RSNA 2026 Honorary Member

Andrea G. Rockall, FRCR


Andrea G. Rockall, BSc, MBBS, FRCR, MRCP
Rockall

An internationally recognized expert in genitourinary imaging with a deep understanding of machine-learning (ML) applications in radiology, Andrea G. Rockall, FRCR, is clinical chair of radiology at Imperial College London and honorary consultant radiologist at Imperial College Healthcare NHS Trust. Her special interests are in genitourinary cancer, image-based clinical trials, machine-learning and sustainability in radiology.

“Professor Rockall’s exceptional career reflects the very highest ideals of our profession. Her internationally recognized scholarship in genitourinary and oncologic imaging, influential research and contributions to evidence-based tools have advanced diagnostic confidence and patient care,” said RSNA President, Jeffrey S. Klein, MD. “RSNA is honored to recognize a physician-scientist, educator and leader whose innovation, service and commitment continue to shape the future of radiology worldwide.”

Dr. Rockall presided over the European Congress of Radiology in 2025 under the theme of Planet Radiology, focusing on the environmental impact of radiology. She is now the past president of the European Society of Radiology (ESR), having previously served as chair of the ESR Board of Directors. She is also the former chair of the ESR National Societies Committees. Through her work with the ESR sustainability sub-committee, she launched the Green Imaging Department (Green ID) scheme.

Dr. Rockall was chief investigator of several multicenter studies, including CRUK and NIHR-funded studies in the fields of machine learning, novel PET tracers and MRI in ovarian cancer and prostate cancer. She was the co-investigator and senior author for the prospective multicentre study that established the evidence base for O-RADS MRI score, which was published in JAMA Network Open.

She is also currently involved in several projects conducting life cycle assessment in radiology, including energy usage and data storage modelling, as well as life cycle assessment of entire diagnostic pathways, to evaluate the best strategies to reduce greenhouse gas emissions and waste in radiology departments.