Fiona Gilbert - FRCR, FRCPS, FACR, FRSE, FMedSci
Professor Gilbert, Department of Radiology, University of Cambridge.
As an academic radiologist she evaluates new imaging technology and how this impacts on patients health. Her particular clinical expertise is breast cancer. She is currently working on early cancer detection, biomarkers to predict cancer and response to neoadjuvant therapy, novel imaging techniques such as sodium imaging with MRI. She is working on Artificial Intelligence and the impact on radiology services and patient care. She has worked in developing AI algorithms with academic groups and commercial companies, is currently testing new research and commercial AI tools.
She has over 300 peer reviewed publications and has over £26 million in grant applications. She is a regular speaker at international Radiology conferences including RSNA in Chicago and ECR in Vienna. She is a member of the NIHR imaging science group and past President of the European Society of Breast Imaging. She has Honorary membership of Radiological Society of North America, Honorary Fellowship of the American College of Radiologists, Gold Medal from the European Society of Radiology, Fellowship of the Royal Society of Edinburgh and Fellowship of the Academy of Medical Sciences.
She has sat on a number of committees and funding Boards and is on a number of advisory panels. She is Lead advisor for AI for Clinical Radiology for the Royal College of Radiologists. She is a director of a public financial investment company NASCIT.
Research Workshop - Update on prospective UK AI trial in breast Screening - UK NIHR Trial
The EDITH trial (Early Detection using Information Technology in Health) has been funded by the NHS NIHR. The trial started on 1st August and is in set up phase. 15 sites will be set up in the first year with site agreements signed and connections made to the platform which will host the AI tools. The changes to NBSS have been agreed to allow triage of reading according to likelihood of cancer. The roll out of the triage arm will be ready in November 2026 when the NBSS changes have been implemented. The replacement of one of the readers arm will start in Spring 2026. Readers, will be given the chance to work with AI in live mode following a period of training.
Testing of the commercially available AI tools has been conducted on Philips and GE images and data collections of Hologic and Siemens images are on going.
A Continuous Monitoring System is being developed at Royal Surrey and this will be used to monitor changes in recall rates and time to results and assessment during the trial.
ASM - Formal breast density reporting – Is the UK ready?
Breast density is not recorded in the national breast screening programme but is extensively reported on mammograms in the symptomatic setting. The sensitivity and specificity of screening mammography is significantly reduced in dense breast tissue which has led a number of countries to inform women of their breast density and offer supplemental imaging with breast ultrasound. There is reluctance to alarm women by informing them of their density and offer nothing.
Density tools vary in how density is measured whether from raw data or processed images. There is not a standard by which tools are validated. Some use MRI volume of fibroglandular tissue while other companies use clinical assessment of density and map their digital assessment onto the BIRADS scoring system.
The UK needs to agree which density tools are acceptable, agree whether the four point BIRADS scale or a more detailed measure is used and amend NBSS to record density. Many mammography vendors give breast density measurement but readers do not always agree with these. There is disagreement between readers on which density score to give a case with overlap between c and d and between c and d.
The National Screening Committee has commissioned a cost effectiveness review to examine whether or not breast density should be recorded and supplemental imaging offered. The evidence on supplemental imaging will be reviewed together with tools to measure density.
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