AI and HealthCare, Author Interviews, Brain Cancer - Brain Tumors, Lancet, Mammograms / 30.01.2026
AI-Supported Mammography Screening Showed Consistently More Favourable outcomes Compared with Standard Screening
MedicalResearch.com Interview with:
[caption id="attachment_72182" align="alignleft" width="200"]
Dr. Lång[/caption]
Kristina Lång MD PhD
Associate professor, Diagnostic Radiology
Translational Medicine, Lund University
Senior consultant, Unilabs Mammography Unit
Skåne University Hospital, Malmö, Sweden
MedicalResearch.com: What is the background for this study?
Response: Prior to the start of the trial, several retrospective studies had shown that AI could discriminate between screening mammograms at low and high risk of cancer, with performance comparable to that of average breast radiologists. These findings suggested a potential to improve both the efficiency and sensitivity of mammography screening. This motivated us to design and evaluate an AI-supported screening procedure in a randomised controlled trial. The MASAI trial was among the first prospective studies in this field and, to date, remains the only randomised trial with reported results on the use of AI in breast cancer screening.
In European breast cancer screening programmes, every mammogram is usually read by two radiologists, so called double reading, to ensure a high sensitivity. In the MASAI trial we compared AI-supported mammography screening to standard double reading without AI. I
n the AI-supported approach, mammograms identified as low-risk by the AI were read by a single radiologist, while high-risk mammograms underwent double reading, with AI providing additional detection support.
Dr. Lång[/caption]
Kristina Lång MD PhD
Associate professor, Diagnostic Radiology
Translational Medicine, Lund University
Senior consultant, Unilabs Mammography Unit
Skåne University Hospital, Malmö, Sweden
MedicalResearch.com: What is the background for this study?
Response: Prior to the start of the trial, several retrospective studies had shown that AI could discriminate between screening mammograms at low and high risk of cancer, with performance comparable to that of average breast radiologists. These findings suggested a potential to improve both the efficiency and sensitivity of mammography screening. This motivated us to design and evaluate an AI-supported screening procedure in a randomised controlled trial. The MASAI trial was among the first prospective studies in this field and, to date, remains the only randomised trial with reported results on the use of AI in breast cancer screening.
In European breast cancer screening programmes, every mammogram is usually read by two radiologists, so called double reading, to ensure a high sensitivity. In the MASAI trial we compared AI-supported mammography screening to standard double reading without AI. I
n the AI-supported approach, mammograms identified as low-risk by the AI were read by a single radiologist, while high-risk mammograms underwent double reading, with AI providing additional detection support.