This application brings together two world-renowned research- and educational-focused Universities in a unique collaboration to create an interdisciplinary training approach to meet challenges in healthcare. With complementary strengths in basic physical sciences, engineering and clinical translation, close strategic and geographical links and a CDT embedded within a top-rated teaching hospital, the KCL/ICL alliance is superbly placed to train the next generation of imaging scientists and research leaders. The CDT will provide a unique interdisciplinary training program to develop the skills for creating innovative technical solutions through integration of the physical sciences, engineering and biological and clinical disciplines. The Centre will be integrated into a large research portfolio in medical imaging funded through EPSRC/Wellcome Trust Medical Engineering Centres, MRC centres, the CRUK/EPSRC Cancer Imaging Centres, and the BHF Centres of Excellence. In order to foster clinical translation of research, the CDT will be linked into two Academic Health Science Centres and NIHR-Biomedical Research Centres. The CDT will create a critical mass of teachers and researchers to establish an interdisciplinary training program by bringing together students from different disciplines to work on research topics in medical imaging. The CDT will feature a 1 + 3 years MRes+PhD structure and will manage the students as a single cohort. We have developed the different phases of the PhD programme, i.e. Recruitment, MRes, PhD and Alumni, to achieve the highest quality in training, research and career development for the individual student. We place a strong emphasis on clinical translation, therefore the CDT will continue with a formal training programme in clinical applications in parallel to the PhD projects. In addition, the teaching location of the Centre in a dedicated, newly-refurbished CDT teaching hub within a world-class teaching hospital engenders strong links with the NHS and provides further enhanced opportunities for clinical translation. The first and foremost goal of this CDT will be to provide the highest quality supervision for individual students. To achieve this, we will combine the experience of senior supervisors with the energy and development of more junior academics. At the start of the CDT, we will be defining PhD projects from 60 supervisors with world-leading research expertise in the underpinning of the multidisciplinary themes in medical imaging. All of those scientists have a track record in PhD supervision and delivering research funded by research councils. We have also identified clinical champions in three major disease areas (Cardiology, Oncology, Neuro) who will organize training in clinical application. This training is designed to forge interactions between scientists and clinicians. It will provide students with valuable contacts with whom they can discuss clinical implications of their PhD research. The CDT will provide training of a new generation of scientists with skills in interdisciplinary research, clinical translation and entrepreneurship. The focus of both graduate training and the individual student research projects will be to innovate medical imaging technologies in the care cycle of patients across a range of diseases. Another central theme within the program will be training to translate innovations into commercial products. For this, we will leverage our strong industrial links and have obtained financial commitment for more than 25 co-funded industrial CDT studentships from various industrial partners. The partners, including new UK-based SMEs and start-up companies, will also provide internships to enable career paths into industry.

This programme aims to change the way medical imaging is currently used in applications where quantitative assessment of disease progression or guidance of treatment is required. Imaging technology traditionally sees the reconstructed image as the end goal, but in reality it is a stepping stone to evaluate some aspect of the state of the patient, which we term the target, e.g. the presence, location, extent and characteristics of a particular disease, function of the heart, response to treatment etc. The image is merely an intermediate visualization, for subsequent interpretation and processing either by the human expert or computer based analysis. Our objectives are to extract information which can be used to inform diagnosis and guide therapy directly from the measurements of the imaging device. We propose a new paradigm whereby the extraction of clinically-relevant information drives the entire imaging process. All medical imaging devices measure some physical attribute of the patient's body, such as the X-ray attenuation in CT, changes acoustic impedance in ultrasound, or the mobility of protons in MRI. These physical attributes may be modulated by changes in structure or metabolic function. Medical images from devices such as MR and CT scanners often take 10s of seconds to many minutes to acquire. The unborn child, the very young, the very old or very ill cannot stay still for this time and methods of addressing motion are inefficient and cannot be applied to all types of imaging. Usually triggering and gating strategies are applied, which result in a low acquisition efficiency (since most of the data is rejected) and often fail due to irregular motion. As a result the images are corrupted by significant motion artifact or blurring.Accurate computational modeling of physiology and pathological processes at different spatial scales has shown how careful measurements from imaging devices might allow the clinician or the medical scientist to infer what is happening in health, in specific diseases and during therapy. Unfortunately, making these accurate measurements is very difficult due to the movement artifacts described above. Imaging systems can provide the therapist, interventionist or surgeon with a 3D navigational map showing where therapy should be delivered and measuring how effective it is. Unfortunately image guided interventions in the moving and deforming tissues of the chest and abdomen is very difficult as the images are often corrupted by motion and as the procedure progresses the images generally diverge from the local anatomy that the interventionist or surgeon is treating.Our programme brings together three different groups of people: computer scientists who construct computer models of anatomy, physiology, pharmacological processes and the dynamics of tissue motion; imaging scientists who develop new ways to reconstruct images of the human body; and clinicians working to provide better treatment for their patients. With these three groups working together we will devise new ways to correct for motion artifact, to produce images of optimal quality that are related directly to clinically relevant measures of tissue composition, microscopic structure and metabolism. We will apply these methods to improve understanding of disease progression; guide therapies and assess response to treatment in cancer arising in the lung and liver; to ischaemic heart disease; to the clinical management of the foetus while still in the womb; and to caring for premature babies and young children.

