Tag: mammography

New Mammography AI Insights

Posted on by Brian Casey

Breast screening is becoming one of the most promising use cases for AI, but there’s still a lot we’re learning about it. A new study in Radiology: Artificial Intelligence revealed new insights into how well mammography AI performs in a screening environment. 

As we’ve reported in the past, mammography is one of radiology’s most challenging cancer screening exams, with radiologists sorting through large volumes of normal images before encountering a case that might be cancer.

In the new study, researchers applied Lunit’s Insight MMG algorithm to mammograms in a retrospective study of 136.7k women screened in British Columbia from 2019 to 2020. 

  • Canada uses single reading for mammography, unlike the double-reading protocols employed in the U.K. and Europe. 

AI’s performance was compared to single-reading radiologists using various metrics and follow-up periods, finding … 

  • At one-year follow-up, AI had slightly lower sensitivity (89% vs. 93%) and specificity (79% vs. 92%) compared to radiologists.
  • At two-year follow-up, there was no statistically significant difference in sensitivity between the two (83.5% vs. 84.3%, p=0.69). 
  • AI’s overall AUC at one year was 0.93, but this varied based on mammographic and demographic features, with AI performing better in cases with fatty versus dense breasts (0.96 vs. 0.84) and cases with architectural distortion (0.96 vs. 0.92) but worse in cases with calcifications (0.87 vs. 0.92).

The researchers then constructed hypothetical scenarios in which AI might be used to assist radiologists, finding …

  • If radiologists only read cases ruled abnormal by AI, it would reduce workload by 78%, but at a price of reduced sensitivity (86% vs. 93%) and 59 missed cancers across the cohort.

It’s worth noting that Insight MMG is designed to analyze 2D digital mammography exams.

The Takeaway

While the new findings aren’t a slam dunk for mammography AI, they do provide valuable insight into its performance that can inform future research, especially into areas where AI could use improvement. 

Has Breast Cancer Mortality Bottomed Out?

Posted on by Brian Casey

The decades-long decline in breast cancer mortality has been lauded as a major public health success story. But a new study in Journal of Breast Imaging suggests that the long decline in breast cancer death rates may be coming to an end, at least for some women.

Breast cancer mortality’s drop has been well-documented, with studies estimating the drop to range between 44% to 58% over the last three to four decades – saving at least 500k lives. 

  • Most experts believe the breast cancer mortality decline has been driven by a combination of organized mammography screening and better cancer treatments.

But amid the success are disturbing signs. Cancer incidence rates are increasing for women younger than 40 – the established starting age for screening. 

  • Mammography screening also has seen disparities in care that have resulted in higher incidence and death rates for women of color. 

In the new study, researchers examined U.S. data for breast cancer mortality from 1990 to 2022, finding that over the study period breast cancer mortality …

  • Fell by 44% for women of all ages and ethnicities over the full study period.
  • Decreased by -1.7% to -3.3% annually from 1990 to 2010, but the decline slowed to -1.2% a year from 2010 to 2022. 
  • Declined -2.8% per year for women 20-39 years old from 1990-2010, but showed no decline from 2010-2022.
  • Lowered by -1.3% per year for women older than 75 from 1993-2014, but showed no decline from 2013-2022. 
  • Declined for White and Black women of all ages, but not for Asian, Hispanic, and Native American women.
  • Was 39% higher for Black women compared to White women from 2004-2022.   

The authors acknowledge that much of their data pertain to women who are outside current screening guidelines. 

  • But they see this as an opportunity to revisit whether screening guidelines should be extended – especially to women 75 and older – to realize the benefits of early breast cancer detection. 

The Takeaway

The new findings on breast cancer mortality indicate that even as mammography’s successes are celebrated, more work remains to be done to ensure that breast screening’s benefits are enjoyed by as many women as possible. 

Screening Takes Center Stage at ECR 2025

Posted on by Brian Casey

New advances in cancer screening were among the major trends at last week’s ECR 2025 conference in Vienna. From traditional screening exams like mammography to up-and-coming tests like CT lung cancer exams, radiologists are emerging at the forefront of efforts to improve population health through early detection.

