Research: Many radiographers don’t understand how smart computer systems diagnose problems

A new study shows that many UK radiographers have a limited understanding of how new smart computer systems diagnose problems found on scans such as X-rays, MRI and CT scans.

Artificial intelligence (AI) is about to be introduced more widely in X-ray departments. This research shows that we need to train radiographers to be sure of the diagnosis and how to discuss the role of AI in radiology with patients and other healthcare providers.


Clare Rainey, Principal Investigator

Radiographers are the specialists who meet with patients at the time of the scan. They are trained to recognize the variety of problems found on medical scans, such as broken bones, joint problems and tumors, and have traditionally been considered a bridge between the patient and technology. There is a serious national shortage of radiographers and radiologists, and the NHS is about to introduce AI systems to facilitate diagnosis. Now, a study presented at the UK Imaging and Oncology Conference in Liverpool (with concurrent peer-reviewed publication – see below) suggests that, despite impressive performance reported by developers of AI systems, many radiographers aren’t sure how these new smart systems work.

Clare Rainey and Dr Sonyia McFadden of Ulster University surveyed Reporting Radiographers on their understanding of how AI worked (a ‘Reporting Radiographer’ provides formal reports on X-ray images). Of the 86 radiographers surveyed, 53 (62%) said they are confident in how an AI system makes its decision, but less than a third of respondents would trust that it informs stakeholders, including patients , caregivers and other caregivers, would communicate.

The survey also found that if the AI ​​confirmed their diagnosis, 57% of respondents would have more general confidence in the finding, but if the AI ​​disagreed with their opinion, 70% would request an additional opinion.

Clare Rainey said:

This study highlights issues with radiographers in the UK’s perception of AI being used for image interpretation. There is no doubt that the introduction of AI is a real step forward, but this shows that we need resources to go into radiography education to ensure that we can make the most of this technology. Patients should have confidence in how the radiologist or radiographer arrives at a judgment

Modern forms of AI, where computer-based systems learn along the way, are appearing in many places in everyday life, from machine learning robots in factories to self-driving cars and self-landing planes. Now the NHS is preparing to introduce these learning systems into their imaging services, such as X-rays and MRIs. These automated systems are not expected to replace the final judgment of a skilled radiographer, but they can provide a high-level first or second opinion on X-ray findings. This will help shorten the time needed for diagnosis and treatment, as well as give a ‘belt and brace’ back-up for human decisions.

Clare Rainey said:

“It’s not strictly necessary for radiographers to understand everything about how these AI systems work; after all, I don’t understand how my TV or smartphone works, but I know how to use them. However, they do need to understand how the system makes the choices it makes.” it makes, so they can both decide whether to accept the findings, and explain these choices to patients.”

As Clare Rainey cannot travel to Liverpool, this work is presented at the UKIO by Dr. Nick Woznitza. Dr. Woznitza noted:

“AI is really a set of techniques, which can have an exciting impact on what scans can tell us. My own group is working on how AI is applied to lung scans, which has the potential to help diagnose conditions from lung cancer to COVID

UKIO President, Dr. Rizwan Malik (Bolton NHS Foundation Trust) commented:

“Radiographers are positive about the introduction of AI, but as with any new technology there is a learning process. As the authors point out, this calls for greater investment in appropriately targeted education and training. The introduction of artificial intelligence promises that the NHS will more efficient and cost-effective use of radiological resources and a more reassuring experience for patients. technology”.

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