By Dr. Declan O'Regan
Reader in Imaging Sciences, MRC London Institute of Medical Sciences
Dr Declan O’Regan is a Consultant Cardiac Radiologist and Reader in Imaging Sciences at the MRC London Institute of Medical Sciences within Imperial College London. He leads the Institute’s Robert Steiner MRI Facility and is also Director of Imaging Research at Imperial College Healthcare NHS Trust. His research is focussed on applying machine learning approaches to clinical imaging for understanding the genetic basis of heart disease and predicting patient outcomes. His multidisciplinary research is supported by the British Heart Foundation, Medical Research Council, and National Institute for Health research. He has a number of research collaborations worldwide and has recently been awarded the Roentgen (RCR) and Rohan-Williams (RANZCR) travelling professorships for a series of international talks on the use of artificial intelligence in radiology.
Tech investors have focused on radiology as a domain ripe for developing specialist algorithms that can interpret images. This is unquestionably one of the most exciting areas of biomedical research but the initial advances brought by AI will be less glamorous and directed at ensuring we get the most value out of the resources we already have.
Here are my five tentative predictions for how technology will change the way diagnostic imaging is conceived and delivered:
Imaging is a rich resource of prognostically-valuable data but making accurate predictions about the future progression of a disease depends on multiple interacting features at different scales that may be beyond human perception.
Machine learning is only as good as the quality of the training data – and the current vogue for deep learning networks requires very large datasets to prevent over-fitting. The only route to substantial progress is the development of accessible global registries that link image data with diagnoses and outcomes. As a community of healthcare users and providers we need to accept that the benefits of well-managed data sharing vastly outweigh the potential risks if there is robust protection of confidentiality and safeguards to prevent restrictive commercial exploitation. International standards for the validation of AI in medicine must be established and be a requirement for publication. The American College of Radiology should be congratulated for establishing a Data Science Institute to guide the appropriate development and implementation of AI tools to help radiologists improve medical imaging care.
Autopilots have not replaced humans and have been instrumental in improving the precision, economy and safety of air travel. The same might be expected for the use of automation in medical imaging if appropriate safeguards are in place. Instead of facing extinction, radiologists will be pivotal in this information revolution. If the evidence base is sound we owe it to our patients to embrace new AI technology and be pioneers of its adoption in healthcare.
June 15, 2022
June 09, 2022
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