CT lung cancer screening is gaining momentum in Europe, and a Friday afternoon session explored the experiences of multiple sites…

  • U.K. researchers used DeepHealth’s Lung Nodules AI solution for automated triage of lung nodules found on non-screening CT chest exams, finding the approach could save £25k-£37k annually.
  • A German team documented technical lung CT acquisition parameters for screening centers in the SOLACE consortium across 10 countries, finding some room for improvement. 
  • Preliminary results from an Italian lung screening project were reported, with 2k people scanned with a 1.5% cancer detection rate (77% stage I-II) and 17% recall rate. Smoking cessation advice was also given.
  • Early results from a pilot screening project in Poland were given, with a 1.9% cancer detection rate in 3.1k people screened. They recommend screening be implemented nationwide. 
  • In a secondary analysis of 23.4k people in the NLST study, CT-derived body composition metrics predicted mortality beyond traditional risk factors.

Meanwhile, new ECR cancer screening research builds on the landmark accomplishments from 2024 in AI for breast screening. A Saturday afternoon session explored the progress being made…

  • German breast screening programs that deployed ScreenPoint Medical’s Transpara AI algorithm for 119k women saw their cancer detection rate grow (6 vs. 4.8 cancers per 1k) while the recall rate remained stable at around 2.5%. 
  • AI-supported double-reading in Italy for 120k women led to more breast cancers detected on baseline exams compared to subsequent screening rounds, as well as a 42% lower recall rate.
  • Patients found an AI chatbot based on GPT-4 generated responses to their questions that were more empathetic and readable than those of radiologists.
  • Another Italian study found that using AI for double-reading mammograms of 266k women led to a 21% increase in cancer detection rate and 15% drop in recall rate.
  • A secondary analysis of the MASAI trial suggested that double-reading with two radiologists continue to be used for high-risk women. Single reading of 3.8k high-risk exams resulted in 8.9% fewer detected cancers and 5.9% fewer recalls.

The Takeaway

Last week’s research on cancer screening at ECR 2025 shows that imaging experts see screening as a way to not only improve population health on a broad scale, but also to give radiologists the opportunity to raise their profile with patients and take a more direct role in patient care. The question is whether it’s an opportunity radiologists are ready to take.

Bridging Quality and Efficiency: Why Radiology Groups Are Adopting AI for Mammography Workflows

Posted on by Partner Content

By Dr. Roger Yang, President, University Radiology Group, and Mo Abdolell, CEO, Densitas

Radiology groups offering mammography services operate under ever-tightening demands, including MQSA EQUIP and ACR accreditation standards. Manual case selection, cumbersome paperwork, and lengthy review cycles often divert radiologists and technologists from what matters most – patient care.

But change is coming. By leveraging AI and mammography workflow automation, private radiology groups are reshaping how they manage quality, reduce administrative overhead, and advance patient care. 

AI-powered platforms can significantly streamline mammography quality management by:

  • Automating case selection for EQUIP reviews.
  • Measuring positioning metrics in near real-time.
  • Centralizing documentation to simplify compliance.

Some practices have reported up to a 90% reduction in EQUIP review time and 80% workload reduction in ACR accreditation using AI. But time savings are only part of the story.

Rather than waiting months for sporadic audits, technologists gain instant insights into positioning accuracy. This rapid feedback loop…

  • Accelerates targeted training.
  • Encourages continuous quality improvement.
  • Empowers technologists to self-monitor performance and identify gaps earlier. 

Today’s vendor-agnostic AI solutions integrate seamlessly with diverse imaging systems across multiple sites. 

  • Standards-based platforms can grow from a single mammography unit to dozens, helping radiology groups expand without adding complexity.

In a crowded marketplace, radiology practices that adopt AI-driven mammography quality management and automation stand out as forward-thinking leaders. Advantages include…

  • Enhancing patient perception: Offering efficient exams and high-quality imaging underscores a commitment to excellence, boosting satisfaction and referrals.
  • Leveraging analytics: Aggregated data on image quality and positioning helps leadership identify trends, optimize workflows, and highlight innovation.
  • Attracting top talent: Skilled technologists and radiologists gravitate toward practices with cutting-edge tools.

By integrating AI early, private practices can differentiate themselves, paving the way for growth and success.

Successful AI adoption and mammography workflow automation relies on more than just software. It requires:

  • Deep mammography expertise from vendors.
  • Robust training programs for staff.
  • Change training programs for staff.
  • Responsive customer support that fosters trust.

Mammography workflow automation cuts administrative burdens, curtails physician burnout, and speeds accreditation. Technologists receive clear, timely feedback, improving morale and performance. 

  • Meanwhile, patients benefit from streamlined workflows and consistent image quality, reinforcing trust in the practice.

