Atherosclerosis stratification using advanced imaging and computer-based models

拟议项目的目标是开发一种用于动脉粥样硬化风险分层的新工具。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)是西方世界发病率和死亡率的主要原因。血管动脉粥样硬化性疾病是高比例心血管事件的致病因素。目前，被广泛接受的能够预测心肌梗死和中风等心血管事件的风险标记物是基于吸烟、体重和血压等危险因素。这些生活方式因素和医疗条件来自基于人群的研究，与发生心血管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，使用多参数磁共振成像(MRI)结合生物物理计算机模型来评估个人的动脉粥样硬化级别。先进的磁共振成像将用于斑块负担测量和斑块成分表征，以确定破裂的风险和全身动脉粥样硬化负担。该团队将使用现有的核磁共振方法，结合斑块脆弱性的新标记。这些指标包括：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，生物物理模型将被用来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。该项目将调查和计算壁切应力、颗粒滞留时间和动脉壁硬度等指标，这些指标可以进一步深入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的项目的目标是开发一种新的工具，动脉粥样硬化的风险分层。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)是西方世界发病率和死亡率的主要原因。血管动脉粥样硬化性疾病是高比例心血管事件的致病因素。目前，被广泛接受的能够预测心肌梗死和中风等心血管事件的风险标记物是基于吸烟、体重和血压等危险因素。这些生活方式因素和医疗条件来自基于人群的研究，与发生心血管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，使用多参数磁共振成像(MRI)结合生物物理计算机模型来评估个人的动脉粥样硬化级别。先进的磁共振成像将用于斑块负担测量和斑块成分表征，以确定破裂的风险和全身动脉粥样硬化负担。该团队将使用现有的核磁共振方法，结合斑块脆弱性的新标记。这些指标包括：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，生物物理模型将被用来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。该项目将调查和计算壁切应力、颗粒滞留时间和动脉壁硬度等指标，这些指标可以进一步深入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的项目的目标是开发一种新的工具，动脉粥样硬化的风险分层。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)是西方世界发病率和死亡率的主要原因。血管动脉粥样硬化性疾病是高比例心血管事件的致病因素。目前，被广泛接受的能够预测心肌梗死和中风等心血管事件的风险标记物是基于吸烟、体重和血压等危险因素。这些生活方式因素和医疗条件来自基于人群的研究，与发生心血管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，使用多参数磁共振成像(MRI)结合生物物理计算机模型来评估个人的动脉粥样硬化级别。先进的磁共振成像将用于斑块负担测量和斑块成分表征，以确定破裂的风险和全身动脉粥样硬化负担。该团队将使用现有的核磁共振方法，结合斑块脆弱性的新标记。这些指标包括：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，生物物理模型将被用来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。该项目将调查和计算壁切应力、颗粒滞留时间和动脉壁硬度等指标，这些指标可以进一步深入了解动脉粥样硬化的发展。首次将来自建模和成像的不同参数集成到一个临床工具中，用于在不同评估级别上进行全面和个别的风险分层。

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.