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Prof Miguel Bernabeu
Dr T MacGillivray
No more applications being accepted
Funded PhD Project (European/UK Students Only)
About the Project
Background
Diabetic retinopathy (DR) is the leading cause of visual loss in developed countries worldwide. Previous studies have reported haemodynamic changes in the diabetic eye that precede clinically evident pathological alterations of the retinal microvasculature. Therefore, new methods that allow greater understanding of these early haemodynamic changes may empower earlier detection of DR helping to limit vision loss.
Optical Coherence Tomography Angiography (OCT-A) [1] is a non-invasive technique for retinal imaging. OCT-A can resolve the microvasculature of the eye to a level of detail never seen before. Only very recently, OCT-A commercial products have started to be utilised in clinical centres. One of the first OCT-A devices installed in the UK is hosted in Edinburgh at the Clinical Research Imaging Centre (CRIC). CRIC’s Image Analysis Laboratory Manager, Dr MacGillivray, is one of the co-supervisors of this project and works closely with a team at Queen’s University in Belfast, where a second OCT-A device is hosted. Furthermore, co-supervisors Prof. Dhillon and Dr MacGillivray have over 12 years’ experience developing a successful research programme around retinal image analysis and are behind the software package VAMPIRE used in research centres worldwide [2].
In recent work [3], co-supervisor Dr Bernabeu and colleagues showed that it is possible to build computational blood flow models from high-resolution images of the parafoveal region of the retina (of paramount importance for sharp central vision and visual detail). These computational models can provide a detailed haemodynamic characterisation of the region. This will enable us to run longitudinal studies featuring patients with diabetes and identify flow- based early indicators of the structural changes that lead to visual loss in advanced DR stages. We now have a unique opportunity to combine this technology with the OCT-A datasets at Edinburgh and Belfast and the VAMPIRE toolkit in order to realise the full potential of this patient-specific modelling approach to achieving Precision Medicine for eye care.
The supervisory team brings together a unique set of skills in order to lead a programme of research of high calibre: Prof. Andrew Morris (Health Informatics, Data Science), Dr Miguel O. Bernabeu (computational modelling in Biology and Medicine), Dr Tom MacGillivray (multimodal image acquisition and retinal image processing), and Prof. Baljean Dhillon (Clinical Ophthalmology and Brain Sciences).
Aims
In this project, the student will bring together cutting edge image processing and computational modelling methods in order to characterise the early changes in microvascular haemodynamics associated with DR. The project will take advantage of the new OCT-A datasets in Edinburgh and Belfast, which are world-leading. The main objective is to investigate clinically relevant diabetic retinopathy biomarkers and design the computational pipelines necessary to facilitate their use in future large-scale clinical studies.
Training outcomes
The student will receive state-of-the-art training in the core disciplines of image analysis, computational modelling, statistical methods, and data science while gaining expert knowledge in the context of diabetic retinopathy. The student will develop the essential soft and domain-specific skills necessary to design and implement novel quantitative and computational methods that could solve challenging problems across the entire spectrum of vascular medicine both in academic and industrial settings.
Application
This MRC DTP programme is joint between the Universities of Edinburgh and Glasgow. You will be registered at the host institution of the primary supervisor detailed in your project selection.
You can apply here via the University of Glasgow: http://www.gla.ac.uk/research/opportunities/howtoapplyforaresearchdegree/
Within the application, at the programme of study search field option, please select ‘MRC DTP in Precision Medicine’.
Please note that, in step 6 within the online application process, you are asked to detail supervisor/project title information. Please ensure that you clearly detail this information from the information provided within this abstract advert. Within the research area text box area, you can also add further details if necessary.
