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Many radiographers lack understanding of how smart computer systems diagnose problems


A new study has shown that many radiographers in the UK have a limited understanding of how the new computer system diagnoses problems detected on scans such as X-rays, MRI. and CT scan.

Artificial Intelligence (AI) is at the top of being more widely introduced by x-ray departments. This research shows that we need to train radiographers so they can be sure of diagnosis, and know how to address the role of AI in radiology in patients and other healthcare practitioners.


Clare Rainey, lead researcher

Radiographers are specialists who meet with patients during the scan. They are trained to identify a variety of problems found on medical scans, such as broken bones, joint problems, and tumors, and have traditionally been considered to bridge the gap between patient and technology. There is a severe shortage in the country of radiographers and radiologists, and the NHS is about to introduce AI systems to help with diagnosis. Now a study presented at the UK Imaging and Oncology Conference in Liverpool (along with the simultaneously reviewed publication-see below) suggests that, despite the impressive performances reported by the developers of AI systems, many radiographers are unsure of how intelligent these new systems are.

Clare Rainey and Dr Sonyia McFadden from Ulster University surveyed Reporting Radiographers on their understanding of how AI works (a ‘Reporting Radiographer’ provides formal reports on x-ray images). In 86 radiographers surveyed, 53 (62%) said they were confident in how an AI system achieved its decision.However, less than a third of respondents were confident in communicating the AI ​​decision to stakeholders, including patients, carers and other healthcare practitioners.

The study also found that if the AI ​​confirmed their diagnosis then 57% of the respondents had a higher overall confidence in the search, however, if the AI ​​did not agree with their opinion then 70% would seek an additional opinion. .

Clare Rainey says:

This survey highlights UK issues reporting on the perspectives of AI radiographers used for image interpretation. There is no doubt that the introduction of AI represents a real step forward, but it shows that we need the resources to get into radiography education to ensure we can use this technology. Patients need to have confidence in how the radiologist or radiographer comes to an opinion“.

Modern forms of AI, in which computer-based systems learn as they go, are appearing in many areas of daily life, from self-taught robots in factories to self -driving cars and self -launching planes. Now the NHS is preparing to introduce these learning systems into their imaging services, such as x-rays and MRIs. It is not expected that these computerized systems will replace the final judgment of a skilled radiographer, however they may offer a high-level first, or second opinion on x-ray findings. This will help reduce the time required for diagnosis and treatment, as well as provide a backup ‘belt and braces’ to the person’s decision.

Clare Rainey says:

“It’s not strictly necessary for radiographers to understand everything 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 need to understand how the system makes the choices it makes, so that they can both decide whether to accept the findings, and be able to explain these choices to patients ”.

Since Clare Rainey cannot travel to Liverpool, this work was presented to UKIO by Dr Nick Woznitza. Dr. Woznitza comments:

“AI is really a different technique, with an exciting impact on what the scans tell us. My own team is working on how AI is applied to lung scans, with the potential to can help diagnose conditions that can be lung cancer with COVID“.

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

“Radiographers are positive about the introduction of AI, but like any new technology there is a learning process. As the authors point out, it calls for more investment in appropriately focused education and training.The introduction of Artificial Intelligence promises that the NHS will provide a more efficient and cost effective use of radiology resources, as well as a more reassuring experience for patients.We need to ensure that this investment in teaching and training is widely available to all radiographers to ensure we can do it best. technology ”.

Source:

UK Imaging and Oncology Congress (UKIO)



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