Research from TMU reveals breakthrough in AI-assisted pathology for breast cancer
Toronto, February 12, 2024 – Groundbreaking new research from Toronto Metropolitan University (TMU) is showing remarkable success in using AI tools to assess and interpret breast cancer tissue, particularly focusing on the Ki-67 biomarker. Led by professor April Khademi, Canada Research Chair and medical image analysis expert, a custom developed AI tool has been shown to augment the decisions of pathologists which can revolutionize cancer care. Khademi’s research was first published as a paper “AI improves accuracy, agreement and efficiency of pathologists for Ki67 assessments in breast cancer” published in Nature here (external link) .
The Ki-67 biomarker, identified as a crucial indicator for deciding treatment (source (external link) ) has traditionally posed challenges for pathologists - in that there is a high level of disagreement on how to score the tissue. This impedes the pathologists’ ability to deliver accurate and efficient assessments (source) (external link) . Khademi's pioneering research, supported by a consortium of leading organizations including the Canadian Cancer Society (CCS) and the Vector Institute has propelled the field forward.
Khademi’s AI-powered tool was rigorously tested and was shown to out-perform commercial solutions (source (external link) ). This tool was tested live in an innovative study with 90 international pathologists and showed AI assistance significantly enhanced pathologists' assessments, leading to more accurate and efficient diagnoses. Most notably, the AI tool improved pathologist scoring accuracy, agreement and turn-around-time (TAT). This study demonstrates how using AI can result in more consistent and reliable treatment decisions which has the potential to dramatically improve quality of care. Khademi’s study, which is one of the largest of its kind, highlights the transformative potential of AI in pathology.
"This research represents a significant milestone in the integration of AI technologies into pathology workflows,” said Khademi. “Findings suggest that AI tools not only improve assessment accuracy which results in more reliable treatment options, but also offer a substantial return on investment by streamlining workflow and enhancing patient care."
Khademi, along with her PhD student, Amanda Dy, at TMU, aim to leverage these findings for further advancements in cancer research and diagnostics.
"Our current study primarily focuses on the assessment stage, and our ultimate goal is to enhance treatment planning and patient outcomes," said Khademi. "By harnessing the power of AI, we aim to empower pathologists with additional insights and solutions that may have previously gone unnoticed, ultimately prioritizing the well-being of patients."
This groundbreaking research solidifies TMU’s position as a leader in health-care education and underscores Canada's prominence in the global scientific community. With continued collaboration and innovation, Khademi and her team are poised to revolutionize cancer diagnostics and improve patient care worldwide.
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For media inquiries:
Jessica Leach
Toronto Metropolitan University
jleach@torontomu.ca
About Toronto Metropolitan University
Toronto Metropolitan University (TMU) is Canada’s leader in innovative, career-oriented education. Urban, culturally diverse and inclusive, the university is home to more than 46,000 students, including 2,900 Master’s and PhD students, 4,000 faculty and staff, and over 240,000 alumni worldwide. For more information, visit torontomu.ca.
About Dr. April Khademi
April Khademi is Canada Research Chair in AI for Medical Imaging, an Associate Professor of Biomedical Engineering at Toronto Metropolitan University and Principle Investigator of the Image Analysis in Medicine Lab (IAMLAB), which specializes in the design of AI algorithms for medical imaging. Her research is funded by CIHR, NSERC, Ontario Government, Alzheimer’s Society, Canadian Cancer Society and MITACs. April is also a Faculty Affiliate of the Vector Institute, Associate Professor (status) in Medical Imaging at the University of Toronto, Associate Scientist at St. Michael’s Hospital and Member of the Institute for Biomedical Engineering, Science & Technology (iBEST) and T-CAIREM. She had previous roles in research at the University of Guelph, GE Healthcare/Omnyx, Pathcore Inc., Sunnybrook Research Institute and Toronto Rehab Institute. She is a licensed Professional Engineer in Ontario and IEEE Senior Member. www.torontomu.ca/akhademi.