in comparison with patient MR and arrhythmia incidence data to make an important step towards translating these findings into the clinic, helping provide a mechanistic explanation of the underlying observed relationships uncovered in the clinical data.Overall, the findings from this research will pave the way for improved of risk stratification in patients with cardiac scars, and the development of novel clinically-useful therapies targeting the scar as a source of arrhythmia generation. The potential beneficiaries from this research will be extensive due to the high incidence of heart attacks annually in the UK (124,000), and the significant risk posed by arrhythmia to individuals following a heart attack. Consequently, this work also has the potential to reduce the health and economic costs of associated death and illness.
虽然越来越多的人在心脏病发作后幸存下来,但他们心肌中留下的疤痕使他们在最初的发作后患致命的心脏“心律失常”(心脏跳动异常)的风险增加。关于疤痕的存在与心律失常死亡率增加之间的潜在联系,人们知之甚少。具体而言,尚不清楚疤痕是否参与心律失常的实际产生,或者它是否只是有助于稳定由另一种机制产生的心律失常发作,而与疤痕本身无关。因此,对这些患者的诊断和治疗计划是非最佳的,并且在这一人群中由于心脏病事件而导致的猝死率仍然很高。临床磁共振(MR)成像提供了一个重要的非侵入性手段,分析的位置和形状的疤痕患者。此外,分析心律失常期间的临床心电图(ECG)记录不仅可以提示心律失常的类型,还可以提示瘢痕在此类事件中可能发挥的作用。特别是,对最初几次心跳中ECG轨迹形状的仔细分析表明,在许多情况下,疤痕本身极有可能是导致心律失常的异位活动的实际来源。基础科学研究表明,疤痕内和疤痕周围的组织结构高度多样化,并且功能性电特性也从正常健康的心脏组织的功能性电特性改变。因此,疤痕如何产生致命的心律失常被认为涉及高度复杂的过程,这还没有得到很好的理解。我们的目标是使用计算机建模以及高分辨率的动物和临床图像,以深入了解直接从心脏疤痕中产生致命心律失常的潜在过程。通过使用高分辨率的疤痕动物图像,我们将产生非常详细的计算模型来研究疤痕内结构和功能多样性之间的相互作用如何可能促进心律失常的产生。这将使我们能够了解疤痕和周围组织的精细尺度特性如何使其易受心律失常的影响,识别代表最危险的潜在心律失常活动源的关键“热点”区域。然后,我们将利用这些知识与患者MR和心律失常发生率数据进行比较,从而朝着将这些发现转化为临床迈出重要一步。总体而言,这项研究的发现将为改善心脏瘢痕患者的风险分层以及开发针对瘢痕作为心律失常产生来源的新型临床有用疗法铺平道路。这项研究的潜在受益者将是广泛的,因为英国每年心脏病发作的发病率很高(124,000),以及心脏病发作后心律失常对个人造成的重大风险。因此,这项工作也有可能减少相关死亡和疾病的健康和经济成本。
项目成果
期刊论文数量(7)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Image-Based Personalization of Cardiac Anatomy for Coupled Electromechanical Modeling.
- DOI:10.1007/s10439-015-1474-5
- 发表时间:2016-01
- 期刊:
- 影响因子:3.8
- 作者:Crozier A;Augustin CM;Neic A;Prassl AJ;Holler M;Fastl TE;Hennemuth A;Bredies K;Kuehne T;Bishop MJ;Niederer SA;Plank G
- 通讯作者:Plank G
Structural heterogeneity modulates effective refractory period: a mechanism of focal arrhythmia initiation.
结构异质性调节有效的难治期:局灶性心律不齐的机制。
- DOI:10.1371/journal.pone.0109754
- 发表时间:2014
- 期刊:
- 影响因子:3.7
- 作者:Bishop MJ;Connolly A;Plank G
- 通讯作者:Plank G
Computational Representations of Myocardial Infarct Scars and Implications for Arrhythmogenesis.
- DOI:10.4137/cmc.s39708
- 发表时间:2016
- 期刊:
- 影响因子:0
- 作者:Connolly AJ;Bishop MJ
- 通讯作者:Bishop MJ
Local Gradients in Electrotonic Loading Modulate the Local Effective Refractory Period: Implications for Arrhythmogenesis in the Infarct Border Zone.