The Takeaway

By embracing AI-driven mammography workflow automation and quality management, radiology groups can stay focused on delivering exceptional patient care while meeting regulatory requirements. This strategic investment propels private practices toward sustained growth and innovation, securing a competitive edge in a rapidly evolving healthcare landscape. Learn more.

Mammography Rates Fall for Women in 40s

Posted on by Brian Casey

A new study on mammography screening confirms the worst fears of women’s health advocates: screening rates fell for women ages 40-49 after the USPSTF in 2009 withdrew its recommendation that younger women get biennial screening.

Breast screening has long been the most controversial cancer screening exam, with screening’s opponents claiming that its “harms” – such as breast biopsies and overdiagnosis – don’t justify its benefits.

  • The anti-mammography wave crested in 2009 when the USPSTF withdrew its screening recommendation for women ages 40-49 and older than 75, instead advising them to consult with their physicians. 

The change prompted confusion and anger that persisted until the task force in 2024 rescinded the 2009 guidance and returned to a broad recommendation in favor of biennial screening for women in their 40s (screening still isn’t recommended for women over 74).

  • This left the breast imaging community pondering the impact that 15 years of the more restrictive guidance had on breast screening rates.

Researchers address that question in a new study in JAMA Network Open, in which they analyzed screening records for 1.6M women, finding the probability of getting a biennial mammogram …

  • Fell -1.1 percentage points for all women ages 40-49.
  • Fell -3 percentage points for non-Hispanic Black women 40-49, the biggest decline among younger women.
  • Fell -4.8 percentage points for all women 75 years and older.
  • Fell -6.2 percentage points for Hispanic women over age 75, the biggest decline among all age groups.

The new research confirms other studies finding that the USPSTF 2009 guidance led to a small – but statistically significant – decline in overall breast screening rates. 

  • What’s new is its discovery of demographic variations in the magnitude of the change, an important finding given recent studies showing that Black women have a 39% higher breast cancer mortality rate. 

In fact, rising cancer risk in Black women was cited by the USPSTF as one of its reasons for changing its guidance in 2024. 

  • The USPSTF estimated that lowering screening’s starting age to 40 would avert 1.8 additional deaths per 1k Black women screened every two years

The Takeaway

Hopefully, we’ve seen the end of the “mammography wars” that led to the USPSTF’s 2009 guideline change. A better future is one in which breast screening decisions are made with consideration for factors like cancer risk in addition to just age.

Hospital Slashes Mammography Backlog

Posted on by Brian Casey

A Michigan hospital was able to reduce its backlog of screening mammograms and speed up report turnaround time through a series of steps that included batched workflow and elimination of paper forms. Researchers describe their work in a new paper in Current Problems in Diagnostic Radiology. 

Mammography screening has always been a big challenge for breast radiologists, who typically read hundreds of normal mammograms before encountering an actual breast cancer. 

  • These challenges have only gotten worse with rising exam volumes and the well-documented shortage of radiologists, a combination that can lead to growing backlogs and longer report turnaround times. 

At the University of Michigan Health System, turnaround times for mammography reports had ballooned to 8.3 days, prompting researchers to investigate ways to make the breast imaging service more efficient. 

Study authors identified three main areas that slowed mammography TAT …

  • Interruptions during radiologist reading shifts.
  • Paper-based workflow. 
  • Cumbersome report dictation workflow.

So they developed a program called “Uninterrupted with Assistant” that eliminated the facility’s traditional reading model – eight-hour reading shifts in which radiologists were also responsible for other tasks like breast MRI and interventional procedures. 

  • Instead, they implemented four-hour shifts where radiologists batch-read mammograms without interruption. They were also aided by a clerical staff member as a “live transcriptionist” who reviewed charts and drafted pre-dictated reports in real time. 

The mammography service also ditched its paper workflow in favor of having patients complete intake forms on tablets, while technologists entered data on computers.

  • Finally, they updated their reporting to a standard template with pre-populated fields, based on FDA- and MQSA-approved verbiage. 

They then tested the Uninterrupted with Assistant program over 32 weeks in 2021, finding that during the program … 

  • Mean report turnaround time fell 39% (51 vs. 83 hours).
  • The institution’s TAT goal of less than 72 hours was achieved more often (93% vs. 35%).
  • Radiologists experienced fewer distractions (2.0 vs. 5.6 on a 10-point scale). 

