AI mammography screening cuts aggressive breast cancer diagnoses by 12% in landmark trial

AI-assisted mammograms cut risk of developing aggressive breast cancer

Interval cancers are aggressive tumours that grow during the interval after someone has been screened for cancer and before they are screened again, and AI seems to be able to identify them at an early stage People who are screened for breast cancer by AI-supported radiologists are less likely to develop aggressive cancers before their next screening round than those who are screened by radiologists alone, raising hopes that AI-assisted screening could save lives. "This is the first randomised controlled trial on the use of AI in mammography screening," says Kristina Lång at Lund University in Sweden. The AI-supported approach involves using the software - which has been trained on more than 200,000 mammography scans from 10 countries - to rank the likelihood of cancer being present in mammograms on a scale of 1 to 10, based on visual patterns in the scans. The scans receiving a score of 1 to 9 are then assessed by one experienced radiologist, while scans receiving a score of 10 - indicating cancer is most likely to be present - are assessed by two experienced radiologists. An earlier study found that this approach could detect 29 per cent more cancers than standard screening, where each mammogram is assessed by two radiologists, without increasing the rate of false detections - where a growth is flagged but follow-up tests reveal it isn't actually there or wouldn't go on to cause problems. "That was terrific," says Fiona Gilbert at the University of Cambridge, who wasn't involved in the trial. Now, Lång and her colleagues have found that the AI approach also reduces the likelihood of people developing so-called interval cancers. These are tumours that develop rapidly in the time interval between screenings - hence the name - and that consequently tend to be particularly aggressive and more likely to spread elsewhere in the body. Lång and her colleagues made the discovery during an analysis of more than 100,000 women in Sweden, aged 55 on average. They randomly assigned about half of the women to receive their standard round of breast cancer screening, where each mammogram is assessed by two radiologists. The remaining participants were screened initially by the AI model - which was developed by biotech firm ScreenPoint Medical in Nijmegen, the Netherlands - and then the scans were assessed by radiologists, most of whom had at least five years of experience in analysing mammograms. The women who received the AI-assisted screening were 12 per cent less likely, on average, to develop an interval cancer than the women who received the standard screening. "When we got the results, we were extremely thrilled," says Lång. This result may be down to the fact that the AI is better able to detect cancers at a very early stage. So while radiologists might overlook small tumours that would develop into an interval cancer, the AI can spot them. Even so, the study was only designed to explore whether AI can work as well as standard screening, not to see if it can perform better, meaning further trials are needed to confirm it really is superior, says Lång. What's more, the team didn't assess whether the AI-supported approach performs better in certain ethnic groups. Further trials, including an ongoing trial in the UK, will help to address this, says Gilbert. Research should also be conducted to test whether less experienced radiologists see the same benefit when using AI, but Gilbert doesn't expect a huge difference. Off the back of these results, Lång expects the AI approach to be rolled out across south-west Sweden, where the trial was performed, within a few months. But it will probably take about five years for other countries to complete similar trials that justify the roll-out elsewhere, says Gilbert. "Countries need to see what the impact is on their own population, where people are screened more or less often, and are of different ethnicities," she says. They also need to establish whether the AI approach is cost-effective. By some estimates, AI assistance may be worth investing in if it cuts interval cancer rates by at least 5 per cent. Radiologists will also need to be trained, although that probably won't be too cumbersome as the software is fairly easy to use, says Lång. It's important to note that, even as AI improves, breast screening should always involve radiologists, says Lång. "Women that participate in screening say they do not want to have AI as a standalone tool, they want to have a human in the loop, and I agree with them. I think it's very important that it's a tool for radiologists," she says.

Is AI Better Than Radiologists at Interpreting Mammograms?

