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Automated way to detect eye surface cancer developed: Study

Australian researchers have developed a new automated non-invasive technique for diagnosing eye surface cancer. This new technique offers the potential to reduce the need for biopsies, prevent therapy delays, and make treatment far more effective for patients. Eye surface cancer, also known as Ocular Surface Squamous Neoplasia (OSSN), is a common malignancy of the cornea and conjunctiva parts of the eye. The novel technique involves custom-building of an advanced imaging microscope linked with computing and Artificial Intelligence (AI) operations.

Lead scientist Abbas Habibalahi, at the Australian Research Council (ARC) Centre of Excellence for Nanoscale BioPhotonics, said that 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. He said that 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 removal of the eye, and also has the risk of mortality.

The new technique scans natural light given off by specific eye cells — diseased cells — that have their own unique ‘light-wave signature’. The researchers said that they will be able to confirm the disease straight away through a simple eye scan with no biopsy required and appropriate action can be quickly progressed by the specialist.

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