Automated system non-invasively detects eye surface cancer

Monday, 08 April, 2019

Automated system non-invasively detects eye surface cancer

Australian researchers have developed a new automated non-invasive technique for diagnosing eye surface cancer, known as ocular surface squamous neoplasia (OSSN). Described in The Ocular Surface, the technique has the potential to reduce the need for biopsies, prevent therapy delays and make treatment far more effective for patients.

“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 Abbas Habibalahi, a researcher at the ARC Centre of Excellence for Nanoscale BioPhotonics (CNBP) and lead scientist on the project.

“The early detection of OSSN 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.”

Habibalahi and his research team have now devised a technological approach that comprises the custom-building of an advanced imaging microscope in association with state-of-the-art computing and artificial intelligence operation. The result is an automated system that is able to successfully identify between diseased and non-diseased eye tissue, in real time, through a simple scanning process.

“Our high-tech system scans the natural light given off by specific cells of the eye, after being stimulated by safe levels of artificial light,” Habibalahi said. “Diseased cells have their own specific ‘light-wave’ signature which our specially designed computational algorithm is then able to identify providing a quick and efficient diagnosis.”

Tissue samples from 18 patients with OSSN were tested using the method, which was able to identify the diseased cells in all 18 cases. The diagnostic technology was able to precisely map the location of abnormal tissue margins on the eye, which Habibalahi said is “highly desirable in a clinical setting”.

“Accurate boundary delineation of OSSN means that curative treatments such as topical medications or surgery can be more accurately and effectively applied,” he said.

OSSN diagnosis also foregoes the need for a biopsy approach, which benefits “both the patient and the doctor” according to Habibalahi.

“Biopsies of the eye can be traumatic and can also be costly and time-intensive with samples needing to be sent to a laboratory for testing.”

Habibalahi believes the automated technology has potential for widespread use on an outpatient basis, especially in developing countries where there may be a lack of pathology equipment and associated specialists.

“Next steps are to make our system practical and workable in a clinical setting,” he said. “We hope to do this by incorporating our system into a standard retinal camera set-up — similar to that used by opticians and optometrists when undertaking regular eye examinations.”

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