| EPSRC Reference: |
EP/R014094/1 |
| Title: |
Development of New Low Cost Point of Care Diagnostic Technologies for Diabetic Retinopathy in China |
| Principal Investigator: |
Zheng, Dr Y |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Institute of Ageing and Chronic Disease |
| Organisation: |
University of Liverpool |
| Scheme: |
GCRF (EPSRC) |
| Starts: |
01 February 2018 |
Ends: |
31 January 2022 |
Value (£): |
1,150,450
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| EPSRC Research Topic Classifications: |
| Med.Instrument.Device& Equip. |
Medical Imaging |
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| EPSRC Industrial Sector Classifications: |
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| Panel History: |
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Summary on Grant Application Form |
We will develop novel, low-cost, diagnostic technologies for the detection of a blinding condition called diabetic retinopathy (DR) in China. These technologies will enable cost-effective, large-scale detection of sight-threatening disease to be performed by non-expert health care workers at the time and place of patient care in China.
Over 110 million people in China live with diabetes and this number is expected to increase to 150m by 2040. Diabetes causes visual loss through damage to blood vessels of the retina at the back of the eye. Treatments are effective (and increasingly affordable in China) but only if the disease is detected early enough. Improving early diagnosis and treatment of DR is one of the principal objectives of the Chinese Government's 5-Year National Plan of Eye Health (2016-2020). Current methods of detecting DR rely on costly imaging equipment and many skilled personnel to take and interpret retinal images. China has very few health workers with these skills. Case detection strategies which are cost-effective in Western Europe cannot possibly be replicated at the scale necessary for China.
Building on an existing collaboration between the University of Liverpool, Peking University and the Chinese Medical Association (CMA), our joint research team from Liverpool and China of engineers, statisticians, education specialists, eye doctors and health economists are well placed to develop a new diagnostic imaging solution tailored to local needs.
Our objectives for this project are:
1. To develop a novel, low-cost, robust imaging device for detection of DR
2. To develop new automated computer algorithms to rate images of the retina for sight-threatening disease
3. To develop a novel comparative judgement method to refine the DR severity grading from automated computer algorithms
4. To validate the new technologies in the UK and test them in China to ensure maximum cost-effectiveness
We will develop a new low-cost, camera designed specifically for the needs of China. This device will produce both high-quality colour images and optical coherence tomography (OCT) images of the retina. OCT is widely available but current commercial systems are very expensive. Our new device will be based on our novel patent-pending technology and will be first tested on human donor tissue.
We will develop and evaluate new, automated image analysis techniques allowing computers to learn to analyse both colour and OCT images of the retina. We aim to produce systems capable of differentiating between patients with and without DR and between those with mild/moderate and severe disease at the time and place of patient care.
In order to achieve a high level of diagnostic accuracy (over and above automated image analysis), we will develop and evaluate a new human learning system. This system will harness the collective judgements of Chinese health workers to rank images in terms of DR severity. We will create a self-sustaining network of activity where novices and experts support each other in making effective clinical judgements. We will develop new statistical methods to underpin the system and to evaluate both diagnostic accuracy and performance of the health workers. Our imaging and diagnostic system will be validated in 241 patients with diabetes in the UK. Our project team in China will then undertake a pilot study of 461 patients and a costing exercise. The diagnostic accuracy of the system and its cost-effectiveness will be investigated.
We will engage policy makers through our Chinese team who occupy leading roles in the CMA. Detection and treatment of sight threatening DR will prevent disability with benefit to Chinese society and China's economy. Our systems will upskill health care workers, strengthen existing health systems and build research capacity in China. Dissemination of our techniques through open-source software will maximise benefits for other low and middle-income countries.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.liv.ac.uk |