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.

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.

Medicine is undergoing a simultaneous shift at the levels of the individual and the population: we have unprecedented tools for precision monitoring and intervention in individual health and we also have high-resolution behavioural and social data. Precision medicine seeks to deploy therapies that are sensitive to the particular genetic, lifestyle and environmental circumstances of each patient: understanding how best to use these numerous features about each patient is a profound mathematical challenge. We propose to build upon the mathematical, computational and biomedical strengths at Imperial to create a Centre for the Mathematics of Precision Healthcare revolving around the theme of multiscale networks for data-rich precision healthcare and public health. Our Centre proposes to use mathematics to unify individual-level precision medicine with public health by placing high-dimensional individual data and refined interventions in their social network context. Individual health cannot be separated from its behavioural and social context; for instance, highly targeted interventions against a cancer can be undermined by metabolic diseases caused by a dietary behaviour which co-varies with social network structure. Whether we want to tackle chronic disease or the diseases of later life, we must simultaneously consider the joint substrates of the individual together with their social network for transmission of behaviour and disease. We propose to tackle the associated mathematical challenges under the proposed Centre bringing to bear particular strengths of Imperial's mathematical research in networks and dynamics, stochastic processes and analysis, control and optimisation, inference and data representation, to the formulation and analysis of mathematical questions at the interface of individual-level personalised medicine and public health, and specifically to the data-rich characterisation of disease progression and transmission, controlled intervention and healthcare provision, placing precision interventions in their wider context. The programme will be initiated and sustained on core research projects and will expand its portfolio of themes and researchers through open calls for co-funded projects and pump-priming initiatives. Our initial set of projects will engage healthcare and clinical resources at Imperial including: (i) patient journeys for disease states in cancer and their successive hospital admissions; multi-omics data and imaging characterisations of (ii) cardiomyopathies and (iii) dementia and co-morbidities; (iv) national population dynamics for epidemiological and epidemics simulation data from Public Health; social networks and (v) health beliefs and (vi) health policy debate. The initial core projects will build upon embedded computational capabilities and data expertise, and will thus concentrate on the development of mathematical methodologies including: sparse state-space methods for the characterisation of disease progression in high-dimensional data using transition graphs in discrete spaces; time-varying networks and control for epidemics data; geometrical similarity graphs to link imaging and omics data for disease progression; stochastic processes and community detection from NHS patient data wedding behavioural and social network data with personal health indicators; statistical learning for the analysis of stratified medicine. The mathematical techniques used to address these requirements will need to combine, among others, ingredients from dynamical and stochastic systems with graph-theoretical notions, sparse statistical learning, inference and optimisation. The Centre will be led by Mathematics but researchers in the Centre span mathematical, biomedical, clinical and computational expertise.

DPUK is a public-private partnership to accelerate the development of new treatments for dementia. Since inception (2014) DPUK has increased the UK capacity for dementia research through infrastructure development and strategic data collection, leveraging a further £74.4m for dementia research. The second phase of DPUK (DPUK2) focuses on developing UK capacity for dementia experimental medicine. A major challenge in developing new treatments is understanding the mechanisms through which a drug might operate. This involves precision studies where individuals of known vulnerability to specific causes of dementia are recruited to studies of cause-specific mechanistic pathways. These studies are very difficult to do as they require detailed assessment of volunteers before the study begins and standardising all the procedures in centres across the UK. These studies are also high risk in that there is no guarantee of success. DPUK2 addresses these issues head-on at two levels. First it uses the UK's rich legacy in population cohort studies to identify suitable volunteers by using and enhancing existing cohort data. Second it creates a pre-competitive environment that brings together industry, academic and third-sector entities into partnership. This not only shares the costs and risks of experimental medicine (EM) studies, it also shares the benefits amongst a wider spread of stakeholders, each able to exploit the findings. DPUK2 does this through 3 inter-dependent work-streams. 1. The Data Portal (DP): The DP is a world leading end-to-end dementia focused data management solution. It enables large and complex datasets to be accessed remotely from around the globe without compromising data security. The DP is being developed in partnership with Health Data Research UK (HDR UK) so that we can maximise the data available to dementia research. The DP is used to manage all the data and information systems necessary for conducting precision studies. It brings large and complex datasets together in order to test new ideas; it manages personal information securely to enable recruitment to precision studies; it manages many types of data so that genetics, brain imaging, cognitive performance; and questionnaire data can all be analysed together. 2. The Trials Delivery Framework (TDF): The TDF is the vehicle that enables the DPUK2 experimental medicine programme to be efficient. The TDF organises our Clinical Studies Register (CSR) through which cohort members can volunteer for experimental medicine studies. The CSR allows us to contact members to enrich their data in terms of background information, cognitive testing, and where necessary genetics. As part of the CSR, and in partnership with the Alzheimer's Society, we have a PPI programme to understand what best practice is in terms if recruitment to experimental medicine studies. The TDF also enables us to identify centres of excellence across the UK for conducting experimental studies rigorously. This not only assures data quality, but also means that volunteers do not have to travel too far to participate. 3. The EM Incubator: The incubator is where our partners meet to plan and execute the experimental medicine programme. It has three themes; the first is Vascular Health. This is important because so many factors that affect the heart also affect the brain. If any area is likely to have drugs that already exist and could be re-purposed for dementia, this is it.The second theme is Synaptic Health. Here we investigate factors that affect the loss of neuron synapses. This is important because unlike neurons, synapses (the connections between neurons), can be generated, which is critical to learning and maintaining memory. The third area is Neuroimmunology. This is important as inflammation is a systemic problem that is known to affect the brain and might have systemic solutions, and so represents a promising area for new treatments.

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.