Tag: mammography

More Positive News on Mammo AI from MASAI

Posted on by Brian Casey

The latest results from the landmark MASAI study of AI for mammography screening show a favorable trend toward reducing the rate of interval cancers, or breast cancers that appear between screening rounds. The new findings – published Friday in The Lancet – also confirm mammography AI’s sharp workload reduction and trend toward higher sensitivity. 

MASAI is a large randomized controlled trial conducted in Sweden that examined the impact of ScreenPoint Medical’s Transpara AI algorithm on breast screening.

  • It’s an important issue, because mammography is one of the radiology segments where AI can provide the most help by reducing radiologist workload while improving cancer detection.

Previous MASAI studies demonstrated that AI can reduce radiologist workload by 44% and improve cancer detection rates by 28%.

  • The findings suggest that AI could eliminate the need for double-reading of most mammograms, a practice that’s common in European screening programs.

The new findings focus specifically on interval cancers, cancers that are missed in one screening round, only to be found later. 

  • Like other MASAI studies, the patient population consisted of 106k women screened with mammography and Transpara AI in Sweden’s national program in 2021 and 2022. 

Results indicated that AI-aided mammography…

  • Cut interval cancer rates by 12% per 1k women (1.55 vs. 1.76).
  • Reduced invasive interval cancers by 16% (75 vs. 89) with 27% fewer cancers of aggressive subtypes (43 vs. 59).
  • Detected 9% more cancers at screening (81% vs. 74%) with comparable specificity (99% for both) and recall rates (1.5% vs. 1.4%).

The researchers acknowledged that the study was not powered to show a statistically significant difference in the interval cancer rate. 

  • But its positive trend indicates that AI can be used to replace double-reading without negative consequences for patients – resulting in a sharp workload reduction for radiologists. 

The Takeaway

Results from the MASAI study on mammography AI just keep on getting better. Last week’s findings indicate that there’s really no reason for European breast screening programs to not dive in and replace their second readers with AI for the majority of exams.

Risk-Based Mammography Screening Returns

Posted on by Brian Casey

The idea of risk-based mammography screening is back with the publication of a new study in JAMA Network Open claiming that some risk-based strategies averted more breast cancer deaths with fewer false positives than age-based criteria. But like a previous paper on risk-based screening, the new findings raise concerns.

The idea behind risk-based screening is to focus healthcare resources on the people who need them most while sparing low-risk individuals from unnecessary medical interventions.

  • But risk-based breast cancer screening needs more clinical validation before it can be adopted broadly. This was tried with the WISDOM study, but researchers found no statistically significant difference in biopsy rates and only a modest reduction in mammograms performed.

A slightly different tack was taken with the new study, which compared conventional age-based biennial screening to a package of risk-based approaches based on a patient’s five-year breast cancer risk as calculated by widely accepted techniques like the Gail model and BCSC calculator.

  • Out of 50 risk-based strategies, nine averted more deaths than biennial age-based screening for women aged 40-74 (both were compared to no screening), and resulted in fewer false-positive recalls.

One such strategy highlighted by the authors used no screening for younger low-risk women, biennial screening for average-risk women, and annual screening for intermediate- and high-risk women, with the following results…

  • 6% more breast cancer deaths averted per 1k women versus conventional screening (7.2 vs. 6.8).
  • 8% fewer false-positive recalls (1,257 vs. 1,365).
  • While other risk-based strategies saw death reductions as high as 7.5 deaths per 1k women and false-positive reductions of 8-23%.

One key thing to note with the new study is its use of biennial screening as the control group, in line with current USPSTF recommendations for women aged 40-74. 

  • But many clinical organizations like ACR, ACOG, SBI, and NCCN recommend annual screening, and the new study’s findings may have been very different if compared to an annual model.

The Takeaway

This week’s findings are generally more supportive of risk-based screening than those of last year’s WISDOM study. But the new paper’s marginal improvement in cancer deaths averted might disappear when compared with annual age-based mammography. And like WISDOM, its use of clinical models for risk prediction may soon be obsolete given rapid developments in AI-based risk assessment. 

Breast Density’s Impact on Mammography

Posted on by Brian Casey

Breast density has a well-known effect on the accuracy of mammography screening – and it’s not a positive one. But a new study in Academic Radiology sheds light on density’s impact thanks to a massive patient population and its use of digital breast tomosynthesis, the most current breast screening technology.

