IU Faculty of Drugs’s Spyridon Bakas mentioned the brand new suggestions are a much-needed replace to the present normal of care by which particular person radiologists measure tumor dimension, which dictates therapy choices. Credit score: Liz Kaye, Indiana College
A world, multidisciplinary workforce of main neuro-oncology researchers and clinicians has launched new suggestions for good scientific follow—a set of pointers that helps guarantee scientific trial outcomes are dependable, and sufferers are protected—concerning the usage of synthetic intelligence strategies to extra precisely diagnose, monitor and deal with mind most cancers sufferers.
The workforce not too long ago printed two companion coverage evaluations in The Lancet Oncology, on behalf of the clinically authoritative Response Evaluation in Neuro-Oncology cooperative group, which is a collaboration of worldwide consultants who develop standardized standards for evaluating therapy response in scientific trials for mind most cancers.
Indiana College Faculty of Drugs’s Spyridon Bakas is the lead writer on the second coverage evaluation, which establishes pointers for standardization, validation and good scientific follow of AI for neuro-oncology.
He mentioned the brand new suggestions are a much-needed replace to the present normal of care by which particular person radiologists measure tumor dimension, which dictates therapy choices. This isn’t ideally suited, Bakas mentioned, as a result of the evaluation is usually subjective. Every radiologist can interpret imaging scans in a different way, resulting in therapy methods that fluctuate primarily based on who views the scan.
“We can use AI to look at images of the tumors more objectively,” mentioned Bakas, the Joshua Edwards Affiliate Professor in Pathology and Laboratory Drugs and the director of the Division of Computational Pathology on the IU Faculty of Drugs, in addition to a researcher within the IU Melvin and Bren Simon Complete Most cancers Middle. “AI programs can help determine quickly what type of disease it is, what subtype of tumor and what particular grade it is, in addition to helping track the progress of a lesion during treatment.”
In accordance with the workforce, there are predictive, prognostic and diagnostic AI fashions and options which can be changing into accessible for well being care practitioners, however how they’re used varies extensively at completely different establishments.
“Thanks to new technology, there are ways to use AI to help assess whether a tumor is progressing or is stable,” mentioned Raymond Y. Huang, affiliate professor at Harvard Medical Faculty and neuroradiology division chief at Brigham and Girls’s Hospital in Boston, Massachusetts. “However, there needs to be a standardized way to use AI to accurately diagnose and treat patients.”
The workforce reviewed current analysis articles and publications associated to present developments of AI within the area to develop the rules, which have been introduced at this yr’s American Society of Medical Oncology assembly in Chicago, Illinois, and the annual assembly of the European Affiliation for Neuro-Oncology in Glasgow, Scotland. The rules may also be introduced on the Society for Neuro-Oncology assembly in November in Houston, Texas.
A few of the authors’ pointers embrace:
Utilizing software program that has been developed utilizing giant and importantly various cohorts of affected person knowledge.
Making certain the AI fashions for outlining a tumor observe World Well being Group standards.
Contemplating how the tumor photographs are obtained, processed and segmented earlier than analyzing them.
“These guidelines are critical for ensuring that AI tools developed in the U.K. and beyond meet rigorous standards and improve patient outcomes,” mentioned Thomas Sales space, a co-author from King’s School London. “With these recommendations, we can move towards more accurate, standardized AI applications that benefit both clinicians and patients across the U.K. and internationally.”
As a result of AI remains to be new, these suggestions are among the many first on this planet concerning its correct use in most cancers care. Nevertheless, additional examine is important.
“It is important that we continue our study of these AI models on large, diverse patient populations to continue extending our understanding of disease and improving the way we use them,” Bakas mentioned.
Extra data:
Javier E Villanueva-Meyer et al, Synthetic Intelligence for Response Evaluation in Neuro Oncology (AI-RANO), half 1: evaluation of present developments, The Lancet Oncology (2024). DOI: 10.1016/S1470-2045(24)00316-4
Spyridon Bakas et al, Synthetic Intelligence for Response Evaluation in Neuro Oncology (AI-RANO), half 2: suggestions for standardisation, validation, and good scientific follow, The Lancet Oncology (2024). DOI: 10.1016/S1470-2045(24)00315-2
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