Tag: breast screening

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. 

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.

Mammography AI Predicts Cancer Before It’s Detected

Posted on by Brian Casey

A new study highlights the predictive power of AI for mammography screening – before cancers are even detected. Researchers in a study JAMA Network Open found that risk scores generated by Lunit’s Insight MMG algorithm predicted which women would develop breast cancer – years before radiologists found it on mammograms. 

Mammography image analysis has always been one of the most promising use cases for AI – even dating back to the days of computer-aided detection in the early 2000s. 

  • Most mammography AI developers have focused on helping radiologists identify suspicious lesions on mammograms, or triage low-risk studies so they don’t require extra review.

But a funny thing has happened during clinical use of these algorithms – radiologists found that AI-generated risk scores appeared to predict future breast cancers before they could be seen on mammograms. 

  • Insight MMG marks areas of concern and generates a risk score of 0-100 for the presence of breast cancer (higher numbers are worse). 

Researchers decided to investigate the risk scores’ predictive power by applying Insight MMG to screening mammography exams acquired in the BreastScreen Norway program over three biennial rounds of screening from 2004 to 2018. 

  • They then correlated AI risk scores to clinical outcomes in exams for 116k women for up to six years after the initial screening round.

Major findings of the study included … 

  • AI risk scores were higher for women who later developed cancer, 4-6 years before the cancer was detected.
  • The difference in risk scores increased over three screening rounds, from 21 points in the first round to 79 points in the third round.
  • Risk scores had very high accuracy by the third round (AUC=0.93).
  • AI scores were more accurate than existing risk tools like the Tyrer-Cuzick model.

How could AI risk scores be used in clinical practice? 

  • Women without detectable cancer but with high scores could be directed to shorter screening intervals or screening with supplemental modalities like ultrasound or MRI.

The Takeaway
It’s hard to overstate the significance of the new results. While AI for direct mammography image interpretation still seems to be having trouble catching on (just like CAD did), risk prediction is a use case that could direct more effective breast screening. The study is also a major coup for Lunit, continuing a string of impressive clinical results with the company’s technology.

Breast Cancer Mortality Falls Again

Posted on by Brian Casey

New data from the American Cancer Society highlight the remarkable strides that have been made against breast cancer, with the U.S. death rate falling 44% over the last 33 years – saving over half a million lives. But the statistics also underscore the work that remains to be done, particularly with minority women. 

The fight against breast cancer has been one of public health’s major success stories.

  • High mammography screening uptake has led to early detection of cancers that can then be treated with revolutionary new therapies. 

Much of the credit for this success goes to the women’s health movement, which has conducted effective advocacy campaigns that have led to …

But breast cancer remains the third most common killer of women after heart disease and lung cancer, and there have been disturbing trends even as the overall death rate falls. 

  • Breast cancer incidence has been rising especially in younger women, and major disparities continue to be seen, particularly with survival in Black women.

The American Cancer Society’s new report represents the group’s biennial review of breast cancer statistics, finding … 

  • In 2024 there will be 311k new cases of invasive breast cancer, 56.5k cases of DCIS, and 42.3k deaths. 
  • The breast cancer mortality rate has fallen 44% from 1989 to 2022, from 33 deaths per 100k women to 19 deaths.
  • Some 518k breast cancer deaths have been averted.
  • The mortality rate ranges from 39% higher than average for Black women to 38% lower for Asian American Pacific Islander women. 
  • The mortality rate is slightly higher than average (0.5%) for White women.
  • The average breast cancer incidence rate is 132 per 100k women, but ranges from 5% higher for White women to 21% lower for Hispanic women.
  • Women 50 years and older will account for most invasive cases (84%) and deaths (91%).

The Takeaway

As Breast Cancer Awareness Month begins, women’s health advocates should be heartened by the progress that’s been made overall. But battles remain, from eliminating patient out-of-pocket payments for follow-up studies to addressing race-based disparities in breast cancer mortality. In many ways, the fight is just beginning. 

The Cost of Extra Cancer Detection

Posted on by Brian Casey

It’s well known that using additional screening modalities beyond traditional 2D mammography can detect more cancers in women with dense breast tissue. But at what cost? A new study in Clinical Breast Cancer documents both the clinical value and the economic cost of supplemental breast imaging technologies. 

2D mammography is the basis for any breast cancer screening program, but the modality’s shortcomings are well known, especially in women with dense breasts. 

  • In fact, the FDA earlier this month began requiring breast imaging providers to notify women of their density status and explain how higher density is a breast cancer risk factor. 

Imaging vendors and clinicians have developed a range of technologies to supplement 2D mammography when needed, ranging from DBT to molecular breast imaging to breast MRI.

  • Each has its own advantages and disadvantages, which can leave many breast imaging providers confused about the best technology to use.

To shed some light, Matthew Covington, MD, of the University of Utah compared detection rates for various supplemental imaging modalities; he then estimated costs for each if it was the only modality used for supplemental imaging with 2D mammography in a U.S. population with 469k detectable breast cancers. 

  • The study assumed that 2D mammography would detect only 41% of cancers – leaving the majority undetected. 

Adding a supplemental modality boosted cancer detection rates, but also screening’s cost …

  • DBT detected 47% of all cancers at a cost of $933M
  • Ultrasound detected 51% at a cost of $1.84B
  • MBI detected 71% at a cost of $4.16B
  • Contrast-enhanced mammography detected 80% at a cost of $3.87B
  • MRI detected 100% at a cost of $6.36B

As the data indicate, MRI is clearly the most effective supplemental modality, but at a cost that’s almost 7X that of DBT. 

The Takeaway

The new data are a fascinating – if sobering – look at the intersection of clinical value and economic cost. They also highlight healthcare’s inconvenient truth: The resources needed to provide the highest-quality care are finite, regardless of whether you’re in a single-payor or fee-for-service system.

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