Tag: breast cancer

Patients Want Mammo AI, But Mostly As Backup

Posted on by Brian Casey

Patients support the idea of having AI review their screening mammograms – under certain conditions. That’s according to a new study in Radiology: Imaging Cancer that could have implications for breast imagers seeking to integrate AI into their practices.

Mammography screening has been identified as one of the most promising use cases for AI, but clinical adoption has been sluggish for reasons that range from low reimbursement to concerns about data privacy, security, algorithm bias, and transparency. 

  • Vendors and providers are working on solving many of the problems impeding greater AI use, but patient preference is an often overlooked factor – even as some providers are beginning to offer AI review services for which patients pay out of pocket.

To gain more insight into what patients want, researchers from the University of Texas Southwestern Medical Center surveyed 518 women who got screening mammography over eight months in 2023, finding …

  • 71% preferred that AI be used as a second reader along with a radiologist.
  • Only 4.4% accepted standalone AI interpretation of their images.
  • 74% wanted patient consent before AI review.
  • If AI found an abnormality, 89% wanted a radiologist to review their case, versus 51% who wanted AI to review abnormal findings by radiologists.
  • If AI missed a finding, 58% believed “everyone” should be accountable, while 15% said they would hold the AI manufacturer accountable. 

Patient preference for use of AI in collaboration with radiologists tracks with other recent research. 

  • Patients seem to want humans to retain oversight of AI, and seem to value trust, empathy, and accountability in healthcare – values associated with providers, not machines. 

The findings should also be good news for imaging services companies offering out-of-pocket AI review services. 

The Takeaway

The new findings should be encouraging not only for breast imagers and AI developers, but also for the imaging services companies that are banking on patients to shell out their own money for AI review. As insurance reimbursement for AI languishes, this may be the only way to move mammography AI forward in the short term.

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. 

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. 

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.

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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