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expert reaction to interim safety analysis of randomised trial on AI-supported mammography screening

A study published in The Lancet Oncology looks at artificial intelligence-supported mammography screen reading versus the standard double reading.


Prof Fiona Gilbert, Professor of Radiology & Head of Department, University of Cambridge, said:

“This exciting, large, prospective mammography study shows that one reader using AI is comparable or better than the standard of two expert readers. There are considerable manpower savings which will translate favourably to the UK to help address our workforce issues. These findings will help plan the testing and implementation of AI into the UK national breast screening programme.”


Prof Stephen Duffy, Professor of Cancer Screening, Wolfson Institute of Population Health, Queen Mary University of London (QMUL), said:

“This paper presents interesting results of a high-quality study of artificial intelligence in breast screening. The results illustrate the potential for artificial intelligence to reduce the burden on radiologist’s time. This is an issue of considerable importance in many breast screening programmes, including the NHS Programme in the UK. The results indicate that this reduction in reading time can be achieved with an increase in detection capability. There may be concerns that such technology-driven increases in detection might include overdetection of relatively harmless lesions. For example, the results of this paper include an increase in detection of ductal carcinoma in situ, which is thought to be potentially overdiagnosed. The authors plan to address this issue by estimating the effect of incorporation of artificial intelligence on the rate of symptomatic cancers arising in future years in those who were screened negative. In the meantime, it would have been helpful to see the distribution of cancers detected by grade and biological subtype. If these were similar between the artificial intelligence group and the control group, fears of overdiagnosis would be lessened.”


Prof Dame Wendy Hall, Professor of Computer Science, University of Southampton, said:

“It is really great to see a paper like this on the application of AI in radiography. We need this type of evidenced-based research to support the claims that AI will help us improve healthcare. This is only one experiment but others will follow. The experiment needs to be replicated many times over before we can draw any general conclusions but it is very encouraging to see the positive results.”



Artificial intelligence-supported screen reading versus standard double reading in the Mammography Screening with Artificial Intelligence trial (MASAI): a clinical safety analysis of a randomised, controlled, non-inferiority, single-blinded, screening accuracy study’ by Kristina Lång et al. was published in The Lancet Oncology at 23:30 UK Time Tuesday 1 August 2023.

DOI: 10.1016/S1470-2045(23)00298-X



Declared interests

Prof Fiona Gilbert: “No conflicts.”

Prof Stephen Duffy: “No conflict to report.”

Prof Dame Wendy Hall: “No conflicts.”

For all other experts, no reply to our request for DOIs was received.




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