A new artificial intelligence (AI) tool developed by La Trobe University researchers could help predict which stage-two bowel cancer patients are at risk of relapse, in an advance that could ultimately lead to thousands getting life-saving treatment earlier.
Published in the journal Gastroenterology, the research documents the creation of SÉMIL (Semantically-Enhanced Multiple Instance Learning), an AI algorithm that uses images and written descriptions to analyse routine pathology slides to identify patients at greater risk of recurrent bowel cancer.
Researchers analysed more than 1600 pathology slides and validated the findings across 1220 stage-two bowel cancer patients in three independent cohorts and multiple Australian institutions.
The study also found that when AI-based assessment and pathologist evaluation aligned, this produced the most accurate risk rating for stage-two cancer patients.
Lead author and PhD candidate Francis Magisson, from La Trobe University’s School of Computing, Engineering and Mathematical Sciences (SCEMS) said the technology assessed the tumour's growth pattern at its invasive front, a feature that is prognostically important but difficult for pathologists to classify consistently. It then assigned each tumour to a higher or lower risk group.
“This information could be used to assist pathologists and clinicians to identify which stage-two cancer patients are at higher risk of relapse and may need closer monitoring or additional treatment such as chemotherapy,” Francis said.
Current Australian clinical guidelines recommend only using chemotherapy after surgery for high-risk stage-two bowel cancer patients. Therefore, more accurately determining which patients are at high risk is very valuable.
Associate Professor Zhen He, who leads the Digital Biology program at La Trobe’s Institute for Molecular Science (LIMS), SCEMS, and the Australian Centre for Artificial Intelligence in Medical Innovation (ACAMI) said the research highlighted the growing role of AI in supporting precision medicine.
“SÉMIL could be integrated into existing digital pathology workflows without requiring expensive new tests or tissue samples to provide more consistent and objective assessments of cancer pathology,” Professor He said.
“In future, AI-based pathology assessments could be combined with other emerging biomarkers to improve risk stratification and treatment planning.”
Associate Professor David Williams, an anatomical pathologist from Austin Health and the Olivia Newton-John Cancer Research Institute which is affiliated with the La Trobe School of Cancer Medicine said the tool was designed to support, not replace, clinical decision-making.
“One of the biggest challenges in stage-two bowel cancer is identifying which higher-risk patients require treatment and weighing up the potential benefits of administering chemotherapy against side effects,” Associate Professor Williams said.
“Our study shows that AI-based assessment has potential to provide pathologists with an additional layer of information that could help clinicians make more informed decisions about next-stage treatment options.”
Bowel cancer is Australia’s fourth most commonly diagnosed cancer and the second most common cause of cancer death. Worldwide, it is the third most common cancer.
The study also involved research collaborators from the La Trobe Centre for Molecular Science, La Trobe School of Cancer Medicine, WEHI, Monash University, University of Melbourne, UNSW Sydney, Peter MacCallum Cancer Centre and other leading cancer centres around Australia.
About the La Trobe AI Institute and the Australian Centre for Artificial Intelligence for Medical Innovation
La Trobe University’s newly established La Trobe AI Institute provides a single front door to the University’s AI capability across research, education and industry collaboration.
A key component of the Institute is La Trobe’s Australian Centre for Artificial Intelligence for Medical Innovation, Australia’s first AI medical research facility and the first university innovation centre specialising in using artificial intelligence to develop immunotherapies and cancer vaccines.
Media enquiries
Debora McInnes – d.mcinnes@latrobe.edu.au, + 61 487 448 734
