Professor Alicja Rudnicka is a Professor in Statistical Epidemiology in the Population Health Research Institute. Professor Rudnicka has been involved in a wide spectrum of epidemiological enquiry including large-scale population based studies and the application of artificial intelligence (AI) technology for analyzing retinal images for risk prediction and disease detection. She is involved in evaluating AI technology to analyse retinal images to detect sight-threatening diabetic eye disease patients with diabetes attending for annual screening for eye disease. Within the Population Health Research Institute she collaborates with colleagues on other areas of public health importance including, accuracy of body composition measurement in children in different ethnic groups, interventions to improve sleep in children and adolescents as well as collaborating with colleagues within St George's University Hospital Trust on a wide range of clinical outcomes. Professor Rudnicka is undergraduate lead for Population Health Research Institute and theme lead for Population Health & Evidence Based Practice for undergraduate programmes including MBBS and Biomedical Sciences programmes at St George’s, and teaches on MSc courses to postgraduate students from a wide range of clinical and non-clinical backgrounds, in addition to MD and PhD supervision.
Professor Rudnicka qualified as an Optometrist in 1987 and gained a PhD from City, University of London in 1994. She later achieved a Master’s degree in Medical Statistics in 1998 from the London School of Hygiene and Tropical Medicine, having been awarded a Medical Research Council scholarship. She was appointed as Researcher at Wolfson Institute of Preventive Medicine at Queen Mary, University of London later that year and worked on projects related to cardiovascular epidemiology, antenatal screening and Bayesian meta-analyses.
Professor Rudnicka joined St George's, University of London in 2005 as a Research Fellow and was appointed a Reader in Medical Statistics in 2014 and Professor of Statistical Epidemiology in 2018. She has worked on lifecourse epidemiological studies examining early life exposures in relation to visual outcomes and cardio-respiratory disease risk and examining ethnic differences in cardiometabolic risk as part of a team on the the Child Heart And Health Study in England (CHASE, a school-based study of the cardiovascular health of 5,000 9-10 year old UK children of white European, black African-Caribbean, and South Asian origin in three UK cities (see http://www.chasestudy.ac.uk/).
She has experience in complex meta-analyses of observational evidence in ophthalmic epidemiology to quantify the global burden of common eye diseases and examining retinal vessel characteristics in large population-based adult studies in relation to cardiometabolic risk markers and disease, including the EPIC Norfolk and UK Biobank datasets.
She regularly reviews for a numbers of general medicine, ophthalmology and specialist journals including BMJ, Lancet, JAMA, Circulation, British Journal of Ophthalmolgy. She also reviews for numerous funding bodies including Medical Research Council, NIHR, HTA, EU Horizon 2020, BHF, Scottish Government Health Directorate, National Medical Research Council, Singapore.
Professor Rudnicka has published near 190 peer reviewed articles (H-index of 53, with over 17,000 citations). Recent invited presentations: (i) expert for National Screening Committee working group on ‘AI in the Diabetic Eye Screening Programme’ in April 2021 (ii) Westminster Health Forum keynote speaker for themed conference ‘AI-driven technologies within health and social care in March 2022’; and ‘Next steps for stroke prevention, treatment and care in the UK’ in April 2023, (iii); (iv), NHBLI / NIH Novel Retinal Biomarkers for Hypertension and Cardiovascular Disease Workshop in October 2022 (Novel Retinal Biomarkers for Hypertension and Cardiovascular Disease | NHLBI, NIH); (v) NEI / NIBIB / NIH ‘Opportunities for Ophthalmology Research in Large Cohort Studies: Integration of Ocular Imaging Data into All of Us Research Program’ meeting in April 2023.
In 2017 she received an award from The College of Optometrists for her multidisciplinary approach to ophthalmic epidemiology and retinal imaging. In July 2021 she received St George's Education Excellence Award for her approach to teaching statistics and epidemiology to medical students.