Breast density is known to reduce the effectiveness of X-ray mammography by obscuring suspicious areas and making cancers harder to find. 

  • Women with dense breast tissue are typically directed to other imaging modalities for screening, such as ultrasound, breast MRI, and contrast-enhanced mammography.

The problem posed by breast density is significant enough that in 2024 the FDA implemented new MQSA rules requiring women getting screening mammograms to be notified of their density status.

  • It’s particularly important because having dense breast tissue is also a risk factor for breast cancer.

In the new study, MGH researchers aimed to quantify exactly how much breast density affects mammography screening through a large patient population screened with DBT, the state of the art in the U.S.

  • Researchers included 111.1k women who got DBT exams from 2013 to 2019 at their institution. 

They then calculated important metrics like sensitivity and specificity, as well as cancer detection and false-negative rates, across the four categories of dense breast tissue, from entirely fatty (A) to extremely dense (D), finding…

  • Sensitivity was lowest in extremely dense tissue compared to entirely fatty (62% vs. 93%).
  • Specificity was also lower for extremely dense and heterogeneously dense categories compared to entirely fatty (93% for both vs. 97%).
  • The false-negative rate for extremely dense tissue was over 8X that of entirely fatty based on adjusted odds ratio (aOR = 8.35).
  • While the abnormal interpretation rate was 57% higher for extremely dense versus entirely fatty tissue.

The Takeaway

The new findings are some of the most definitive yet on the negative effect breast density has on screening mammography’s accuracy and support the FDA’s 2024 notification requirement. They hopefully will spur development of new technologies to mitigate density’s impact. 

Risk-Based Mammo Screening – Ready for Prime Time?

Posted on by Brian Casey

Is mammography screening based on patient risk ready to take over for age-based screening? Results from the WISDOM study presented at last week’s San Antonio Breast Cancer Symposium and published simultaneously in JAMA suggest that while risk-based screening has its merits, more work may need to be done. 

Cancer screening exams like mammography have reduced disease-specific mortality, but (with the exception of lung cancer screening) all use exclusively age-based criteria to determine who should get screened.

  • Age isn’t a great tool for determining who’s at higher risk of getting cancer, but it’s the best tool we’ve had – up to now.

New cancer risk prediction tools are now becoming available, prompting debate over whether these techniques could make screening more precise by directing it to those most at risk.

  • Higher-risk people could get more frequent screening, while lower-risk individuals might be directed to longer screening intervals.

The WISDOM study presented at SABCS 2025 investigates this question. WISDOM is a randomized clinical trial that compared risk-based breast screening to age-based annual screening in 28.4k women followed for five years. 

  • Risk categorization was performed with genetic testing, polygenic risk scores, and BCSC scores, which incorporate family history and imaging results. 

Women in the risk-based screening group were directed into one of four screening strategies, from alternating mammography and MRI every six months for high-risk women to no screening until age 50 for low-risk women.

  • The study’s primary outcomes were detection rates for breast cancers rated as stage IIB or higher and effectiveness in reducing biopsy rates – a proxy for screening-caused morbidity.

Across the study population, researchers found…

  • The rate of mammograms per 100k person-years was lower in the risk-based cohort compared to age-based screening (43.1k vs. 46.9k). 
  • The rate of stage IIB or higher cancers per 100k person-years was also lower in the risk-based cohort (30 vs. 48).
  • But there was no statistically significant difference in biopsy rates, with a rate difference of 99 per 100k person-years (p = 0.10).

One problem with the WISDOM trial was that the actual screening exams were performed outside the study, and some patients did not comply with screening recommendations, potentially confounding results. 

The Takeaway

The WISDOM authors concluded that a risk-based screening approach is safe, but the lack of a difference in biopsy rates makes one wonder if veering from established age-based criteria is worth it. In any event, the coming arrival of risk stratification based on AI mammogram analysis could make the genetic testing-based approach used in WISDOM obsolete.

Mammo Screening Deserts Limit Access

Posted on by Brian Casey

It’s no secret that there are sharp regional differences in healthcare access in the U.S. But a new report puts a price on the access problem as it pertains to mammography – nearly 10k additional cases of breast cancer a year due to limited access in “cancer screening deserts” that don’t have mammography equipment. 