A commercially available artificial intelligence (AI) system can improve upon human-only mammogram screening but not replace radiologist readings, suggested the findings of a new study. Final results of the Mammography Screening with Artificial Intelligence (MASAI) trial, published in The Lancet, "demonstrated that AI-supported mammography screening outperformed standard double reading by radiologists," senior study author Kristina Lång, MD, PhD, senior consultant at the Unilabs Mammography Unit at Skåne University Hospital in Malmö, Sweden, told Medscape Medical News. The trial randomized 105,934 women in Sweden to either AI-supported mammography screening or the European standard of having two radiologists reading each mammogram without AI and compared outcomes of the two approaches. The study participants had digital breast tomosynthesis, also known as pseudo-three-dimensional (3D) mammography. AI-supported screening involved AI triage to single and double reading by radiologists, depending on the examination risk score, and using AI as detection support by highlighting suspicious areas. "AI support increased cancer detection by 29%, reduced interval cancers by 12%, and did not increase false positive recalls," Lång said. She added that previously published interim MASAI trial results reported that AI-supported screening reduced radiologists' screen-reading workload by 44%. "Together," Lång added, "these findings suggest that AI can enhance the early detection of clinically relevant breast cancers and may improve outcomes for women participating in screening programs." First Study of AI in Mammography The MASAI trial is the first randomized controlled trial evaluating the use of AI in mammography screening and the first to report on its effect on interval cancers, according to the study authors. Interval cancers are found after a negative screening but before the next scheduled screening. The trial used one commercially available AI system to interpret examinations in the intervention group. The AI system, trained, validated, and tested with more than 200,000 examinations from multiple institutions in the US, Asia and Europe, analyzed mammograms for suspicious findings, and provided an overall examination risk score ranging from 1 to 10. Scores of 1-9 were assigned to a single reading by a radiologist; scores of 10 were assigned to double reading by radiologists. During the 2-year follow-up, the study found a rate of 1.55 interval cancers per 1000 women in the AI-supported mammography group vs 1.76 in the standard care group, a 12% reduction in interval cancer diagnosis for the AI group. "The interval cancer rate is an important measure that reflects both the effectiveness of a screening program and the performance of the screening test itself," first author Jessie Gommers, a PhD student at Radboud University Medical Centre in Nijmegen, Netherlands, said. "Interval cancers are often more aggressive and are associated with poorer outcomes than cancers detected at screening. For this reason, the interval cancer rate is considered a central indicator of screening efficacy and is commonly used as a surrogate measure for breast cancer mortality." Additionally, the study found 16% fewer invasive, 21% fewer large, and 27% fewer aggressive sub-type cancers in the AI group. In the AI-supported group, 81% of cancer cases were detected at screening vs 74% in the standard reading group. The rate of false positives was similar in both groups: 1.5% and 1.4%, respectively. "A similar false positive rate indicates that AI-supported screening did not increase unnecessary recalls, which can cause anxiety and additional diagnostic procedures for women," Gommers said. The recalls prompted by AI were appropriate and were "largely limited to women who were ultimately diagnosed with breast cancer." The findings do not obviate a role for radiologists in breast cancer screening, Lång said. "In this study, AI did not replace radiologists." Instead, she said, it supported them by triaging exams for single or double reading and by highlighting suspicious areas. "Final recall decisions remained entirely with the radiologist," Lång added. "The results show that AI detection support helps radiologists avoid overlooking suspicious regions." The study's randomized design in a real-world screening "strengthens the validity of the findings," Lång said. "While replication in other screening programs will be important, the current results suggest that AI can help radiologists detect relevant cancers early without increasing unnecessary recalls." One limitation is that the study was conducted in southwest Sweden using a single AI system, "so additional research in diverse populations and with other AI tools is needed to strengthen the evidence for AI in mammography screening," Lång said. Also, the trial only covered a single screening round. "Longer-term data across multiple rounds would provide further insight into sustained effects," she said. Digital vs 3D Mammography The study results are not generalizable to breast cancer screening done in the US and other countries, Joann Elmore, MD, MPH, at the David Geffen School of Medicine at UCLA, told Medscape Medical News. "This MASAI trial evaluated the use of AI support tools on digital mammography examinations, but in the US most of the screening exams are now done with 3D tomography," Elmore said. She added that the double-reading standard in Europe is not usually done in the US. "Thus, this study needs to be repeated on 3D tomography exams and in health system that do not routinely double read all exams," Elmore said. "The reductions shown in the study should be interpreted cautiously until further studies can support the findings across multiple settings, multiple patient populations, and multiple AI algorithms," said Vignesh Arasu, MD, PhD, radiologist and research scientist at the Kaiser Permanente Division of Research in Northern California. Arasu noted the study was not powered to show superiority but rather noninferiority. "Even so, the findings suggest there may be a clinical benefit, and that AI could reduce interval cancers," he said. "I hope we see more studies that will attempt to answer this question." The MAISAI results also leaves open the question of whether 3D mammography would reduce the interval cancer rate vs digital breast tomosynthesis, Arasu added. More studies that look at the ability of AI to reduce interval cancers are needed, both Arasu and Elmore said. "There is also a need to look at the best ways to introduce AI into radiologist's workflows," Arasu said. Two potential pitfalls of AI supported mammography he cautioned about are the risk for overdiagnosis, especially for low-grade or indolent lesions, and a risk for over-reliance on a new technology. Elmore is a principal investigator of the PRISM trial (Pragmatic Randomized Trial of Artificial Intelligence for Screening Mammography), which launched last year. She said it will include about 400,000 3D tomography exams in the US interpreted with a radiologist assisted by an AI support platform or by radiologists only. "I would emphasize that the goal of PRISM is not to replace human expertise but to understand how AI might complement it," she said. "Our expert radiologists will continue to make the final call. AI may be a useful co-pilot, but it's the radiologist who holds the wheel." This study received funding from the Swedish Cancer Society. Lång reported financial relationships with Siemens Healthineers, N23 Health, and AstraZeneca. Gommers, Elmore, and Arasu reported having no relevant financial relationships. Richard Mark Kirkner is a medical journalist based in Philadelphia.