Professor Rudnicka has been working on the evaluation of AI technology to analyse retinal images from diabetic patients to detect sight-threatening diabetic eye disease for the past 10 years. Current focus is on AI and racial and ethnic equalities in health and care to develop validation, implementation and monitoring systems for AI imaging systems in healthcare settings and set standards for the regulatory/policy framework of AI in healthcare as applied to screening for secondary prevention. Recent funding (PI, £0.5M NIHR October 2021) from The NHS Transformation Directorate and The Health Foundation (funding managed by the National Institute of Health and Care Research)is concerned with the evaluation of current CE marked AI algorithms for detection of diabetic eye disease in different population groups (e.g., by age or ethnicity) prior to commissioning and deployment within the English NHS Diabetic Eye Screening Programme. This will include the first staged live implementation of AI in a real-life screening setting within the English NHS Diabetic Eye Screening Programme at the North East London. AI-assisted screening for diabetic eye disease detection has the potential to provide substantial savings for the NHS by partially replacing manual human grading of retinal images. Alongside this work, PPI initiatives examining perceptions, acceptability and expectations of health care professionals and people with diabetes in relation to the application of AI systems within the NHS DESP. She is co-applicant on a UK-US Wellcome Trust Collaborative Award (£1.1M) with internationally leading researchers from both the UK (lead institution St George’s, working with colleagues at Moorfields Eye Hospital, Institute of Ophthalmology, UCL, Kingston University) and USA (including National Institute of Health, and University of Washington) to compare prognostic modelling techniques vs. machine learning vs. end-to-end AI technology for individualized risk prediction of complications related to diabetes using a combination of systemic markers of diabetes control, cardiovascular risk markers and retinal imaging.
Other recent research has focused on the utility of detailed quantification of the retinal microvasculature from retinal images as a biomarker of vascular health in relation to health outcomes such as type 2 diabetes (T2D), cardiovascular disease and circulatory mortality in large population-based adult studies (EPIC Norfolk and UK Biobank).
Professor Rudnicka has been involved in several projects within the Population Health Research Institute, including accuracy of body composition measurement in children in different ethnic groups, interventions to improve sleep in children and adolescents, the ENABLE London (http://www.enable.sgul.ac.uk/) examining the effect of the built environment on physical activity levels, Bayesian methods for complex meta-analyses of observational studies to assess the global burden of common eye diseases, and ife course cardiorespiratory studies within large UK based cohorts (including the National Child Development Study - 1958 birth cohort and 1946 birth cohort).
She mentors non-clinical and clinical academics, and collaborates with colleagues from St George's University Hospitals NHS Foundation Trust on breast cancer surgery related research (including co-supervision of clinical academic MD examining outcomes from excision surgery) and analyses of primary and secondary care data in relation to peripheral vascular outcomes among people living with diabetes.
Publications January 2021 to May 2023
- Jiang X, Hysi PG, Khawaja AP, Mahroo OA, Hammond CJ, Foster PJ, Welikala RA, Barman SA, Whincup PH, Rudnicka AR, Owen CG, Strachan DP. GWAS of retinal vasculometry phenotypes. PLoS Genetics 2023;19(2):e1010583. org/10.1371/journal.pgen.1010583
- Rudnicka AR, Welikala R, Barman S, Foster PJ, Luben R, Hayat S, Khaw KT, Whincup P, Strachan D, Owen CG. Artificial intelligence-enabled retinal vasculometry for prediction of circulatory mortality, myocardial infarction and stroke. Br J Ophthalmol. 2022;106(12):1722-1729. doi: 10.1136/bjo-2022-321842
