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
• 负责人: Tobias Richard Schaeffter
• 金额: $ 39.46万
• 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: 2014
• 资助国家: 英国
• 起止时间: 2014 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FL505304%2F1
• 关键词: Atherosclerosis; stratification; using; advanced; imaging

The goal of the proposed project is to develop a novel tool for atherosclerosis risk stratification. Cardiovascular disease(CVD) via atherosclerotic plaque rupture (coronary artery disease (CAD) and stroke) is the leading single cause ofmorbidity and mortality in the Western world. Vascular atherosclerotic disease is a causative factor in a high percentage ofCVD events. Widely accepted risk markers that allow predicting cardiovascular events such as myocardial infarction andstroke are currently based on risk factors such as smoking, weight and blood pressure. These lifestyle factors and medicalconditions are derived from population based studies and are linked to an average probability of having a CV event, but donot measure the individual's personal risk, and are therefore can result in potential overtreatment.The main deliverable from this project will be a computational tool to assess the grade of atherosclerosis of an individualperson using multi-parametric magnetic resonance imaging (MRI) in combination with biophysical computer models.Advanced imaging with Magnetic Resonance will be used for plaque burden measurement and plaque componentcharacterization in order to identify the risk of rupture and the systemic atherosclerosis burden. The team will use exitingMRI methods in combination with novel markers of plaque vulnerability. These markers include: plaque volume, intraplaquehaemorrhage, lipid content, calcification, endothelial permeability and extracellular volume. In addition, biophysicalmodels will be used to predict biomechanical properties related to atherosclerotic changes in the vascular system. Theteam will investigate and compute markers such as wall shear stress, particle residence time and arterial wall stiffness,which can give further insight into atherosclerosis development. For the first time, different parameters from modelling and The goal of the proposed project is to develop a novel tool for atherosclerosis risk stratification. Cardiovascular disease(CVD) via atherosclerotic plaque rupture (coronary artery disease (CAD) and stroke) is the leading single cause ofmorbidity and mortality in the Western world. Vascular atherosclerotic disease is a causative factor in a high percentage ofCVD events. Widely accepted risk markers that allow predicting cardiovascular events such as myocardial infarction andstroke are currently based on risk factors such as smoking, weight and blood pressure. These lifestyle factors and medicalconditions are derived from population based studies and are linked to an average probability of having a CV event, but donot measure the individual's personal risk, and are therefore can result in potential overtreatment.The main deliverable from this project will be a computational tool to assess the grade of atherosclerosis of an individualperson using multi-parametric magnetic resonance imaging (MRI) in combination with biophysical computer models.Advanced imaging with Magnetic Resonance will be used for plaque burden measurement and plaque componentcharacterization in order to identify the risk of rupture and the systemic atherosclerosis burden. The team will use exitingMRI methods in combination with novel markers of plaque vulnerability. These markers include: plaque volume, intraplaquehaemorrhage, lipid content, calcification, endothelial permeability and extracellular volume. In addition, biophysicalmodels will be used to predict biomechanical properties related to atherosclerotic changes in the vascular system. Theteam will investigate and compute markers such as wall shear stress, particle residence time and arterial wall stiffness,which can give further insight into atherosclerosis development. For the first time, different parameters from modelling and The goal of the proposed project is to develop a novel tool for atherosclerosis risk stratification. Cardiovascular disease(CVD) via atherosclerotic plaque rupture (coronary artery disease (CAD) and stroke) is the leading single cause ofmorbidity and mortality in the Western world. Vascular atherosclerotic disease is a causative factor in a high percentage ofCVD events. Widely accepted risk markers that allow predicting cardiovascular events such as myocardial infarction andstroke are currently based on risk factors such as smoking, weight and blood pressure. These lifestyle factors and medicalconditions are derived from population based studies and are linked to an average probability of having a CV event, but donot measure the individual's personal risk, and are therefore can result in potential overtreatment.The main deliverable from this project will be a computational tool to assess the grade of atherosclerosis of an individualperson using multi-parametric magnetic resonance imaging (MRI) in combination with biophysical computer models.Advanced imaging with Magnetic Resonance will be used for plaque burden measurement and plaque componentcharacterization in order to identify the risk of rupture and the systemic atherosclerosis burden. The team will use exitingMRI methods in combination with novel markers of plaque vulnerability. These markers include: plaque volume, intraplaquehaemorrhage, lipid content, calcification, endothelial permeability and extracellular volume. In addition, biophysicalmodels will be used to predict biomechanical properties related to atherosclerotic changes in the vascular system. Theteam will investigate and compute markers such as wall shear stress, particle residence time and arterial wall stiffness,which can give further insight into atherosclerosis development. For the first time, different parameters from modelling and imaging will be integrated into one clinical tool for comprehensive and individual risk stratification on different assessmentlevels.