AI-supported mammography screening results in fewer aggressive and advanced breast cancers

Artificial intelligence (AI)-supported mammography identifies more cancers during screening and reduces the rate of breast cancer diagnosis by 12% in the years following, finds the first randomized controlled trial of its kind. The trial involved over 100,000 Swedish women, and its results are published in The Lancet. The interim safety results of the MASAI trial, published in The Lancet Oncology in 2023, found a 44% reduction in screen-reading workload for radiologists. Additionally, a different early analysis of the trial, published in The Lancet Digital Health, found a 29% increase in cancer detection without an increase in false positives. The full results of the latest trial show that AI-supported mammography also reduces cancer diagnoses in the years following a breast cancer screening appointment by 12% -- a key test of screening program effectiveness. What the trial found Lead author Dr. Kristina Lång from Lund University, Sweden, says, "Our study is the first randomized controlled trial investigating the use of AI in breast cancer screening and the largest to date looking at AI use in cancer screening in general. It finds that AI-supported screening improves the early detection of clinically relevant breast cancers, which leads to fewer aggressive or advanced cancers diagnosed in between screenings. "Widely rolling out AI-supported mammography in breast cancer screening programs could help reduce workload pressures among radiologists, as well as helping to detect more cancers at an early stage, including those with aggressive subtypes. "However, introducing AI in health care must be done cautiously, using tested AI tools and with continuous monitoring in place to ensure we have good data on how AI influences different regional and national screening programs and how that might vary over time." Why interval cancers remain a concern Mammography screening has been associated with a lower breast cancer death rate, largely due to the early detection and treatment of the cancer. However, despite European guidelines recommending two radiologists read mammograms, some cancers still go undetected in screening. Estimates suggest that 20-30% of breast cancers diagnosed after a negative screen and before the next scheduled screen (interval cancers) could have been spotted at the preceding mammogram. Interval cancers are often more aggressive or advanced than cancers detected during routine screening, making them harder to treat effectively. Previous observational studies and interim results of this trial have found AI-supported mammography increases breast cancer detection compared with standard screening. However, a key question has been if this increase in breast cancer detection translates into a reduction in interval cancers. How the Swedish trial was designed Between April 2021 and Dec 2022, over 100,000 women who were part of mammography screening at four sites in Sweden were randomly assigned to either AI-supported mammography screening (intervention arm) or to standard double reading by radiologists without AI (control arm). Double reading, where two radiologists read each mammogram, is standard practice in European screening programs. In the intervention arm, a specialist AI system analyzed the mammograms and triaged low-risk cases to single reading and high-risk cases to double reading performed by radiologists. The radiologists also used AI as detection support, in which it highlighted suspicious findings in the image. The AI system was trained, validated, and tested with more than 200,000 examinations from multiple institutions across more than ten countries. Key reductions in interval cancers During the two years of follow-up, there were 1.55 interval cancers per 1,000 women (82/53,043) in the AI-supported mammography group, compared to 1.76 interval cancers per 1,000 women (93/52,872) in the control group, a 12% reduction in interval cancer diagnosis for the AI arm. Additionally, there were 16% fewer invasive (75 v. 89), 21% fewer large (38 v. 48), and 27% fewer aggressive sub-type cancers (43 v. 59) in the AI group compared to the control arm. In the AI-supported mammography group, 81% of cancer cases (338/420) were detected at screening, compared to 74% of cancer cases (262/355) in the control group, a 9% increase. The rate of false positives was similar for both groups, at 1.5% in the intervention group and 1.4% in the control group. First author Jessie Gommers, Ph.D. student, Radboud University Medical Centre, Netherlands, says, "Our study does not support replacing health care professionals with AI, as the AI-supported mammography screening still requires at least one human radiologist to perform the screen reading, but with support from AI. However, our results potentially justify using AI to ease the substantial pressure on radiologists' workloads, enabling these experts to focus on other clinical tasks, which might shorten the waiting times for patients." Limitations and questions for future research The authors note several limitations, including that the analysis was conducted in one country (Sweden), was limited to one type of mammography device and one AI system which might limit the generalizability of the results. Additionally, in this trial, radiologists were moderately to highly experienced, which could limit the generalizability of the findings to less experienced radiologists. Lastly, information on race and ethnicity was not collected. Dr. Lång says, "Further studies on future screening rounds with this group of women and cost-effectiveness will help us understand the long-term benefits and risks of using AI-supported mammography screening. If they continue to suggest favorable outcomes for AI-supported mammography screening compared with standard screening, there could be a strong case for using AI in widespread mammography screening, especially as we face staff shortages."

