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New diagnostic offers hope to sufferers of serious eye infections that pose biggest risk to contact lens wearers

Published: Fri Dec 22 2017

Some of the most devastating eye infections leading to possible blindness and to which contact lens wearers are particularly vulnerable have until now proved difficult to diagnose quickly enough for effective treatment.

Now researchers at the University of Bradford and ophthalmologists at Manchester Royal Eye Hospital have developed an automatic diagnostic system to improve the detection, and treatment, of two of the most serious eye infections.

Infectious keratitis (Acanthamoeba keratitis and fungal keratitis or Fusarium) attacks the cornea and can lead to irreversible complications and even blindness.

A significant risk factor is contact lens wear for acanthoamoeba infections, especially in unhygienic circumstances such as swimming while wearing contact lenses, the use of non-sterile lens solutions, and insufficient disinfection practices. In the United Kingdom, Europe, Hong Kong, and the USA, the estimated infection rate is 1.2 per million adults per year, but this rises to between 0.2 and 1 per 10,000 amongst contact lens wearers.

Successful treatment needs early diagnosis and intervention but accurate and rapid identification of the infectious agent involved and proper management of corneal ulcers are challenging clinical problems. Microorganisms need time to be detected using corneal cultures and smears, which are currently considered to be the gold standard diagnostic tools for infectious keratitis, and they may not be detected because of inadequate sample material, delay in performing the investigations, deeply seated lesions, and previous use of empirical antimicrobial treatments.

The affected areas of Acanthamoeba keratitis (cysts) and Fusarium (fungal filaments) need to be detected first using confocal microscopy (an optical imaging technique for increasing optical resolution and contrast) and then need to be tracked in the sequence of images that are captured from different depths of the patient's cornea. However, manual detection and tracking of those signs in confocal images are subjective, time-consuming and error-prone.

Now, researchers at the University of Bradford, working with Manchester Royal Eye Hospital, have developed an automatic corneal diagnostic tool that can help ophthalmologists in diagnosing corneal abnormalities by detecting the visual signs of the disease and then extracting the main quantitative features using confocal microscopy images of that disease.

The system colour maps the images, tracks the depth of infection across all the images of the whole cornea and detects clinical parameters that can help in the diagnosis of the disease.

The system was developed by Professor Rami Qahwaji of the University of Bradford and his research student Rania Alzubaidi. Prof Qahwaji said: “Our work with Manchester Royal Eye Hospital has already shown its clinical usefulness, demonstrating remarkably high efficiency and reliability.

“It can be difficult to find and train confocal microscopy graders to accurately detect Acanthamoeba cysts or fungal filaments in the images. An automated system can overcome this problem, help the clinician to make the diagnosis then start the correct treatment more quickly. Response to treatment can be difficult to assess using clinical examination alone. 

“There is also evidence that Acanthamoeba cysts and fungal filament morphology may change over time with use of the correct treatment. An automated system to analyse confocal microscopy images for such changes would assist the clinician in determining whether the ulcer is improving, or whether a change of treatment is needed.”

Mr Arun Brahma, Consultant Ophthalmologist at Manchester Royal Eye Hospital, said: “The use of this system will enhance patient care with these serious conditions. These blinding eye infections are difficult to treat and use of this system will allow easier monitoring and result in more effective treatments. In addition, using the same system, certain genetic corneal diseases may be monitored and novel treatments evaluated.”

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