- Tapp RJ, Owen CG, Barman SA, Strachan DP, Welikala RA, Foster PJ, Whincup PH, Rudnicka AR, Eyes UKB, Vision C. Retinal microvascular associations with cardiometabolic risk factors differ by diabetes status: results from the UK Biobank. 2022;65(10):1652-1663. doi: 10.1007/s00125-022-05745-y
- Olvera-Barrios A, Mishra AV, Schwartz R, Khatun M, Seltene M, Rutkowska C, Rudnicka AR, Owen CG, Tufail A, Egan C. Formal registration of visual impairment in people with diabetic retinopathy significantly underestimates the scale of the problem: a retrospective cohort study at a tertiary care eye hospital service in the UK. Br J Ophthalmol. 2022 Oct 14;bjophthalmol-2022-321910. doi: 10.1136/bjo-2022-321910
- Olvera-Barrios A, Seltene M, Heeren TFC, Chambers R, Bolter L, Tufail A, Owen CG, Rudnicka AR, Egan C, Anderson J. Effect of ethnicity and other sociodemographic factors on attendance at diabetic eye screening: a 12-month retrospective cohort study. BMJ Open 2021;11(9):e046264. doi: 10.1136/bmjopen-2020-046264
- Olvera-Barrios A, Kihara Y, Wu Y, A NW, Muller PL, Williams KM, Rudnicka AR, Owen CG, Lee AY, Egan C, Tufail A, Eyes UKB, Vision C. Foveal Curvature and Its Associations in UK Biobank Participants. Invest Ophthalmol Vis Sci. 2022;63(8):26. doi: 10.1167/iovs.63.8.26
- Magee L, Goldsmith LP, Chaudhry UAR, Donin AS, Wahlich C, Stovold E, Nightingale CM, Rudnicka AR, Owen CG. Nonpharmacological Interventions to Lengthen Sleep Duration in Healthy Children: A Systematic Review and Meta-analysis. JAMA Pediatr. 2022;176(11):1084-1097. doi: 10.1001/jamapediatrics.2022.3172
- Heydon P, Egan C, Bolter L, Chambers R, Anderson J, Aldington S, Stratton IM, Scanlon PH, Webster L, Mann S, du Chemin A, Owen CG, Tufail A, Rudnicka AR. Prospective evaluation of an artificial intelligence-enabled algorithm for automated diabetic retinopathy screening of 30 000 patients. Br J Ophthalmol 2021;105(5):723-28. doi: 10.1136/bjophthalmol-2020-316594
- Donin A, Nightingale C, Perkin M, Ussher M, Jebb S, Landberg R, Welsh P, Sattar N, Adab P, Owen C, Rudnicka AR, et al. Evaluating an intervention to increase cereal fiber intake in children: a randomized controlled feasibility trial. J Nutr 2021 151:379-386. doi: 10.1093/jn/nxaa347.
- Hudda MT, Owen CG, Rudnicka AR, Cook DG, Whincup PH, Nightingale CM. Quantifying childhood fat mass: comparison of a novel height-and-weight-based prediction approach with DXA and bioelectrical impedance. Int J Obes (Lond). 2021;45(1):99-103. doi: 10.1038/s41366-020-00661-w
- Hudda MT, Aarestrup J, Owen CG, Cook DG, Sorensen TIA, Rudnicka AR, Baker JL, Whincup PH, Nightingale CM. Association of Childhood Fat Mass and Weight With Adult-Onset Type 2 Diabetes in Denmark. JAMA Netw Open. 2021;4(4):e218524.
Current grants as Principal investigator
- NIHR AI and racial and ethnic inequalities in health and care award ‘Ethnic differences in performance and perceptions of Artificial Intelligence retinal image analysis systems for the detection of diabetic retinopathy in the NHS Diabetic Eye Screening Programme’ Award £499,160 for 24 months (October 2021), PI Alicja Rudnicka (St. George’s), co-PI Prof. Adnan Tufail (Moorfields Eye Hospital/UCL), co-applicants Prof. Christopher Owen (St. George’s), Dr. John Anderson (Homerton University Hospital), Prof. Catherine Egan (Moorfields Eye Hospital/UCL), Prof. Sarah Barman (Kingston University), Prof. Aaron Lee (University of Washington, USA), Prof. Paolo Remagnino (Kingston University). Grant no. AI_HI200008.
- Policy Support Fund and Participatory Research Fund, St George’s, University of London – ‘Exploring perceptions and concerns among NHS staff and people living with diabetes about the potential deployment of Artificial Intelligence (AI) systems in the English NHS Diabetic Eye Screening Programme (DESP)’ Award £9,000 for 12 months (Feb 2023), PIs Miss Kathryn Willis (SGUL), Prof. Alicja Rudnicka (SGUL), co-applicants Dr Umar Chaudhry (SGUL), Dr Lakshmi Chandrasekaran (SGUL), Dr Charlotte Wahlich (SGUL), Prof. Christopher Owen (SGUL).