Mammography has been a success story among population-based cancer screening tests. 

  • The widespread implementation of breast screening in the 1980s is generally credited – along with improved treatments – with reducing breast cancer mortality by 44% from 1982 to 2022.

But breast cancer is still a lethal disease, killing 42k women a year in the U.S.

  • And screening’s benefits have not been distributed equally, with women in rural areas and those with lower socioeconomic status having lower completion rates.

What would it take to even out the differences? To answer this question, researchers from the Milken Institute analyzed the U.S. mammography installed base at the county level. 

  • They then correlated machine distribution with county population as well as cancer detection rates to find out how efficiently different counties were performing. 

They discovered…

  • High regional variation in mammography machine distribution.
  • The lowest distribution was in the Southwest and southern Midwest while the highest was in major urban areas, particularly on the coasts.
  • 890 counties did not have mammography machines.
  • Counties with the most mammography machines had 7.5% higher breast cancer incidence rates per 100k women compared to counties with no machines (329 vs. 306) – a sign they were detecting more cancers. 
  • There were 155 counties where mammography machine deployment would have the biggest return. 
  • And 9.6k breast cancer cases would be detected if counties with low or no mammography capacity detected breast cancer at the same rate as high-detection counties.

The new results track with another recent study that also revealed the presence of cancer screening deserts in the Southwest.

So what can be done? The Milken researchers proposed that low-resource counties be targeted for investment, but simply installing new machines won’t by itself cure the access problem. 

  • It’s also important to address barriers such as language, transportation, and cost-sharing in order to achieve equal access. 

The Takeaway

The new report shows that mammography access isn’t just an abstract issue – it’s one that is claiming the lives of thousands of U.S. women a year. Fortunately, the Milken researchers have done much of the legwork in identifying the specific areas that deserve attention. 

AI in Radiology: Old Problems, New Tech

Posted on by Partner Content

By Mo Abdolell, CEO, Densitas

Radiology has seen this movie before. Big promises (efficiency, accuracy, burnout relief). Big anxieties (ROI, workflow chaos, pressure to “keep up”). The question isn’t whether AI is powerful. It’s whether we’ve learned how to deploy new technology without repeating the pain of PACS migrations and the EHR era.

The Myth of the Perfect Rollout. Health technology assessment (HTA) sounds great in theory – rigorous, comprehensive, evidence-first. In practice, few organizations have the time, talent, or budget to execute it at scale. 

  • Remember EHRs: adoption happened because policy and money forced it, not because the playbook was tidy. Healthcare’s default pattern is to adopt, then evolve – messy, market-driven, and iterative. Waiting for perfect plans is how you get left behind.

Are AI’s Problems really new?

  • Black box déjà vu. Radiology has long trusted complex, opaque systems (reconstruction algorithms, vendor-specific pipelines). What mattered – and still matters – is validated performance and dependable outputs, not full internal transparency.
  • Model drift ≈ old friends. We’ve always recalibrated clinical tools as populations and scanners change. Monitoring and revalidation are known problems, not alien ones.

What’s Different This Time? Unlike the top-down EHR mandate, AI is largely market-driven. That gives providers agency. 

  • AI solutions must save time, improve outcomes, or avoid costs – not just publish a ROC curve. They must show operational value inside the native radiology workflow.

Fortunately, there are ways to adopt AI and then evolve your processes to make it work…

  • Workflow or bust. Demand in-viewer evidence objects, one-click report insertion, and EHR write-back. If AI adds steps, it subtracts value.
  • Start narrow, scale deliberately. Pick high-volume, high-friction tasks. Prove value in weeks, not years. Expand only when the operational signal is undeniable.
  • Measure what matters. Track operational metrics like seconds saved and coverage (e.g. eligible cases processed before dictation), reliability (e.g. results present before finalization, fail-open behavior), and user friction like context-switching rate and time-to-evidence.
  • Monitor. Stand up organization and site-level performance checks. Treat AI like equipment – scheduled, observed, and maintained.
  • Invest in long-term value. Favor standards, vendor-agnostic interoperability, clear telemetry, and transparent pricing.

The Takeaway

AI’s success in radiology won’t be defined by elegance of algorithms but by pragmatism of deployment. This will be an evolution – hands-on, incremental, sometimes messy. The difference now is that radiology can drive. Make the technology serve the service line – not the other way around.