Please ensure that all of the following supporting documents are uploaded at point of application:
• CV/Resume
• Degree certificate (if you have graduated prior to 1 July 2016)
• Language test (if relevant)
• Passport
• Personal statement
• Reference 1 (should be from an academic who has a knowledge of your academic ability from your most recent study/programme)
• Reference 2 (should be from an academic who has a knowledge of your academic ability)
• Transcript
For more information about Precision Medicine at the University of Edinburgh, visit http://www.ed.ac.uk/medicine-vet-medicine/postgraduate/research-degrees/phds/precision-medicine
Diabetic retinopathy (DR) is the leading cause of visual loss in developed countries worldwide. Previous studies have reported haemodynamic changes in the diabetic eye that precede clinically evident pathological alterations of the retinal microvasculature. Therefore, new methods that allow greater understanding of these early haemodynamic changes may empower earlier detection of DR helping to limit vision loss.
Optical Coherence Tomography Angiography (OCT-A) [1] is a non-invasive technique for retinal imaging. OCT-A can resolve the microvasculature of the eye to a level of detail never seen before. Only very recently, OCT-A commercial products have started to be utilised in clinical centres. One of the first OCT-A devices installed in the UK is hosted in Edinburgh at the Clinical Research Imaging Centre (CRIC). CRIC’s Image Analysis Laboratory Manager, Dr MacGillivray, is one of the co-supervisors of this project and works closely with a team at Queen’s University in Belfast, where a second OCT-A device is hosted. Furthermore, co-supervisors Prof. Dhillon and Dr MacGillivray have over 12 years’ experience developing a successful research programme around retinal image analysis and are behind the software package VAMPIRE used in research centres worldwide [2].
In recent work [3], co-supervisor Dr Bernabeu and colleagues showed that it is possible to build computational blood flow models from high-resolution images of the parafoveal region of the retina (of paramount importance for sharp central vision and visual detail). These computational models can provide a detailed haemodynamic characterisation of the region. This will enable us to run longitudinal studies featuring patients with diabetes and identify flow- based early indicators of the structural changes that lead to visual loss in advanced DR stages. We now have a unique opportunity to combine this technology with the OCT-A datasets at Edinburgh and Belfast and the VAMPIRE toolkit in order to realise the full potential of this patient-specific modelling approach to achieving Precision Medicine for eye care.
The supervisory team brings together a unique set of skills in order to lead a programme of research of high calibre: Prof. Andrew Morris (Health Informatics, Data Science), Dr Miguel O. Bernabeu (computational modelling in Biology and Medicine), Dr Tom MacGillivray (multimodal image acquisition and retinal image processing), and Prof. Baljean Dhillon (Clinical Ophthalmology and Brain Sciences).
Aims
In this project, the student will bring together cutting edge image processing and computational modelling methods in order to characterise the early changes in microvascular haemodynamics associated with DR. The project will take advantage of the new OCT-A datasets in Edinburgh and Belfast, which are world-leading. The main objective is to investigate clinically relevant diabetic retinopathy biomarkers and design the computational pipelines necessary to facilitate their use in future large-scale clinical studies.
Training outcomes
The student will receive state-of-the-art training in the core disciplines of image analysis, computational modelling, statistical methods, and data science while gaining expert knowledge in the context of diabetic retinopathy. The student will develop the essential soft and domain-specific skills necessary to design and implement novel quantitative and computational methods that could solve challenging problems across the entire spectrum of vascular medicine both in academic and industrial settings.
Application
This MRC DTP programme is joint between the Universities of Edinburgh and Glasgow. You will be registered at the host institution of the primary supervisor detailed in your project selection.
You can apply here via the University of Glasgow: http://www.gla.ac.uk/research/opportunities/howtoapplyforaresearchdegree/
Within the application, at the programme of study search field option, please select ‘MRC DTP in Precision Medicine’.
Please note that, in step 6 within the online application process, you are asked to detail supervisor/project title information. Please ensure that you clearly detail this information from the information provided within this abstract advert. Within the research area text box area, you can also add further details if necessary.