AI use in breast cancer screening cuts rate of later diagnosis by 12%, study finds

Swedish study of 100,000 women found higher rate of early detection, suggesting potential to support radiologists The use of artificial intelligence in breast cancer screening reduces the rate of a cancer diagnosis by 12% in subsequent years and leads to a higher rate of early detection, according to the first trial of its kind. Researchers said the study was the largest to date looking at AI use in cancer screening. It involved 100,000 women in Sweden who were part of mammography screening and were randomly assigned to either AI-supported screening or to a standard reading by two radiologists between April 2021 and December 2022. The AI system worked by analysing the mammograms and assigning low-risk cases to a single reading and high-risk cases to a double one by radiologists, as well as highlighting suspicious findings to support radiologists. Mammography screening supported by AI reduced cancer diagnoses in the years after a breast screening appointment by 12%, according to the research, published in The Lancet. There were 1.55 cancers per 1,000 women in the AI-supported group compared with 1.76 cancers per 1,000 women in the control group. More than four in five cancer cases (81%) in the AI-supported mammography group were detected at the screening stage, compared with just under three quarters (74%) in the control group, and there were also almost a third (27%) fewer aggressive sub-type cancers in the AI group compared with the control. Dr Kristina Lång, from Lund University in Sweden and the lead author of the study, said that AI-supported mammography could help detect cancers at an early stage, but that there were caveats. "Widely rolling out AI-supported mammography in breast cancer screening programmes could help reduce workload pressures among radiologists, as well as helping to detect more cancers at an early stage, including those with aggressive subtypes," Lång said. "However, introducing AI in healthcare must be done cautiously, using tested AI tools and with continuous monitoring in place to ensure we have good data on how AI influences different regional and national screening programmes and how that might vary over time." Breast cancer is the leading cause of death in women aged 35 to 50, with more than 2 million people globally diagnosed with the disease each year. Although the study showed the apparent benefits AI could bring to mammography screening, the researchers do not support replacing healthcare professionals with AI, as screening still requires at least one human radiologist to perform the reading with AI support. Dr Sowmiya Moorthie, a senior strategic evidence manager at Cancer Research UK, said the findings were promising but urged caution. "Using AI to assist in reading mammograms can be more efficient, but there's a concern that it can lead to missing some cancers. This study helps to address concerns, but the results are from a single centre, so more research will be needed to know for sure if this will help save lives," Moorthie said. She added: "With a growing number of people expected to be diagnosed with cancer in the years ahead, innovations like this will be vital to improving the NHS, but it's important that they are properly evaluated to ensure people affected by cancer are helped rather than harmed." Simon Vincent, the chief scientific officer at Breast Cancer Now, said: "This first trial underlines the huge potential of AI to support radiologists in breast cancer screening. Screening is a vital tool for early detection, and the sooner the disease is found, the better chance of successful treatment. "This study shows real promise for earlier diagnosis that could improve and save lives, which is why trials launched last year in the UK exploring the use of AI within the NHS breast screening system will be important in determining the safest and most effective way to use these tools to find more cancers early."