该项目的目标是开发一种新的动脉粥样硬化危险分层工具。在西方世界，通过动脉粥样硬化斑块破裂（冠状动脉疾病（CAD）和中风）引起的心血管疾病（CVD）是发病率和死亡率的主要单一原因。血管粥样硬化性疾病是高比例心血管事件的致病因素。目前，广泛接受的可以预测心血管事件（如心肌梗死和中风）的风险标志物是基于吸烟、体重和血压等风险因素。这些生活方式因素和医疗条件来自基于人群的研究，与发生CV事件的平均概率相关，但不衡量个体的个人风险，因此可能导致潜在的过度治疗。该项目的主要成果将是一种计算工具，用于使用多参数磁共振成像（MRI）评估个体的动脉粥样硬化程度。结合生物物理计算机模型。先进的磁共振成像将用于斑块负荷测量和斑块成分表征，以确定破裂风险和全身动脉粥样硬化负荷。研究小组将使用现有的MRI方法结合新的斑块易损性标记物。这些标志物包括：斑块体积、斑块内出血、脂质含量、钙化、内皮通透性和细胞外体积。此外，生物力学模型将用于预测与血管系统中动脉粥样硬化变化相关的生物力学特性。研究小组将调查和计算壁面剪切应力、颗粒停留时间和动脉壁硬度等指标，这些指标可以进一步了解动脉粥样硬化的发展。第一次，不同的参数从建模和拟议项目的目标是开发一种新的工具动脉粥样硬化风险分层。在西方世界，通过动脉粥样硬化斑块破裂（冠状动脉疾病（CAD）和中风）引起的心血管疾病（CVD）是发病率和死亡率的主要单一原因。血管粥样硬化性疾病是高比例心血管事件的致病因素。目前，广泛接受的可以预测心血管事件（如心肌梗死和中风）的风险标志物是基于吸烟、体重和血压等风险因素。这些生活方式因素和医疗状况源自基于人群的研究，并与发生CV事件的平均概率有关，但不衡量个人的个人风险，因此可能导致潜在的过度治疗。该项目的主要成果将是一种计算工具，用于使用多参数磁共振成像（MRI）评估个体的动脉粥样硬化程度。结合生物物理计算机模型。先进的磁共振成像将用于斑块负荷测量和斑块成分表征，以确定破裂风险和全身动脉粥样硬化负荷。研究小组将使用现有的MRI方法结合新的斑块易损性标记物。这些标志物包括：斑块体积、斑块内出血、脂质含量、钙化、内皮通透性和细胞外体积。此外，生物力学模型将用于预测与血管系统中动脉粥样硬化变化相关的生物力学特性。研究小组将调查和计算壁面剪切应力、颗粒停留时间和动脉壁硬度等指标，这些指标可以进一步了解动脉粥样硬化的发展。第一次，不同的参数从建模和拟议项目的目标是开发一种新的工具动脉粥样硬化风险分层。在西方世界，通过动脉粥样硬化斑块破裂（冠状动脉疾病（CAD）和中风）引起的心血管疾病（CVD）是发病率和死亡率的主要单一原因。血管粥样硬化性疾病是高比例心血管事件的致病因素。目前，广泛接受的可以预测心血管事件（如心肌梗死和中风）的风险标志物是基于吸烟、体重和血压等风险因素。这些生活方式因素和医疗状况源自基于人群的研究，并与发生CV事件的平均概率有关，但不衡量个人的个人风险，因此可能导致潜在的过度治疗。该项目的主要成果将是一种计算工具，用于使用多参数磁共振成像（MRI）评估个体的动脉粥样硬化程度。结合生物物理计算机模型。先进的磁共振成像将用于斑块负荷测量和斑块成分表征，以确定破裂风险和全身动脉粥样硬化负荷。研究小组将使用现有的MRI方法结合新的斑块易损性标记物。这些标志物包括：斑块体积、斑块内出血、脂质含量、钙化、内皮通透性和细胞外体积。此外，生物力学模型将用于预测与血管系统中动脉粥样硬化变化相关的生物力学特性。研究小组将调查和计算壁面剪切应力、颗粒停留时间和动脉壁硬度等指标，这些指标可以进一步了解动脉粥样硬化的发展。这是第一次，来自建模和成像的不同参数将被整合到一个临床工具中，用于在不同评估水平上进行综合和个体风险分层。

项目成果

Aortic length measurements for pulse wave velocity calculation: manual 2D vs automated 3D centreline extraction.

• DOI: 10.1186/s12968-017-0341-y
• 发表时间: 2017-03-08
• 期刊: Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
• 作者: van Engelen A;Silva Vieira M;Rafiq I;Cecelja M;Schneider T;de Bliek H;Figueroa CA;Hussain T;Botnar RM;Alastruey J
• 通讯作者: Alastruey J

Aortic centreline tracking for PWV measurements in multiple MRI sequences

主动脉中心线跟踪，用于多个 MRI 序列中的 PWV 测量

• 发表时间: 2016
• 作者: VanEngelen A

Automatic coronary centerline tracking from coronary MRI

通过冠状动脉 MRI 自动跟踪冠状动脉中心线

• 发表时间: 2016
• 作者: Van Engelen A

Simultaneous [18F]fluoride and gadobutrol enhanced coronary positron emission tomography/magnetic resonance imaging for in vivo plaque characterization.

同时[18F]氟化物和钆布醇增强冠状动脉正电子发射断层扫描/磁共振成像，用于体内斑块表征。

• DOI: 10.1093/ehjci/jeab276
• 发表时间: 2022
• 期刊: European heart journal. Cardiovascular Imaging
• 作者: Wurster TH

Medical Image Understanding and Analysis

医学图像理解与分析

• DOI: 10.1007/978-3-319-60964-5_14
• 发表时间: 2017
• 作者: Van Engelen A