Please ensure that all of the following supporting documents are uploaded at point of application:
• CV/Resume
• Degree certificate (if you have graduated prior to 1 July 2016)
• Language test (if relevant)
• Passport
• Personal statement
• Reference 1 (should be from an academic who has a knowledge of your academic ability from your most recent study/programme)
• Reference 2 (should be from an academic who has a knowledge of your academic ability)
• Transcript
For more information about Precision Medicine at the University of Edinburgh, visit http://www.ed.ac.uk/medicine-vet-medicine/postgraduate/research-degrees/phds/precision-medicine
Funding Notes
Start date:
September/October 2016
Qualifications criteria:
Applicants applying for a MRC DTP in Precision Medicine studentship must have obtained, or soon will obtain, a first or upper-second class UK honours degree or equivalent non-UK qualifications, in an appropriate science/technology area.
Residence criteria:
The MRC DTP in Precision Medicine grant provides tuition fees and stipend of £14,296 (RCUK rate 2016/17) for UK and *EU nationals that meet all required eligibility criteria.
(*must have been resident in the UK for three years prior to commencing studentship)
Full qualifications and residence eligibility details are available here: http://www.mrc.ac.uk/skills-careers/studentships/studentship-guidance/student-eligibility-requirements/
General enquiries regarding programme/application procedure: [Email Address Removed]
September/October 2016
Qualifications criteria:
Applicants applying for a MRC DTP in Precision Medicine studentship must have obtained, or soon will obtain, a first or upper-second class UK honours degree or equivalent non-UK qualifications, in an appropriate science/technology area.
Residence criteria:
The MRC DTP in Precision Medicine grant provides tuition fees and stipend of £14,296 (RCUK rate 2016/17) for UK and *EU nationals that meet all required eligibility criteria.
(*must have been resident in the UK for three years prior to commencing studentship)
Full qualifications and residence eligibility details are available here: http://www.mrc.ac.uk/skills-careers/studentships/studentship-guidance/student-eligibility-requirements/
General enquiries regarding programme/application procedure: [Email Address Removed]
References
[1] de Carlo et al. “A review of optical coherence tomography angiography (OCTA)”
International Journal of Retina and Vitreous 2015 1:5. DOI:10.1186/s40942-015-0005-8
[2] E. Trucco, A. Giachetti, L. Ballerini, D. Relan, A. Cavinato, T. MacGillivray, Morphometric Measurements of the Retinal Vasculature in Fundus Images with VAMPIRE, in Biomedical Image Understanding: Methods and Applications, J. Lim, S. Ong, W. Xiong, Eds., John Wiley & Sons, 2015. DOI:10.1002/9781118715321.ch3
[3] Bernabeu et al. “Characterization of parafoveal hemodynamics associated with diabetic retinopathy with adaptive optics scanning laser ophthalmoscopy and computational fluid dynamics” in Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE, pp.8070-8073, 25-29 Aug. 2015. DOI:10.1109/EMBC.2015.7320266
International Journal of Retina and Vitreous 2015 1:5. DOI:10.1186/s40942-015-0005-8
[2] E. Trucco, A. Giachetti, L. Ballerini, D. Relan, A. Cavinato, T. MacGillivray, Morphometric Measurements of the Retinal Vasculature in Fundus Images with VAMPIRE, in Biomedical Image Understanding: Methods and Applications, J. Lim, S. Ong, W. Xiong, Eds., John Wiley & Sons, 2015. DOI:10.1002/9781118715321.ch3
[3] Bernabeu et al. “Characterization of parafoveal hemodynamics associated with diabetic retinopathy with adaptive optics scanning laser ophthalmoscopy and computational fluid dynamics” in Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE, pp.8070-8073, 25-29 Aug. 2015. DOI:10.1109/EMBC.2015.7320266
Project supervisors
Career overview
