As AI and its handmaiden, big data, make increasing inroads into healthcare, major U.S. and European radiology organizations have issued statements concerning the need to be proactive to ensure its ethical use in the field.

The multi-society statement — which focuses on data, algorithms and practice — appeared in the Journal of the American College of Radiology, Radiology, Insights into Imaging and the Canadian Association of Radiologists Journal.

“Radiologists remain ultimately responsible for patient care and will need to acquire new skills to do their best for patients in the new AI ecosystem,” said Dr. J. Raymond Geis, ACR Data Science Institute senior scientist and one of the paper’s leading contributors in an American Academy or Radiology statement.

The societies collaborating on the statement included the ACR, European Society of Radiology (ESR), Radiological Society of North America (RSNA), Society for Imaging Informatics in Medicine (SIIM), European Society of Medical Imaging Informatics (EuSoMII), Canadian Association of Radiologists (CAR) and American Association of Physicists in Medicine (AAPM).

"Developments in artificial intelligence represent one of the most exciting, and most challenging, changes in how radiology services will be delivered to patients in the near future,” noted Dr. Adrian Brady, chairperson of the ESR Quality, Safety and Standards Committee and co-author. “The potential for patient benefit from AI implementation is great, but there are also significant risks of unexpected or unplanned harmful effects of these changes.”

AI's great promise comes with significant risks to personal privacy, rights and freedom — as it contains the possibility of taking humans significantly out of much of the the decision process for diagnosis and treatment.

And as various AI systems have come online, albeit in preliminary and experimental forms, it has become clear to many observers that the field lacks “clear standards guiding its development and use,” note the authors, stressing that the ethical use of such systems in he field “should promote well-being and minimize harm resulting from potential pitfalls and inherent biases.”

The impact of AI will clearly be huge in radiology and “it is incumbent upon the radiology community to develop codes of ethics and practice to guide the utilization of this powerful technology and ensure the privacy and safety of patients,” said co-author Dr. Matthew B. Morgan, associate professor and director of IT and Quality Improvement in Breast Imaging, department of Radiology and Imaging Sciences, University of Utah, and member of the RSNA Radiology Informatics Committee.

There is also the international nature of AI. Guerbet and IBM Watson Health inked an agreement in late September to co-develop an AI solution to help clinicians diagnose and monitor patients with prostate cancer. In 2018, the two companies reached a deal to use AI for liver cancer.

Because of this international aspect of AI work, including rapid technology development and cross-border deployment of AI software, “an ethical framework for AI in radiology was much needed," stressed Dr. An Tang, chair of CAR's AI Working Group and co-author of the joint statement.

That said, there is no turning back from the use of big data and AI, as it continues to make inroads into many areas of diagnosis and treatment. “Applications of AI to patient care in imaging have great potential, both for good as well as unintended consequences,” said Dr. Marc D. Kohli, associate professor of radiology and biomedical imaging, medical director of imaging informatics for UCSF Health.

In order to allay such unintended issues, the authors stressed that in the end, human radiologists will need to remain involved, informed and vigilant as new tools come online.

“The application of AI tools in radiological practice lies in the hand of the radiologists, which also means that they have to be well-informed not only about the advantages they can offer to improve their services to patients, but also about the potential risks and pitfalls that might occur when implementing them,” said Dr. Erik R. Ranschaert, president of EuSoMII.

Cynthia McCollough, PhD, president of the AAPM stressed that the key lay in ensuring that variability and bias are minimized as machines and big data become more deeply ingrained into the fabric of healthcare delivery.

“In order for AI technology to positively impact human health, it is crucial that robust and reproducible data, methods, guidelines, and tools are developed and made available, she stressed, advising that “as quantitative and interdisciplinary scientists, medical physicists are playing an essential role in the development of these essential resources.”