National, 20th January 2022: Artificial intelligence (AI) systems are able to diagnose prostate cancer biopsies with the same level of accuracy as specialist uropathologists, and better than many general pathologists, international research has found.
An article published in Lancet Oncology in 2020 reported the work of a research consortium that included New Zealand pathologist Professor Brett Delahunt from the Department of Pathology and Molecular Medicine at the University of Otago, Wellington. In this study it was shown that the accuracy of computer-based diagnosis of prostate cancer was comparable to that of specialist urological pathologists.
In a newly published follow-up study in the international science journal Nature Medicine, the performance of different AI models was tested against the gold standard diagnosis of prostate cancer provided by Professor Delahunt and two colleagues from the Karolinska institute in Sweden and the University of Queensland.
The researchers organised a global competition to build AI models to diagnose more than 10,000 prostate biopsies. More than 1,000 AI developers from 65 countries participated in the competition, sending in 1,010 algorithms to be assessed for accuracy in diagnosis, making it the largest competition to be held into the use of AI in pathology.
Fifteen of the algorithms were selected to have their performance measured against diagnoses made by specialist uropathologists and general pathologists.
Professor Delahunt says the research provides the first independent evaluation of AI algorithms across different patient populations and pathology labs and across reference standards developed by expert panels of uropathologists from the United States and Europe.
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Prostate cancer is the second most common cancer among New Zealand men, with almost 4,000 men diagnosed each year. About 650 men die from the disease every year, and Professor Delahunt says achieving more precise diagnoses is key to reducing the number of deaths.
“Assessment of biopsies is crucial when it comes to making decisions on prostate cancer treatment – but there can be significant variations in the assessments made by different pathologists.
“Standardised AI models could really make a difference when it comes to improving outcomes for this disease.”
Pathologists characterise tumours into different ‘Gleason’ growth patterns, with biopsy specimens categorised into one of five International Society of Urological Pathology grade groups.
Professor Delahunt says the process is quite subjective and can lead to both ‘undergrading’ and ‘overgrading’ of prostate cancer biopsies.
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Professor Delahunt says because the algorithms would likely miss fewer cancers than the pathologists did, AI could be used to reduce the workload of pathologists by automating the identification and exclusion of most benign biopsies.
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