Artificial intelligence could be used to review – and possibly one day even make – cancer diagnoses if a team of WA researchers is successful in training a specialised computer to detect abnormalities in lymph nodes.
As part of a bold new research project being led by PathWest anatomical pathologist Jeremy Parry, a computer capable of “deep learning” will initially be taught to detect changes in lymph nodes that may or may not be malignant, with later refinements potentially helping it to discern malignant from benign changes.
Dr Parry, in collaboration with experts in artificial intelligence from Murdoch University’s College of Science, Health, Engineering and Education, says the computer will be taught using digitised whole-slide scans of lymph node tissue collected from Western Australian patient samples.
He hopes that through the process of deep learning – in which the computer learns to recognise patterns within data it has already analysed – it might eventually be able to detect nuanced early indicators of cancer.
Dr Parry’s study is one of 10 projects awarded funding in the latest round of the Department of Health-funded Research Translation Projects (RTP) program.
He says the aim of his project is not to replace pathologists in analysing samples, but to assist in the review and validation of their findings.
In a second part of the project, Dr Parry and his team will assess the value of using digitised whole-slide scans of tissue samples across the WA health system.
The present system for examining tissue samples involves putting them on glass slides so that they can be viewed under a microscope.
“If we need a second opinion we must physically transport the slide to wherever the person is, which could be at another hospital – or even in another state,” Dr Parry explained.
“However if we take the sample on the slide and then scan it using our digital whole-slide pathology scanner, we have access to an image that we can send anywhere in the world and which can be viewed instantaneously.”