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UBC Okanagan and BC Cancer \u2013 Kelowna have partnered on research that uses CT scans to detect cardiovascular disease risk in breast cancer patients.<\/p>\nUBC Okanagan and BC Cancer \u2013 Kelowna have partnered on research that uses CT scans to detect cardiovascular disease risk in breast cancer patients.<\/p>\n
UBC Faculty of Medicine researchers, working with scientists at UBC Okanaganand BC Cancer \u2014 Kelowna, have developed a groundbreaking AI model that can help identify breast cancer patients who may face a double-threat\u2014that of cancer and cardiovascular disease.<\/p>\n
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Dr. Mohammad Shehata<\/p>\n
Cardiovascular disease remains one of the leading causes of death worldwide, responsible for an estimated 17.9 million fatalities annually. According to the American Heart Association, breast cancer patients are more likely to experience cardiovascular complications and related issues than the general population.<\/p>\n
\u201cBreast cancer patients already face immense challenges. Cardiovascular disease is a critical and often overlooked health threat they endure,\u201d says Dr. Mohammad Shehata, a professor in the\u00a0Irving K. Barber Faculty of Science\u2019s<\/a>\u00a0computer science department.<\/p>\n \u201cThe model we have created gives clinicians a new tool to proactively identify those patients who are at high-risk of developing cardiovascular disease, allowing them to intervene earlier and potentially save lives.\u201d<\/p>\n \u201cThis research marks a significant step forward in how we assess cardiovascular risk in breast cancer patients.\u201d<\/p>\n Dr. Rasika Rajapakshe<\/p>\n All breast cancer patients undergoing radiation therapy have chest CT scans to plan the treatment. This new research, published recently in\u00a0Radiotherapy and Oncology<\/a>, demonstrates how the CT scan can serve the added purpose of estimating cardiovascular risk.<\/p>\n \u201cThis research marks a significant step forward in how we assess cardiovascular risk in breast cancer patients,\u201d says study co-lead Dr. Rasika Rajapakshe, clinical associate professor of surgery in UBC\u2019s Faculty of Medicine and senior medical physicist at BC Cancer \u2013 Kelowna. \u201cBy combining routinely collected CT imaging with clinical health records, we can detect risk earlier and more accurately than ever before\u2014without adding extra burden to patients or the health-care system.\u201d<\/p>\n This study demonstrates how the AI model can compare a patient\u2019s CT scan with their electronic health records, including their general health, age, hypertension, diabetes and family history to forecast a more precise and personalized risk assessment.<\/p>\n Traditionally, risk models rely on clinical data, including age or any symptoms of hypertension or diabetes. This new research demonstrates how the AI models effectively identify subtle structural changes in the heart as seen on CT scans, alongside systemic risk factors.<\/p>\n \u201cWhat makes this approach truly powerful is the use of multimodal artificial intelligence,\u201d says Dr. Shehata. \u201cBy integrating imaging and clinical data, the model can capture complex patterns that traditional tools simply miss, opening the door to more personalized and precise care.\u201d<\/p>\n The research team used powerful AI techniques to bring together different kinds of data to combine the information into a single system that helps predict health outcomes.<\/p>\n The model has demonstrated outstanding predictive accuracy\u2014significantly outperforming existing methods.<\/p>\n \u201cOur model achieved exceptionally high predictive performance, highlighting the value of combining advanced imaging analysis with cutting-edge clinical language models in a unified framework,\u201d says Dr. Rajapakshe, also an adjunct computer science professor at UBC Okanagan.<\/p>\n Dr. Shehata says this research underscores the power of locally driven innovation to address global health challenges.<\/p>\n \u201cThis level of precision has the potential to identify high-risk patients early in their treatment while also tailoring interventions and care accordingly,\u201d he adds. \u201cThis approach may serve as a non-invasive, clinically valuable tool for early prediction of cardiovascular-related mortality, enabling timely identification of at-risk patients and improving their survival outcomes.\u201d<\/p>\n This research is supported by the\u00a0BC Cancer Foundation<\/a>.<\/p>\n![\"\"](\"https:\/\/www.newsbeep.com\/ca\/wp-content\/uploads\/2026\/06\/Rasika-Rajapakshe-780x780-1.png\")
Dr. Rasika Rajapakshe<\/p>\n