- DOI:10.1109/tbme.2015.2421296
- 发表时间:2015-09
- 期刊:
- 影响因子:0
- 作者:Connolly A;Trew ML;Smaill BH;Plank G;Bishop MJ
- 通讯作者:Bishop MJ
Simulating photon scattering effects in structurally detailed ventricular models using a Monte Carlo approach.
- DOI:10.3389/fphys.2014.00338
- 发表时间:2014
- 期刊:
- 影响因子:4
- 作者:Bishop MJ;Plank G
- 通讯作者:Plank G
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Martin Bishop其他文献
Developing cardiac digital twin populations powered by machine learning provides electrophysiological insights in conduction and repolarization
开发由机器学习驱动的心脏数字双胞胎群体,提供了在传导和复极化方面的电生理见解
- DOI:
10.1038/s44161-025-00650-0 - 发表时间:
2025-05-16 - 期刊:
- 影响因子:10.800
- 作者:
Shuang Qian;Devran Ugurlu;Elliot Fairweather;Laura Dal Toso;Yu Deng;Marina Strocchi;Ludovica Cicci;Richard E. Jones;Hassan Zaidi;Sanjay Prasad;Brian P. Halliday;Daniel Hammersley;Xingchi Liu;Gernot Plank;Edward Vigmond;Reza Razavi;Alistair Young;Pablo Lamata;Martin Bishop;Steven Niederer - 通讯作者:
Steven Niederer
The integral Chow ring of $\mathcal{M}_{1,n}$ for $n=3,\dots,10$
$mathcal{M}_{1,n}$ 的积分 Chow 环,$n=3,dots,10$
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Martin Bishop - 通讯作者:
Martin Bishop
BS-516-01 A NOVEL COMPUTATIONAL-AI FRAMEWORK TO DETECT SITES OF ORIGINS OF SCAR-RELATED VENTRICULAR TACHYCARDIA FROM IMPLANTED DEVICE ELECTROGRAMS
- DOI:
10.1016/j.hrthm.2022.03.743 - 发表时间:
2022-05-01 - 期刊:
- 影响因子:5.700
- 作者:
Sofia Monaci;Shuang Qian;Karli Gillette;Martin Bishop;Martin Bishop;Gernot Plank;Martin Bishop;Martin J. Bishop - 通讯作者:
Martin J. Bishop
Developing Cardiac Digital Twins at Scale: Insights from Personalised Myocardial Conduction Velocity
大规模开发心脏数字孪生:个性化心肌传导速度的见解
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Shuang Qian;Devran Ugurlu;Elliot Fairweather;M. Strocchi;Laura Dal Toso;Yu Deng;Reza Razavi;Alistair Young;Pablo Lamata;Martin Bishop;Steven A Niederer - 通讯作者:
Steven A Niederer
Performance of atrial conduction velocity algorithms with error-prone clinical measurements for the identification of atrial fibrosis
具有易错临床测量的心房传导速度算法在识别心房纤维化方面的性能
- DOI:
10.1016/j.compbiomed.2025.110119 - 发表时间:
2025-06-01 - 期刊:
- 影响因子:6.300
- 作者:
Ali Gharaviri;Vinush Vigneswaran;Keeran Vickneson;Caroline Roney;Cesare Corrado;Sam Coveney;Kestutis Maciunas;Neil Bodagh;Magda Klis;Irum Kotadia;Iain Sim;John Whitaker;Martin Bishop;Steven Niederer;Mark O'Neill;Steven E. Williams - 通讯作者:
Steven E. Williams
Martin Bishop的其他文献
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{{ truncateString('Martin Bishop', 18)}}的其他基金
Understanding the Mechanistic Links Between Mid-Wall Fibrosis and Arrhythmic Risk in Non-Ischemic DCM Using a Combined Modelling & Clinical Approach
使用组合模型了解非缺血性 DCM 中壁纤维化与心律失常风险之间的机制联系
- 批准号:
MR/N011007/1 - 财政年份:2016
- 资助金额:
$ 12.62万 - 项目类别:
Research Grant
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