Atherosclerosis stratification using advanced imaging and computer-based models

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 of
morbidity and mortality in the Western world. Vascular atherosclerotic disease is a causative factor in a high percentage of
CVD events. Widely accepted risk markers that allow predicting cardiovascular events such as myocardial infarction and
stroke are currently based on risk factors such as smoking, weight and blood pressure. These lifestyle factors and medical
conditions are derived from population based studies and are linked to an average probability of having a CV event, but do
not 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 individual
person 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 component
characterization in order to identify the risk of rupture and the systemic atherosclerosis burden. The team will use exiting
MRI methods in combination with novel markers of plaque vulnerability. These markers include: plaque volume, intraplaque
haemorrhage, lipid content, calcification, endothelial permeability and extracellular volume. In addition, biophysical
models will be used to predict biomechanical properties related to atherosclerotic changes in the vascular system. The
team 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 of
morbidity and mortality in the Western world. Vascular atherosclerotic disease is a causative factor in a high percentage of
CVD events. Widely accepted risk markers that allow predicting cardiovascular events such as myocardial infarction and
stroke are currently based on risk factors such as smoking, weight and blood pressure. These lifestyle factors and medical
conditions are derived from population based studies and are linked to an average probability of having a CV event, but do
not 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 individual
person 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 component
characterization in order to identify the risk of rupture and the systemic atherosclerosis burden. The team will use exiting
MRI methods in combination with novel markers of plaque vulnerability. These markers include: plaque volume, intraplaque
haemorrhage, lipid content, calcification, endothelial permeability and extracellular volume. In addition, biophysical
models will be used to predict biomechanical properties related to atherosclerotic changes in the vascular system. The
team 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 of
morbidity and mortality in the Western world. Vascular atherosclerotic disease is a causative factor in a high percentage of
CVD events. Widely accepted risk markers that allow predicting cardiovascular events such as myocardial infarction and
stroke are currently based on risk factors such as smoking, weight and blood pressure. These lifestyle factors and medical
conditions are derived from population based studies and are linked to an average probability of having a CV event, but do
not 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 individual
person 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 component
characterization in order to identify the risk of rupture and the systemic atherosclerosis burden. The team will use exiting
MRI methods in combination with novel markers of plaque vulnerability. These markers include: plaque volume, intraplaque
haemorrhage, lipid content, calcification, endothelial permeability and extracellular volume. In addition, biophysical
models will be used to predict biomechanical properties related to atherosclerotic changes in the vascular system. The
team 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 assessment
levels.

From a societal and from the individual perspective cardiovascular disease (CVD) is the leading public health problem in
the US, in Europe and in the UK. In particular, CVD caused 40% of all deaths in the United Kingdom in 2002 with an overall
CVD cost to the EU economy of almost £166 billion and the US economy $297.7 billion per year. In the UK, the socioeconomic
costs have been estimated to be £29.1 billion in 2004. Since 1990, the number of prescriptions for antiplatelet
drugs for atherosclerosis treatment has increased steadily to over 38 million prescriptions in England every year. The
number of prescriptions for lipid lowering drugs is more than fifteen times higher than a decade ago. In 2011
antihypertensive drugs were the most prescribed drugs for CVD in England, Scotland and Wales. The cost of prescriptions
for hypertension and heart failure therapy totalled to just over £330 million between 2010 and 2011. Better imaging based
atherosclerosis risk stratification could result in a better personalized understanding of risk, and in significant cost
reductions due to the avoidance of unnecessary prescriptions. Patients would directly benefit from an individually stratified
treatment strategy allowing optimal selection for surveillance, medical or surgical treatment.
The benefit to the UK economy beyond healthcare economics will be twofold. Firstly, the project will employ additional staff
in the UK through the academic partner. Philips staff will be working on the project based in the UK, contributing to tax
income. Secondly, revenue streams are expected to Philips UK companies leading to taxable profits. Philips has a strong
presence in the UK healthcare sector and additional sales of a newly developed package as described in this project will
lead to an increase in the profits of Philips UK business. Licensing of IP generated during the project from KCL to Philips
will generate additional revenue streams for KCL. Philips and KCL collaborate in the framework of a hub strategy which
integrates industrial software development with academic research centres on-site for short clinical feedback loops. The
proposed project strengthens the KCL imaging research hub and attracts R&D investment of a global company to the UK.
The joint spin-off company that could be founded as UK LC after successful completion of the project would generate
revenues on a case-based business model (see appendix A of the application for details). Revenues from sales of
technology developed during the project are expected already immediately after completion of the project on a small scale
by targeting research customers. The full business potential including a reimbursement scenario can be leveraged
following successful outcome trials subsequent to this project. We will establish a link with the King's Imaging Technology
Evaluation Centre (KITEC), which supports the work of the Medical Technologies Evaluation Programme (MTEP) and the
Diagnostic Assessment Programme (DAP) of the National Institute for Health and Care Excellence (NICE). Projects
undertaken by KITEC include randomized controlled trials, systematic reviews, establishment of registers and databases.
The scientific methodology results from this research will be output as research publications in high-impact journals in the
field of medical imaging. Target journals will include Circulation, Journal of the American College of Cardiology, Magnetic
Resonance in Medicine and Journal of Cardiovascular MR. Dissemination will also take place through presentations at the
major international conferences, especially the American Heart Association, the International Society for Magnetic
Resonance in Medicine (ISMRM) and The Society for Cardiovascular Magnetic Resonance (SCMR).