Miguel O. Bernabeu completed a D.Phil. in Computational Biology at the University of Oxford in 2011, focusing on the development of computational methods for simulating ventricular cardiac electrophysiology. This work laid the foundation for multiple subsequent Ph.D. projects and was crucial to the success of the EU-FP7 grant VPH-preDiCT, which involved collaboration with pharmaceutical companies to integrate mathematical modelling into drug cardiotoxicity research. His research was presented at the Heart Rhythm 2011 conference, a significant event in cardiac science. In 2011, Bernabeu joined the Centre for Mathematics and Physics in the Life Sciences and Experimental Biology (CoMPLEX) at University College London, where he investigated the relationship between haemodynamics and vascular remodelling using both computational and experimental methods. His contributions were featured in the New Scientist magazine and published in various journals and conferences. During this period, he recognised the necessity of combining experimental and computational techniques to tackle critical questions regarding blood vessel responses to flow conditions. In 2015, Bernabeu was appointed to The University of Edinburgh as a Chancellor’s Fellow, establishing his first research group at the Centre for Medical Informatics, Usher Institute. He was promoted to Senior Lecturer in 2019. His research group has received funding from several prestigious organisations, including Fondation Leducq, the European Commission, EPSRC, MRC, the British Heart Foundation, The Alan Turing Institute, and Diabetes UK. In May 2021, Bernabeu became the Deputy Director of The Bayes Centre, the university's innovation hub for Data Science and Artificial Intelligence, where he oversees research strategy and delivery as Director of Research.
Research interests
Miguel O. Bernabeu's research focuses on vascular structure and function, particularly the relationship between abnormal vascularisation and various diseases such as myocardial infarction, stroke, and tumourigenesis. Their work aims to advance the understanding of vascular biology and biotransport, translating findings into next-generation vascular normalisation therapies. Specific research interests include the development of automated methods for diagnosing eye and systemic diseases through retinal scans, studying the tumour microvascular environment's impact on treatment, and investigating vascular remodelling during angiogenesis. The approach combines theoretical mathematical modelling and machine learning, in collaboration with vascular and cancer biologists and clinicians.
Computational Medicine
Computational Biology
Cardiac Electrophysiology
Mathematical Modelling
Vascular Biology
Biotransport
Vascularisation
Angiogenesis
Machine Learning
Biomedical Imaging
Retinal Scans
Tumour Microvascular Environment
Vascular Remodelling
Drug Cardiotoxicity
Haemodynamics
Clinical Research
Automated Diagnosis
Research Strategy
Data Science
Artificial Intelligence
Career overview
Dr. Tom MacGillivray specialises in image processing and analysis for clinical research. They manage the Image Analysis Core laboratory at the Edinburgh Clinical Research Facility and oversee the Retinal Imaging facilities for the Edinburgh Imaging group. The laboratory provides expert support for investigators analysing data from various imaging modalities, including MR, CT, PET, ultrasound, and retinal imaging. Dr. MacGillivray has extensive experience in facilitating research involving retinal imaging, contributing to studies on stroke, cardiovascular disease, multiple sclerosis, and dementia. They coordinate the interdisciplinary initiative VAMPIRE (Vascular Assessment and Measurement Platform for Images of the Retina), aimed at developing efficient, semi-automatic analysis of different types of retinal images and ophthalmic data. Dr. MacGillivray holds a Bachelor of Science, a Master of Science by Research, and a Doctor of Philosophy (PhD) from the University of Edinburgh, as well as a Postgraduate Diploma in Academic Practice.
Research interests
Dr. MacGillivray's research focuses on image processing and analysis for clinical research, particularly in the context of retinal imaging. They have extensive experience in facilitating research related to stroke, cardiovascular disease, multiple sclerosis, and dementia. Current research interests include the development of novel image processing algorithms for medical imaging, multi-modal retinal scanning techniques, and the identification of retinal imaging-derived biomarkers for neurodegeneration and systemic diseases. Dr. MacGillivray is also engaged in industry collaborations to enhance the acquisition and application of retinal imaging data. They coordinate the VAMPIRE project, which aims to develop efficient, semi-automatic analysis of various types of retinal images and ophthalmic data.
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