The Takeaway

Batch reading isn’t new (neither is mammography worklist software), but combining the two with a ride-along assistant in the reading room creates a powerful productivity package. The Michigan model is an experience that can be emulated by other mammography centers struggling to improve efficiency and clear their backlog. 

Mobile Mammography’s Value

Posted on by Brian Casey

Despite the proven value of breast screening, compliance rates still aren’t as high as they should be. A new study in Clinical Breast Cancer shows how mobile mammography can improve screening adherence – especially among groups traditionally underserved in the healthcare system.

Estimates of mammography compliance vary – the American Cancer Society estimates that the overall U.S. breast screening rate held steady at 64-66% from 2000 to 2018. 

  • But a variety of factors can influence screening rates, from race to income to location.

Mobile mammography is an obvious solution that brings the imaging test to women rather than requiring them to travel. 

  • But some questions have persisted about mobile screening, such as whether it might cannibalize facility-based mammography programs, which have higher fixed costs. 

In the new study, researchers from the Harvey L. Neiman Health Policy Institute reviewed CMS claims data for 2.6M eligible women from 2004 to 2021. 

Researchers found …  

  • 50% of women had received a screening mammogram.
  • Only 0.4% used mobile mammography, but rates were higher in rural areas (1%) compared to large cities (0.3%) and small towns (0.4%).
  • American Indian or Alaska Native race was the factor most predictive for receiving mobile mammography (OR=5.5).
  • Other predictive factors included residence in a rural geography (OR=3.3), as well as in a community with lower income (OR=1.4).
  • Mobile mammography did not cannibalize facility-based mammography, based on data from heat maps showing utilization of both types of service.

Researchers concluded that mobile mammography can reduce health disparities by bringing imaging technology to underserved communities that might not otherwise have access to it. 

  • The findings echo a study earlier this year in which mobile mammography was also found to benefit the environment by reducing greenhouse gas emissions that occur when patients have to travel to medical facilities for screening.

The Takeaway

It may seem like a no-brainer to bring imaging to the people who need it, but the new study provides valuable evidence that the practice works on a national scale. Increased use of mobile imaging is an important tool for addressing persistent disparities in access to care. 

Mammo AI Kicks Off RSNA 2024

Posted on by Brian Casey

Welcome to RSNA 2024! This year’s meeting is starting with a bang, with two important sessions highlighting the key role AI can play in breast screening. 

Sunday’s presentations cap a year that’s seen the publication of several large studies demonstrating that AI can improve breast cancer screening while potentially reducing radiologist workload. 

  • That momentum is continuing at RSNA 2024, with morning and afternoon sessions on Sunday dedicated to mammography AI. 

Some findings from yesterday’s morning session include … 

  • Two AI algorithms were better than one when supporting radiologists in breast screening, with cancer detection ratios relative to historic performance rising from 0.97 to 1.08 with one AI to 1.09 to 1.14 with two algorithms.
  • ScreenPoint Medical’s Transpara algorithm was able to prioritize the worklist for 57% of breast screening exams by assigning risk scores to mammograms, helping reduce report turnaround times. 
  • iCAD’s ProFound AI software helped radiologists detect 7.8% more breast cancers on DBT exams, and cancers were detected at an earlier stage. 
  • Applying AI for breast screening to a racially diverse population yielded evenly distributed performance improvements.

Meanwhile, the Sunday afternoon session also included significant mammography AI presentations, such as …

  • A hybrid screening strategy – with suspicious breast cancer cases only recalled if the AI exhibits high certainty – reduced workload 50%. 
  • Lunit’s Insight DBT AI showed potential to reduce interval cancer rates in DBT screening by identifying 27% of false-negative and 36% of interval cancers.
  • In the ScreenTrustCAD trial in Sweden, using Lunit’s Insight MMG algorithm to replace a double-reading radiologist reduced workload 50% with comparable cancer detection rates.
  • A German screening program found that ScreenPoint Medical’s Transpara AI boosted the cancer detection rate by 8.7% (from 0.68% to 0.74%), with 8.8% of cancers solely detected by AI.
  • Researchers took a look back at abnormality scores from three commercially available AI algorithms after cancer diagnosis, finding evidence that cancers could be detected earlier. 

The Takeaway

Breast screening seems to be the clinical use case where radiologists need the most help, and Sunday’s sessions show the progress AI is making toward achieving that reality. 

Be sure to check back on our X, LinkedIn, and YouTube pages for more coverage of this week’s events in Chicago. And if you see us on the floor of McCormick Place, stop and say hello!