AI helps doctors spot breast cancer in scans: world-first trial

Paris (France) (AFP) - Artificial intelligence helps doctors spot more cases of breast cancer when reading routine scans, a world-first trial found Friday. The results suggest countries should roll out programmes taking advantage of AI's scanning power to ease the workload of short-staffed radiologists, the Swedish lead researchers said. Well before the release of ChatGPT in 2022 raised global awareness about AI, scientists had been testing out the technology's capacity to read medical scans. But the new study published in The Lancet medical journal marks the first completed randomised controlled trial -- the gold standard for this kind of research -- looking at AI-supported breast cancer screening. The trial involved more than 100,000 women who received routine breast cancer scans across Sweden in 2021 and 2022. They were randomly sorted into two groups. In one, a single radiologist was assisted by an AI system to check the scans. The other followed the standard European method, which requires two radiologists to read the scans. Nine percent more cancer cases were spotted in the AI group compared to the control group. Over the following two years, those in the AI group also had a 12 percent lower rate of being diagnosed with cancer between routine scans, which are known as interval cancers and can be particularly dangerous. The improvement was consistent across different ages and levels of breast density, which can be risk factors. The rate of false positives was similar in both groups. Senior study author Kristina Lang of Sweden's Lund University said that "widely rolling out AI-supported mammography in breast cancer screening programmes could help reduce workload pressures amongst radiologists, as well as helping to detect more cancers at an early stage". But this must be done "cautiously" and with "continuous monitoring", she said in a statement. 'The radiologist's eye' Jean-Philippe Masson, head of the French National Federation of Radiologists, told AFP that "the radiologist's eye and experience must correct the AI's diagnosis". Sometimes the "AI tool will have seen a change in breast tissue that is not actually cancer," he added. The use of AI by radiologists is still in its "infancy" in France because these systems are expensive -- and prone to overdiagnosis, Masson warned. Stephen Duffy, emeritus professor of cancer screening at Queen Mary University of London who was not involved in the study, said it provided further evidence that AI-assisted cancer screening is safe. But he warned that the "reduction in interval cancers following screening in the AI group is not significant". He urged another follow-up of the trial's participants to see if the control group "catches up". Interim results from the trial, published in 2023, showed that AI nearly halved the time radiologists spent reading scans. The AI model Transpara was trained on more than 200,000 previous examinations taken in 10 countries. More than 2.3 million women were diagnosed with breast cancer and 670,000 died from the disease in 2022, according to the World Health Organization.

AI-assisted mammograms result in fewer aggressive and advanced breast cancers, study suggests

The AI was trained and tested with more than 200,000 breast exams from various institutions in more than 10 countries. AI-supported mammography results in fewer aggressive and advanced breast cancers, according to a study. It detected more women with clinically relevant cancers and the authors say there's a case for implementing it in screening programmes. The randomised control trial involved more than 100,000 Swedish women. Cancer diagnoses after AI-supported mammography were 12% lower, and the women were less likely to be diagnosed with more aggressive and advanced breast cancer in the years that followed. European guidelines recommend two radiologists read mammograms but some cancers still go undetected after screening. Estimates suggest 20-30% of breast cancers diagnosed after a negative screening and before the next scheduled one (interval cancers) could have been identified at the initial appointment. Previous studies and interim results of the Swedish trial found using AI increased detection compared with standard screening - but a key question has been if it translates into a reduction in interval cancers. The women who took part in the trial were randomly assigned to either AI-assisted screening or standard double reading by radiologists. The AI was trained and tested with more than 200,000 breast exams from more than 10 countries. During the two years that followed, there were 1.55 interval cancers per 1,000 women in the AI group, compared with 1.76 interval in the control group: a 12% reduction. Eight-one percent of cancer cases were also detected at screening that used AI, compared with 74% of cancer cases in the control group. The rate of false positives was similar for both groups, at 1.5% in the AI group and 1.4% in the control group. The results from the trial have been published in The Lancet medical journal. Read more from Sky News: X to block Grok AI from undressing images of real people Menopause 'triggers loss of brain matter' Lead author Dr Kristina Lang, from Lund University, said the study - which took place between 2021 and 2022 - was the biggest so far to look at AI use in cancer screening in general. "It finds that AI-supported screening improves the early detection of clinically relevant breast cancers, which led to fewer aggressive or advanced cancers diagnosed in between screenings," she said. Dr Lang said using AI in healthcare "must be done cautiously" with constant checks to "ensure we have good data on how AI influences different regional and national screening programmes". Jessie Gommers, a PhD student involved in the study, said AI-assisted mammography still needs at least one human radiologist but the results "potentially justify using AI to ease the substantial pressure on radiologists' workloads" - which could cut waiting times for patients.