The term "dementia" is used to describe a syndrome that results, initially, in cognitive function impairment and in many cases, a descending staircase of psychological dysfunction, leading eventually to death. It is a major socio-economic challenge with care costs approaching 1% of global GDP. Several conditions that lead to serious loss of cognitive ability are grouped under this syndrome, including Alzheimer's disease (AD), Vascular Dementia (VaD), Frontotemporal Dementia, etc. A high publicity announcement was made in 2012, by the Prime Minister, emphasising the high priority that should be given to dementia-related research and that funding will more than double in the immediate future, to partially remedy the fact that the overwhelming impact of the syndrome has been over-looked (Guardian, 26/3/12). On Dec 2013, the G8 Summit hosted in London brought together G8 ministers, researchers, pharmaceutical companies, and charities to develop co-ordinated global action on dementia. Dementia has marked adverse effects on the quality of life of tens of millions of people (both patients and carers) and exerts tremendous pressure on healthcare systems, especially when clear trends towards an ageing population, changing environmental influences and contemporary lifestyle choices are considered. Ca. 35M people suffer from dementia worldwide, a figure to quadruple by 2050. Europe and North America share a disproportionally high burden: the effects of ageing are particularly stark for these regions, exacerbating the healthcare provision implications. The Clinical Relevance: Vascular Cognitive Impairment (VCI). VCI defines alterations in cognition attributable to cerebrovascular causes, ranging from subtle or fixed deficits to full-blown dementia. VCI is a wide and accepted term referring to the "syndrome with evidence of clinical stroke or subclinical vascular brain injury and cognitive impairment affecting at least one cognitive domain", with resulting VaD being its most severe form. VaD is responsible for at least 20% of dementias, second only to AD, with a prevalence doubling every 5. 3 years. Several trials examined cholinesterase inhibitors for the treatment of vascular dementia, but the benefits are very modest, except in the individuals with a combination of AD and VaD. Vascular changes result in white matter (WM) damage (leukoaraiosis), which profoundly affect the fidelity of the information transfer underlying brain function and cognitive health8. Cerebral Magnetic Resonance Imaging (MRI) of Diffusion and Perfusion. MRI is a medical imaging technique affording non-invasive investigation of anatomy and tissue function, which is particularly suited to studying cognitive disorders due to its sensitivity and reliability. Our main interest is to characterise vascular and non-vascular tissues using quantitative diffusion and perfusion MR. Our overall aim is to characterise and quantify early differential alterations in brain blood transport and subsequent microstructural tissue damage using one-stop-shop perfusion/diffusion MR GSI incorporating novel MR signal models and optimal MR sequence design based on new human brain histomorphometric data in health and disease.

