Enhancing Brain Cancer Care: AI Innovations in Neuro-Oncology Guidelines for Diagnosis and Treatment

Enhancing Brain Cancer Care: AI Innovations in Neuro-Oncology Guidelines for Diagnosis and Treatment

November 21, 2024 Catherine Williams - Chief Editor Health

An international team of researchers has created new clinical practice recommendations for using artificial intelligence (AI) in brain cancer care. These guidelines were detailed in a review published by Bakas et al in The Lancet Oncology.

Background

Currently, neuro-oncology relies on radiologists measuring tumor size to guide treatment. This method can be subjective, as different radiologists may interpret scans differently. Predictive and diagnostic AI models are emerging, but their use varies by institution.

“Thanks to new technology, there are ways to use AI to help assess whether a tumor is progressing or stable,” said Dr. Raymond Y. Huang from Harvard Medical School. He emphasized the need for standardized methods to utilize AI in diagnosis and treatment.

AI can objectively analyze tumor images, as explained by Dr. Spyridon Bakas. He noted that AI can quickly identify tumor types and track changes during treatment.

Guideline Overview

This review is one of two related studies from the Response Assessment in Neuro-Oncology group, which aims to standardize criteria for evaluating treatment responses in clinical trials for brain cancer.

The new guidelines address the use of AI software developed from diverse patient data. They ensure that AI definitions of tumors align with World Health Organization criteria and set standards for how imaging data is processed and analyzed.

The researchers believe these updates to the standard of care are crucial.

“These guidelines are critical for ensuring that AI tools from the UK and other places meet rigorous standards and improve patient outcomes,” said Dr. Thomas Booth from King’s College London.

The recommendations represent one of the first global approaches to AI in cancer care, highlighting the need for further research.

“It is important that we continue our study of these AI models on large, diverse patient populations,” Dr. Bakas concluded.

Disclosure

The research received support from the National Institutes of Health, the U.S. Department of Veterans Affairs, the U.S. Department of Defense, the Dana Foundation, the V Foundation for Cancer Research, and the European Union’s European Research Council. For full disclosures, visit thelancet.com.