Debbie Anaby, PhD
Project Title
Transforming Breast Cancer Diagnosis: A Novel Approach for Diagnostic Precision
Named Grant
The Jacqueline and Arthur Burdorf Memorial Research Career Development Award
About the Investigator
Dr. Anaby’s research focuses on extracting quantitative insights from breast MRI scans using advanced image analysis and artificial intelligence. Her goal is to achieve early detection of breast cancer, reduce the number of biopsies, and provide valuable information to assist radiologists and clinicians in making accurate decisions regarding breast health. She received her BSc in Biochemical Engineering from the Technion and her MSc and PhD in advanced MRI techniques from Tel Aviv University. After her postdoctoral training at Cardiff University in Wales, she began her independent research in the Division of Diagnostic Imaging at the Sheba Medical Center, where she established the Breast Cancer Imaging Lab (BreaciL) and serves as its principal investigator.
About the Research
Breast radiology is often subjective and relies heavily on the radiologist’s experience. Breast MRIs contain a lot of information that radiologists may not fully use, but this information has the potential to greatly improve breast cancer diagnostics. Utilizing this data could save time, increase diagnostic accuracy, reduce the number of unnecessary biopsies or additional imaging tests, and help detect very small lesions that might be missed by the human eye.
Advanced image processing and artificial intelligence can help better understand the connection between MRI images and the biological processes happening in the breast. This can assist in distinguishing between cancerous and non-cancerous breast tumors, as well as between different types of cancerous tumors.
Dr. Anaby and her team aim to identify and extract unique information from breast MRIs to create an algorithm that can automatically detect and categorize suspicious areas in the breast. This new method will be tested on a large number of MRIs, including those with known cancerous and non-cancerous lesions. Special attention will be given to challenging cases, such as very small lesions that are harder to detect. After thorough testing and validation by institutional breast radiologists, this method will, ultimately, be developed into a user-friendly system that can be used by others.
