Automated way to detect eye surface cancer developed
Australian researchers have developed a new automated non-invasive technique for diagnosing eye surface cancer, offering the potential to reduce the need for biopsies, prevent therapy delays and make treatment far more effective for patients of the major disease.

The technique involves the custom-building of an advanced imaging microscope linked with state-of-the-art computing and artificial intelligence operations, resulting in an automated system that is "able to successfully identify between diseased and non-diseased eye tissue, in real-time, through a simple scanning process", Xinhua reported quoting from a statement by the ARC Centre of Excellence for Nanoscale BioPhotonics research facility.

Eye surface cancer, also known as Ocular Surface Squamous Neoplasia or OSSN, is a common malignancy of the cornea and conjunctiva parts of the eye. "Clinical symptoms of OSSN are known to be variable and in early stages can be extremely hard to detect, so patients may experience delays in treatment or be inaccurately diagnosed," said facility researcher and project lead scientist Abbas Habibalahi.

Early detection of the condition is critical as it "supports simple and more curative treatments such as topical therapies whereas advanced lesions may require eye surgery or even the removal of the eye, and also has the risk of mortality," he said.

The new technique scans natural light given off by specific eye cells - diseases cells have their own unique "light-wave signature" which the researchers' special computational algorithm is able to identify to provide a "quick and efficient diagnosis" Habibalahi said. His team's findings were reported in clinical journal The Ocular Surface.

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