AI-Assisted Mammograms Catch More Hard-To-Detect Breast Cancers, Clinical Trial Shows

By Dennis Thompson HealthDay ReporterFRIDAY, Jan. 30, 2026 (HealthDay News) -- Artificial intelligence (AI) can help reduce the number of breast cancers found between mammogram screenings, clinical trial results show. There was a 12% reduction in cancer diagnoses in the years following AI-supported breast cancer screening -- a key test of effectiveness, researchers reported Jan. 29 in The Lancet. Researchers previously reported a 29% increase in cancer detection without an increase in false positives when doctors used AI-supported mammography. "Our study is the first randomized controlled trial investigating the use of AI in breast cancer screening and the largest to date looking at AI use in cancer screening in general," said senior researcher Dr. Kristina Lang, an associate professor at Lund University in Sweden. "It finds that AI-supported screening improves the early detection of clinically relevant breast cancers, which led to fewer aggressive or advanced cancers diagnosed in between screenings," Lang said in a news release. Previous studies have estimated that as many as 30% of breast cancers diagnosed after a negative screening could have been spotted from that mammogram, researchers said in background notes. Doctors and researchers have been training AI programs to help improve analysis of mammograms, with the aim of catching those hard-to-see cancers. However, it's been an open question whether AI-aided breast cancer screening actually translates into a reduction in cancers found between mammograms, researchers said. For this new study, more than 100,000 Swedish women undergoing mammography screening were assigned to either AI-supported mammography or standard screening, in which two radiologists evaluated each mammogram. The screenings took place between April 2021 and December 2022. The AI used in this clinical trial had been trained and tested using more than 200,000 prior examinations from multiple hospitals across more than 10 countries, researchers said. In the AI-supported mammogram group, 81% of cancer cases were detected at screening compared to 74% in the standard screening group, the study said. Between screenings, about 1.55 cancers per 1,000 women were detected in the AI group and 1.76 per 1,000 in the control group. Cancers also tended to be caught at an earlier, more treatable stage with AI assistance. There were 16% fewer invasive cancers, 21% fewer large cancers and 27% fewer aggressive cancers in the AI group compared to standard screening, the study said. The rates of false positives were about the same, 1.5% in the AI group and 1.4% in the control group. "Our study does not support replacing health care professionals with AI as the AI-supported mammography screening still requires at least one human radiologist to perform the screen reading, but with support from AI," said lead researcher Jessie Gommers, a doctoral student at Radboud University Medical Center in The Netherlands. "However, our results potentially justify using AI to ease the substantial pressure on radiologists' workloads, enabling these experts to focus on other clinical tasks, which might shorten the waiting times for patients," Gommers said in a news release. Earlier results reported from the clinical trial showed a 44% reduction in radiologists' workload with AI assistance. However, more study is needed to see if AI could help breast cancer screening in other countries, or could help less experienced radiologists read mammograms, researchers said. "Further studies on future screening rounds with this group of women and cost-effectiveness will help us understand the long-term benefits and risks of using AI-supported mammography screening," Lang said. "If they continue to suggest favorable outcomes for AI-supported mammography screening compared with standard screening, there could be a strong case for using AI in widespread mammography screening, especially as we face staff shortages," she said. More information The U.S. Centers for Disease Control and Prevention has more on breast cancer screening. SOURCE: The Lancet, news release, Jan. 29, 2026