Target the toughest workflows. Adapt and evolve with Densitas Breast Imaging AI Suite.

New Cancer Disparity Data Show Socioeconomic Impact

Posted on by Brian Casey

Cancer screening disparities continue to draw scrutiny in radiology. A new study in JAMA Network Open takes a closer look at why some people don’t get screened as often as they should – as well as the factors that contribute to cancer prevalence and mortality. 

There’s extensive research backing the lifesaving potential of the major cancer screening exams, and cancer mortality rates have consistently declined thanks to the combination of screening and better treatments. 

  • But the declines are uneven, prompting researchers to investigate reasons for the disparities, such as in a study earlier this month documenting geographic variations in cancer screening rates. 

In the new study, researchers from the ACR’s Harvey L. Neiman Health Policy Institute looked at how 24 measures like lifestyle, socioeconomic status, and environmental background affected breast, prostate, lung, and colorectal cancer, which account for 50% of new cancer cases.

  • In particular, they examined screening completion rates and cancer prevalence and mortality at the county level in a nationally representative sample of 5% of Medicare fee-for-service beneficiaries, of whom 87% were 65 years and older. 

There’s a lot to unpack in the study, but a few highlights are below as they relate to breast and lung cancer, the two cancers for which imaging-based screening is recommended. The top three factors affecting each (in order of importance) are…

  • Breast cancer:
    • Screening rates – Hispanic population share, levels of insufficient sleep, and poverty. 
    • Prevalence – uninsured status, obesity, and housing insecurity.
    • Mortality – non-Hispanic Black race, environmental justice index, and insufficient sleep.
  • Lung cancer:
    • Screening rates – air pollution exposure, lack of access to primary care physicians, and number of poor physical health days.
    • Prevalence – limited access to healthy foods, uninsured status, and severe housing problems.
    • Mortality – smoking, poor physical health days, and environmental justice index. 

While there are some obvious findings in the data (the connection between smoking and lung cancer mortality, for example), the dominance of socioeconomic measures may take some by surprise (or maybe not). 

  • But they do track with previous research finding that socioeconomic factors account for 40-50% of health impacts.

The Takeaway

The new study – as with previous research – reinforces what we know about the strong connection between socioeconomic status and cancer screening disparities. The new data should give clinicians and public health advocates more detail on the specific factors they need to focus on to improve screening compliance and reduce cancer’s burden on society.

Hologic to Go Private in $18.3B Buyout

Posted on by Brian Casey

Women’s imaging vendor Hologic will go private in an $18.3B buyout led by two private equity firms, Blackstone and TPG. The move is easily the largest acquisition in radiology this year – the question is how it will impact one of the biggest corporate success stories in women’s health. 

Hologic has a long history in medical imaging and was founded in 1985 to develop and market bone densitometry systems. It soon expanded into mammography, molecular diagnostics, and women’s health treatments.

  • The company went public in 1990, and has maintained its independence even as radiology underwent a period of consolidation in the 1990s and 2000s that saw most mid-cap firms get acquired by multinational OEMs.

Much of Hologic’s momentum was driven by the conversion of U.S. mammography facilities from standard 2D mammography to 3D digital breast tomosynthesis. 

  • This shift was led by Hologic’s Selenia Dimensions system, which in 2011 was the first DBT system to get FDA approval. Hologic rode its momentum to a U.S. mammography installed base market share approaching 70%. (Signify Research estimates Hologic currently has a 34% market share of the global mammography market.)

But as often happens to many market leaders, Hologic’s position began slipping in recent years. 

  • The multinational OEMs have improved their positions in women’s imaging, releasing DBT systems that are more competitive with Hologic’s offerings while also benefiting from multiyear purchasing agreements with large health systems in which mammography systems can be bundled with CT, MRI, and other equipment. 

Perhaps as a result, Hologic’s Breast Health segment has become a drag on revenue growth due to lower equipment sales. Breast Health revenues for the most recent Q3 period fell 5.8%, following a 6.9% drop in Q2 and a 2.1% decline in Q1. 

  • Indeed, reports began surfacing in May 2025 that Blackstone and TPG were targeting Hologic for acquisition, with Hologic reportedly rejecting a $16.7B offer. 