The term "dementia" is used to describe a syndrome that results, initially, in cognitive function impairment and in many cases, a descending staircase of psychological dysfunction, leading eventually to death. It is a major socio-economic challenge with care costs approaching 1% of global GDP. Several conditions that lead to serious loss of cognitive ability are grouped under this syndrome, including Alzheimer's disease (AD), Vascular Dementia (VaD), Frontotemporal Dementia, etc. A high publicity announcement was made in 2012, by the Prime Minister, emphasising the high priority that should be given to dementia-related research and that funding will more than double in the immediate future, to partially remedy the fact that the overwhelming impact of the syndrome has been over-looked (Guardian, 26/3/12). On Dec 2013, the G8 Summit hosted in London brought together G8 ministers, researchers, pharmaceutical companies, and charities to develop co-ordinated global action on dementia. Dementia has marked adverse effects on the quality of life of tens of millions of people (both patients and carers) and exerts tremendous pressure on healthcare systems, especially when clear trends towards an ageing population, changing environmental influences and contemporary lifestyle choices are considered. Ca. 35M people suffer from dementia worldwide, a figure to quadruple by 2050. Europe and North America share a disproportionally high burden: the effects of ageing are particularly stark for these regions, exacerbating the healthcare provision implications. The Clinical Relevance: Vascular Cognitive Impairment (VCI). VCI defines alterations in cognition attributable to cerebrovascular causes, ranging from subtle or fixed deficits to full-blown dementia. VCI is a wide and accepted term referring to the "syndrome with evidence of clinical stroke or subclinical vascular brain injury and cognitive impairment affecting at least one cognitive domain", with resulting VaD being its most severe form. VaD is responsible for at least 20% of dementias, second only to AD, with a prevalence doubling every 5. 3 years. Several trials examined cholinesterase inhibitors for the treatment of vascular dementia, but the benefits are very modest, except in the individuals with a combination of AD and VaD. Vascular changes result in white matter (WM) damage (leukoaraiosis), which profoundly affect the fidelity of the information transfer underlying brain function and cognitive health8. Cerebral Magnetic Resonance Imaging (MRI) of Diffusion and Perfusion. MRI is a medical imaging technique affording non-invasive investigation of anatomy and tissue function, which is particularly suited to studying cognitive disorders due to its sensitivity and reliability. Our main interest is to characterise vascular and non-vascular tissues using quantitative diffusion and perfusion MR. Our overall aim is to characterise and quantify early differential alterations in brain blood transport and subsequent microstructural tissue damage using one-stop-shop perfusion/diffusion MR GSI incorporating novel MR signal models and optimal MR sequence design based on new human brain histomorphometric data in health and disease.

Medical imaging has transformed clinical medicine in the last 40 years. Diagnostic imaging provides the means to probe the structure and function of the human body without having to cut open the body to see disease or injury. Imaging is sensitive to changes associated with the early stages of cancer allowing detection of disease at a sufficient early stage to have a major impact on long-term survival. Combining imaging with therapy delivery and surgery enables 3D imaging to be used for guidance, i.e. minimising harm to surrounding tissue and increasing the likelihood of a successful outcome. The UK has consistently been at the forefront of many of these developments. Despite these advances we still do not know the most basic mechanisms and aetiology of many of the most disabling and dangerous diseases. Cancer survival remains stubbornly low for many of the most common cancers such as lung, head and neck, liver, pancreas. Some of the most distressing neurological disorders such as the dementias, multiple sclerosis, epilepsy and some of the more common brain cancers, still have woefully poor long term cure rates. Imaging is the primary means of diagnosis and for studying disease progression and response to treatment. To fully achieve its potential imaging needs to be coupled with computational modelling of biological function and its relationship to tissue structure at multiple scales. The advent of powerful computing has opened up exciting opportunities to better understand disease initiation and progression and to guide and assess the effectiveness of therapies. Meanwhile novel imaging methods, such as photoacoustics, and combinations of technologies such as simultaneous PET and MRI, have created entirely new ways of looking at healthy function and disturbances to normal function associated with early and late disease progression. It is becoming increasingly clear that a multi-parameter, multi-scale and multi-sensor approach combining advanced sensor design with advanced computational methods in image formation and biological systems modelling is the way forward. The EPSRC Centre for Doctoral Training in Medical Imaging will provide comprehensive and integrative doctoral training in imaging sciences and methods. The programme has a strong focus on new image acquisition technologies, novel data analysis methods and integration with computational modelling. This will be a 4-year PhD programme designed to prepare students for successful careers in academia, industry and the healthcare sector. It comprises an MRes year in which the student will gain core competencies in this rapidly developing field, plus the skills to innovate both with imaging devices and with computational methods. During the PhD (years 2 to 4) the student will undertake an in-depth study of an aspect of medical imaging and its application to healthcare and will seek innovative solutions to challenging problems. Most projects will be strongly multi-disciplinary with a principle supervisor being a computer scientist, physicist, mathematician or engineer, a second supervisor from a clinical or life science background, and an industrial supervisor when required. Each project will lie in the EPSRC's remit. The Centre will comprise 72 students at its peak after 4 years and will be obtaining dedicated space and facilities. The participating departments are strongly supportive of this initiative and will encourage new academic appointees to actively participate in its delivery. The Centre will fill a significant skills gap that has been identified and our graduates will have a major impact in academic research in his area, industrial developments including attracting inward investment and driving forward start-ups, and in advocacy of this important and expanding area of medical engineering.