Artificial Intelligence detects breast cancer chemotherapy effectiveness: Study

The open source Cancer-Net initiative’s new AI system could help unfit candidates avoid the harmful side effects of chemotherapy and improve surgical outcomes for those who are qualified. It is led by Dr. Alexander Wong

Representative image. Photo/iStock

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Engineers at the University of Waterloo have created artificial intelligence (AI) technology to predict whether chemotherapy before surgery will be beneficial for women with breast cancer.

The open-source Cancer-Net initiative*’s new AI system could help unfit candidates avoid the harmful side effects of chemotherapy and improve surgical outcomes for those who are qualified. It is led by Dr. Alexander Wong.

“Determining the right treatment for a given breast cancer patient is currently very difficult, and it is crucial to avoid unnecessary side effects from using treatments that are unlikely to be of real benefit to that patient,” says Wong, a professor of systems design engineering. .

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“An AI system that can help predict whether a patient is likely to respond well to a given treatment gives doctors the tool needed to prescribe the best personalized treatment for a patient to ensure recovery and survival improve.”

In a project led by Amy Tai, a graduate student with the Vision and Image Processing (VIP) Lab, the AI ​​software was trained on images of breast cancer made with a new magnetic resonance imaging modality invented by Wong and his team , called synthetic correlated diffusion imaging (CDI).

With knowledge gained from CDI images of old breast cancer cases and information about their outcomes, the AI ​​can predict whether pre-operative chemotherapy treatment will benefit new patients based on their CDI images.

Known as neoadjuvant chemotherapy, the pre-surgical treatment can shrink tumors to make surgery possible or easier and reduce the need for major operations such as mastectomy.

“I am quite optimistic about this technology, as deep-learning AI has the potential to see and discover patterns related to whether a patient will benefit from a given treatment,” said Wong, a director of the VIP Lab and the Canada Research Chair. in Artificial Intelligence and Medical Imaging.

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