The bid was apparently sweetened, with an acquisition price of $79 a share, a 46% premium from before the acquisition rumors started, for a total value of $18.3B. The buyout should close in the first half of calendar 2026.

The Takeaway

Hologic built itself into a radiology success story through a combination of technological innovation and an obsessive focus on a single market segment – women’s health. The question is whether that focus will continue under its new PE-led ownership.

Cancer Screening Rates Vary Geographically

Posted on by Brian Casey

Progress has been made in some U.S. regions in boosting adherence rates for cancer screening exams like mammography, but clusters of regional variation remain. That’s according to a new study in JAMA Network Open that offers hope for reducing access disparities in disadvantaged areas.

Disparities in healthcare access remain one of the nagging problems in the U.S. healthcare system. 

  • Previous studies have shown that racial background, socioeconomic status, and geographic location can all affect access to care, and ultimately, patient outcomes.

Nowhere is this more apparent than in cancer screening, where getting patients in for their exams has always been a challenge. 

  • Screening compliance rates (as of 2021) were approximately 76% for breast cancer, 75% for cervical cancer, and 72% for colorectal cancer. 

But how does geography affect screening rates, and has progress been made over time? 

  • To answer these questions, researchers analyzed geographic variations in rates for the three major cancer screening tests (breast, cervical, and colorectal) over a 22-year period. 

Screening data were analyzed at the county level from 1997 to 2019, with screening prevalence estimated over 3-5-year periods. For mammography screening, authors found…

  • Screening rates were highest in the Northeast (Maine, New Hampshire, Vermont, and Massachusetts).
  • Rates were lowest in the Southwest (Texas, New Mexico, and Arizona).
  • Geographic areas that shifted from low to high uptake had lower socioeconomic status and more non-White residents, suggesting the success of efforts to improve screening in disadvantaged areas. 
  • Counties that did not improve had lower socioeconomic status than counties that maintained high screening rates. 
  • Rural areas had persistently low screening rates, reflecting lack of access to facilities as well as transportation. 

The Takeaway

The new study on geographic variation in cancer screening rates offers encouraging news that – at least in some disadvantaged areas – improving screening uptake is possible. But more research is needed to find out why some areas fail to see improvement. 

Perils of Missed Mammography

Posted on by Brian Casey

Yet another study is illustrating the perils of missing mammography screening. New research in JAMA Network Open found that women diagnosed with breast cancer who missed their previous screening exam had signs of delayed diagnosis and worse clinical outcomes. 

Mammography screening is generally credited – along with improved treatments – with a steady decline in breast cancer death rates since the start of population-based breast screening.

  • But most studies on mammography’s effectiveness tend to compare women who participated regularly in screening with those who never did. 

That’s not really a realistic comparison these days, as mammography’s relatively high compliance rate means that most women are getting screened at least some of the time.

  • But what happens if women miss a screening exam? In a BMJ study published last month, researchers found that women who missed their first screening exam had a 40% higher risk of breast cancer death.

In the current study, researchers took a slightly different tack, looking at 8.6k women in Sweden whose breast cancer was detected on screening exams starting in 2015. 

  • In all, 17% of women missed the screening exam immediately before their cancer diagnosis. 

Compared to women who attended all screening rounds, those who missed their previous exam had higher adjusted odds ratio for…

  • Larger tumors ≥ 20 mm (AOR = 1.55).
  • Lymph node involvement (AOR = 1.28).
  • Distant metastasis (AOR = 4.64).
  • Worse breast cancer-specific survival (AOR = 1.33).
  • Lower 20-year breast cancer-specific survival (86% vs. 89%). 

What’s more, the program’s cancer detection rate per 1k screenings was sharply higher in the second screening round for women who missed the first round (7.35 vs. 5.59). 

  • This is most likely a sign that cancers that could have been detected in the first round instead were detected in the second round – another sign of delayed diagnosis.

Women who had missed their previous screening tended to be younger, unemployed, unmarried, and born outside of Sweden, and also had lower income. 

  • Women with these characteristics could be targeted for more intensive outreach, such as shorter invitation intervals or outreach after a missed appointment. 

The Takeaway

The new study once again highlights the importance of regular mammography screening in detecting breast cancer. Even one missed exam can have serious clinical consequences – highlighting the importance of identifying and contacting women who might be more prone to missed appointments.

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