Atherosclerosis stratification using advanced imaging and computer-based models

该项目的目标是开发一种新的动脉粥样硬化风险分层工具。心血管疾病（CVD）通过动脉粥样硬化斑块破裂（冠状动脉疾病（CAD）和中风）是发病率和死亡率的主要单一原因在西方世界。血管粥样硬化性疾病是导致心血管疾病高发的一个因素。目前，广泛接受的用于预测心血管事件（如心肌梗死和中风）的风险标记是基于吸烟、体重和血压等风险因素。这些生活方式因素和医疗条件来源于基于人群的研究，与心血管事件的平均概率有关，但不能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个计算工具，利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动脉粥样硬化的等级。先进的磁共振成像将用于斑块负担测量和斑块成分表征，以确定破裂风险和系统性动脉粥样硬化负担。该团队将使用现有的mri方法与新的斑块易感性标志物相结合。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，生物物理模型将用于预测与血管系统动脉粥样硬化变化相关的生物力学特性。该团队将研究和计算诸如壁剪切应力，颗粒停留时间和动脉壁刚度等标记，这些标记可以进一步了解动脉粥样硬化的发展。这是第一次，不同的参数从建模和提出的项目的目标是开发一种新的工具动脉粥样硬化风险分层。心血管疾病（CVD）通过动脉粥样硬化斑块破裂（冠状动脉疾病（CAD）和中风）是发病率和死亡率的主要单一原因在西方世界。血管粥样硬化性疾病是导致心血管疾病高发的一个因素。目前，广泛接受的用于预测心血管事件（如心肌梗死和中风）的风险标记是基于吸烟、体重和血压等风险因素。这些生活方式因素和医疗条件来源于基于人群的研究，与心血管事件的平均概率有关，但不能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个计算工具，利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动脉粥样硬化的等级。先进的磁共振成像将用于斑块负担测量和斑块成分表征，以确定破裂风险和系统性动脉粥样硬化负担。该团队将使用现有的mri方法与新的斑块易感性标志物相结合。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，生物物理模型将用于预测与血管系统动脉粥样硬化变化相关的生物力学特性。该团队将研究和计算诸如壁剪切应力，颗粒停留时间和动脉壁刚度等标记，这些标记可以进一步了解动脉粥样硬化的发展。这是第一次，不同的参数从建模和提出的项目的目标是开发一种新的工具动脉粥样硬化风险分层。心血管疾病（CVD）通过动脉粥样硬化斑块破裂（冠状动脉疾病（CAD）和中风）是发病率和死亡率的主要单一原因在西方世界。血管粥样硬化性疾病是导致心血管疾病高发的一个因素。目前，广泛接受的用于预测心血管事件（如心肌梗死和中风）的风险标记是基于吸烟、体重和血压等风险因素。这些生活方式因素和医疗条件来源于基于人群的研究，与心血管事件的平均概率有关，但不能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个计算工具，利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动脉粥样硬化的等级。先进的磁共振成像将用于斑块负担测量和斑块成分表征，以确定破裂风险和系统性动脉粥样硬化负担。该团队将使用现有的mri方法与新的斑块易感性标志物相结合。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，生物物理模型将用于预测与血管系统动脉粥样硬化变化相关的生物力学特性。该团队将研究和计算诸如壁剪切应力，颗粒停留时间和动脉壁刚度等标记，这些标记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，在不同的评估水平上进行全面和个人的风险分层。

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.