This AI Can Predict The Success Of Pre-Operative Chemotherapy In Breast Cancer Patients

The healthcare industry is rapidly evolving and the strategic implementation of artificial intelligence and machine learning tools has been transformational. Today, AI is enabling healthcare providers to improve patient experience, early detection of diseases, streamline clinical workflows and treatment plans, manage patient information, book appointments/follow-up visits, predict emergencies, suggest the right surgical tools, and reduce operational costs.

From suggesting the appropriate IVF treatments and supplementing labor-intensive image scanning to make accurate diagnoses and eliminate health inequities, artificial intelligence has made healthcare accessible as well as affordable for everyone.

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Did you know that breast cancer is the second leading cause of death in women after lung cancer? And, the chance of death from breast cancer is about 1 in 39 (about 2.5%).

With enormous technological advancements in artificial intelligence, early detections, and increased awareness, we are in better shape to combat it.

After New York approved PreciseDX Breast Test Lab, an AI-driven breast cancer diagnostic that enhances cancer grading and categorizing the risk, the University of Waterloo, has developed a technology to predict the success of pre-operative chemotherapy in breast cancer patients.

Engineers at the University of Waterloo developed artificial intelligence technology that can predict if breast cancer patients would benefit from chemotherapy prior to surgery or not.

The New Ai Algorithm

The new AI algorithm, part of the open-source Cancer-Net initiative led by Dr. Alexander Wong, could help unsuitable candidates avoid the serious side effects of chemotherapy and pave the way for better surgical outcomes for those who are suitable.

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Dr. Wongg states that determining the right treatment for a given breast cancer patient is very difficult but at the same time, it is crucial to avoid unnecessary side effects from using treatments that are unlikely to have real benefit for that patient.

“An AI system that can help predict if 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 improve recovery and survival.”

Benefits of Correlated Diffusion Imaging

The AI software was trained with images of breast cancer made with a new magnetic image resonance modality, invented by Wong and his team, called synthetic correlated diffusion imaging (CDI).

With knowledge gleaned from CDI images of old breast cancer cases and information on their outcomes, the AI can predict if pre-operative chemotherapy treatment would 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 surgery such as mastectomies.

“I’m quite optimistic about this technology as deep-learning AI has the potential to see and discover patterns that relate 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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The new AI algorithm and the complete dataset of CDI images of breast cancer have been made publicly available through the Cancer-Net initiative so other researchers can help advance the field.

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