Using AI to aid breast cancer treatment

Researchers from Technion – Israel Institute of Technology have developed an artificial intelligence model that predicts both the risk of breast cancer recurrence and the likelihood that a patient will benefit from chemotherapy.

The model analyses routine pathology slides taken at diagnosis, offering a fast, widely accessible alternative to costly genomic tests.

The study was recently published in The Lancet Oncology and presented at the European Society for Medical Oncology conference. It is the first AI model of its kind to be validated in a large, randomised clinical trial.

Today, genomic tests such as Oncotype DX are commonly used to guide chemotherapy decisions, but these tests are expensive, can take weeks to return results, and are unavailable to many patients globally.

The Technion-led AI model aims to address these limitations by using information already available in standard pathology samples.

The system analyses high-resolution digital images of tumour tissue stained and examined as part of routine pathology. Using deep learning, it evaluates multiple regions of the tumour and its microenvironment, identifying visual patterns associated with cancer behaviour.

Dr Gil Shamai of the Technion’s Geometric Image Processing Laboratory, who led the study, said the model integrates subtle cues to generate a score that reflects both recurrence risk and expected benefit from chemotherapy.

“These are complex biological signals that the human eye cannot consistently quantify,” Shamai said.

Professor Ron Kimmel, head of the laboratory in the Henry and Marilyn Taub Faculty of Computer Science, said the system extracts a visual signature from pathology images.

Clinically, the process is straightforward. After diagnosis, the existing tissue sample is digitally scanned and securely analysed by the AI system. Within minutes, the model produces a numerical score that supports shared decision-making between oncologist and patient.

The researchers were granted access to tissue samples and clinical data from the TAILORx trial, one of the largest randomised breast cancer studies, involving more than 10,000 patients.

The model was further validated on thousands of patients from hospitals in Israel, the United States and Australia, demonstrating consistent performance across different populations and healthcare systems.

Unlike genomic tests, the AI-based assessment requires no additional tissue, laboratory processing or waiting period. It can be performed in minutes in any pathology lab equipped with a digital scanner and internet access.

“In developing countries, where genomic testing is largely unavailable, this tool could dramatically expand access to personalised cancer care,” Aran said.

The research team is now advancing steps toward clinical implementation in Israel and preparing clinical trials in Brazil and India.

The study was led by Shamai, Kimmel and Professor Dvir Aran of the Technion’s Faculty of Biology, in collaboration with oncologists and pathologists from institutions including Dana-Farber Cancer Institute, Mount Sinai Medical Centre, the University of Chicago Medical Centre and IPATIMUP Medical Centre in Portugal.