Current grants as co-applicant
- London Health Data Strategy Programme – Data at Scale Improvement Project Call award ‘Prediction of complications of diabetes mellitus utilising pan-London linked electronic health records data’ Cost £250,000 for 12 months (awarded April 2023 subject to approval from the Data Controllers for each of London’s 5 ICBs), PI Dr Iain Roy (SGHFT), co-PI Prof. Christopher Owen (SGUL), co-applicants Alicja Rudnicka (SGUL), Prof. Adnan Tufail (Moorfields, UCL), Dr John Anderson (Homerton), Prof. Aroon Hingorani (UCL), Dr Dimitrios Moutzouris (GSTT), Dr Luke Dixon (Imperial), Dr Philip James (GOS).
- Wellcome Trust Collaborative Award ‘Prediction of complications of diabetes mellitus utilising novel retinal image analysis, genetics, and linked electronic health records data.’ Award £1,126,103 over 42 months (April 2022). PIs Prof. Christopher Owen (SGUL), Prof Adnan Tufail (UCL); co-applicants Prof Alicja Rudnicka (SGUL), Prof Catherine Egan (MEH), Prof Sarah Barman (Kingston University), Prof Paolo Remagnino (Kingston University), Dr John Anderson (Homerton University Hospital), Dr Aaron Lee (University of Washington, USA), Mr Abraham Olvera-Barrios (UCL), Dr Roy Schwartz (MEH), Prof Reecha Sofat (UCL), Prof Aroon Hingorani (UCL), Dr Rick Ferris (prev NEI/NIH), Prof Emily Chew (NEI/NIH); Named post-docs Dr Alasdair Warwick (UCL), Dr Roshan Welikala (Kingston University). Grant no. 224390/Z/21/Z.
- Fight for Sight ‘Using English primary care data to examine the vascular aetiology of glaucoma’ Award £15,000 for 12 months (October 2021) PI Prof. Christopher Owen, co-applicants Alicja Rudnicka, Dr. Iain Carey (St George's, University of London), Prof. Paul Foster (UCL/Moorfields Eye Hospital).
- Chan Zuckerberg Initiative award ‘Repeat retinal imaging of 60,000 UK Biobank participants for dementia diagnostics discovery’ Award £2M for 24 months (November 2022), PI Prof. Paul Foster (UCL), co-applicants Dr Thomas MacGillivray (University of Edinburgh), Dr Denise Atan (University of Bristol), Dr Axel Petzold (UCL), Alicja Rudnicka, Prof. Christopher Owen (St George's, University of London), Mr Praveen Patel (Moorfields, UCL).
Professor Christopher Owen
Miss Kathryn Willis, Dr Charlotte Wahlich, Dr Umar Chaudhry, Dr Lakshmi Chandrasekaran, Royce Shakespeare
Dr Mohammed Hudda
Dr Katie Snape, Ms Beth Coad
St George's NHS foundation Trust collaborations
Dr Iain Roy, Dr Sarah Tang, Ms Alicia Skervin, Mr David Woodruff
Professor Sarah Barman, Dr Roshan Welikala, Dr Jiri Fajtl – (Faculty of Science, Engineering and Computing, Kingston University, London)
Professor Paul Foster, Professor Adnan Tufail, Miss Cathy Egan – (Moorfields Eye Hospital NHS Foundation Trust, London, Institute of Ophthalmology, UCL)
AI /Automated Retinal Image Analysis System (ARIAS) Research Group - including researchers from St George's University of London, Moorfields Eye Hospital NHS Foundation Trust, Institute of Ophthalmology, UCL, Homerton Healthcare NHS Foundation Trust, NIH and University of Washington, USA
UK Biobank Eyes and Vision Consortium
Professor Rudnicka is undergraduate lead for Population Health Research Institute and theme lead for Population Health & Evidence Based Practice for undergraduate programmes including MBBS and Biomedical Sciences programmes at St George’s. She teaches on MSc courses to postgraduate students from a wide range of clinical and non-clinical backgrounds, in addition to MD and PhD supervision.