Studies Support Breast Ultrasound for Screening

Posted on by Brian Casey

A pair of new research studies offers guidance on when and where to use ultrasound for breast screening. The publications highlight the important advances being made in one of radiology’s most versatile modalities. 

Ultrasound is used in developed countries for supplementary breast cancer screening in women who may not be suitable for X-ray-based mammography due to issues like dense breast tissue.

  • Ultrasound is also being examined as a primary screening tool in developing regions like China and Africa, where access to mammography may be limited.

But despite growing use, there are still many questions about exactly when and where ultrasound is best employed in a breast screening role – and this week’s studies shed some light. 

First up is a study in Academic Radiology in which researchers compared second-look ultrasound to mammography in women with suspicious lesions found on breast MRI. 

  • Their goal was to find the best clinical path for working up MRI-detected lesions without performing too many unnecessary biopsies. 

In a group of 221 women, second-look ultrasound was largely superior to mammography with… 

  • Higher detection rates for mass lesions (56% vs. 17%).
  • A much higher detection rate for malignant mass lesions > 10 mm (89%).
  • But worse performance with malignant non-mass lesions (22% vs. 38%).

They concluded second-look ultrasound is a great tool for assessment and biopsy of MRI-detected lesions > 10 mm without calcifications. 

  • It’s not so great for suspicious non-mass lesions, which might be better sent to mammography for further workup. 

Breast ultrasound of non-mass lesions was also the focus of a second study, this one published in Radiology. 

  • Non-mass lesions are becoming more frequent as more women with dense breast tissue get supplemental screening, but incidence and malignancy rates are low. 

So how should they be managed? In a study of 993 women with non-mass lesions found on whole-breast handheld screening ultrasound, researchers classified by odds ratios the factors indicating malignancy…

  • Associated calcifications (OR=21.6).
  • Posterior shadowing (OR=6.9).
  • Segmental distribution (OR=6.2).
  • Mixed echogenicity (OR=5.0).
  • Larger size (2.6 vs. 1.9 mm).
  • Negative mammography (2.8% vs. 29%).

The Takeaway

Ultrasound’s value comes from its high prevalence, low cost, and ease of use, but in many ways clinicians are still exploring its optimal role in breast cancer screening. This week’s research studies should help.

ABUS Flies Solo for Breast Screening

Posted on by Brian Casey

Is breast ultrasound ready for use as a primary breast screening modality – without mammography? Maybe not in developed countries, but researchers in China gave automated breast ultrasound a try, with results that are worth checking out in a new study in AJR. 

Mammography is unquestionably the primary imaging modality for first-line breast screening, with other technologies like ultrasound and MRI taking a supplemental role, such as for working up questionable cases or for women with dense breast tissue.

  • But the standard mammography-dominated paradigm might not be suitable for some resource-challenged countries that have yet to build an installed base of X-ray-based mammography systems. 

One of these countries is China, which not only has fewer mammography systems in rural areas but also has a population of women who have denser breast tissue, which can cause problems with conventional mammography. 

  • As a result, the Chinese National Breast Cancer Screening Program has adopted ultrasound as its primary screening modality, with women ages 35-69 eligible for screening breast ultrasound every 2-3 years. Mammography is reserved for additional workup. 

But handheld ultrasound has challenges of its own. It’s operator-dependent, and image interpretation requires experienced radiologists – also in short supply in some Chinese regions.

  • So the AJR researchers performed a study of 6k women who were screened with GE HealthCare’s Invenia ABUS 2.0 scanner, which uses ultrasound to scan women lying in the supine position. Images were sent via teleradiology to expert radiologists at a remote institution.

How did ABUS perform as a primary screening modality? The researchers found that after a single round of screening …

  • ABUS had a cancer detection rate of 4.0 cancers per 1k women (4.4 for women 40-69).
  • Sensitivity was 92% and specificity was 88%.
  • Abnormal interpretation rate was 12%.
  • 96% of detected cancers were invasive, and 74% were node-negative.
  • Two interval cancers were detected (rate of 0.33 per 1k).

How do the numbers compare to mammography? 

  • The cancer detection rate in the Breast Cancer Surveillance Consortium study was 5.1 cancers per 1k women, so not far off. 

The Takeaway

The results offer an interesting look at an alternative to the mammography-first breast screening paradigm used in developed countries, where ABUS is mostly used as a supplemental technology. For resource-challenged areas around the world, ABUS with teleradiology could solve multiple problems at once.

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