ABUS Boosts Breast Screening

Automated breast ultrasound led to sharp increases in cancer detection rates and sensitivity when it was performed as a supplement to screening digital mammography in a study of Asian women. 

In Radiology, researchers from South Korea explain the shortcomings of X-ray-based mammography, which has limited sensitivity in women with dense breast tissue. Handheld ultrasound can be used as a screening supplement, but it has drawbacks of its own, such as longer exam time and operator variability. 

ABUS has been proposed as an alternative, acquiring 3D volumes of the entire breast in an automated mode that’s more structured and standardized. ABUS also provides coronal-plane images that can help differentiate malignant from benign lesions.

But most of the studies validating ABUS have been conducted on Western women, and Asian women tend to have mammographically denser breasts.

So researchers decided to test ABUS as a supplement to digital mammography with 2,301 South Korean women who were screened from 2018 to 2019. Women were first screened with digital mammography (either Hologic’s Selenia Dimensions or Siemens Healthineers’ Mammomat Revelation), then received ABUS scans with GE HealthCare’s Invenia ABUS system. 

For women with dense breasts, screening with ABUS and DM turned in better performance than DM alone in multiple categories, including:

  • Higher cancer detection rate per 1,000 screening exams (9.3 vs. 6.5)
  • Better sensitivity (90.9% vs. 63.6%)
  • Higher AUC (0.89 vs. 0.79)
  • Detection of smaller cancers, with a mean size of 1.2 cm vs. 2.3 cm

On the down side, ABUS + DM in women with dense breasts had lower specificity (86.8% vs. 94.6%), driving higher biopsy rates (3.3% vs. 1.9%) and false-positive biopsy rates (2.4% vs. 1.3%).

The Takeaway

In a time when breast cancer inequities are under the microscope, the new study provides encouraging news that imaging technology can help compensate for the shortcomings of the traditional “one size fits all” paradigm of breast screening. 

The results are also a shot in the arm for ABUS as it seeks to cement a role as a complement to X-ray-based screening mammography, although work remains to be done in improving specificity and recall rates.

Health Inequity & Breast Cancer

The last several years have seen growing awareness of how structural inequities can impact individual health outcomes. Two powerful new JAMA Network Open studies reinforced what we know about structural inequity, particularly as it relates to breast cancer. 

In the first study on April 19 addressing racial differences in breast cancer mortality, researchers looked at over 415k women from 2011 to 2020, finding:

  • Black women between 40 and 49 years old had the highest breast cancer mortality rates per 100,000 person years, at 27 deaths. This compares to 15 deaths for White women, and 11 deaths for other ethnicities.
  • If breast screening were tailored based on risk at age 50, Black women should start screening eight years earlier than White women, at 42 years of age versus 51. 
  • Biennial mammography screening of Black women starting at age 40 would reduce the gap in breast cancer mortality compared to White women by 57%. 

In the second study on April 21, researchers drilled even deeper into structural inequity, focusing on breast cancer outcomes in disadvantaged neighborhoods in a large, racially diverse region in southern Florida that’s home to 6.2M people. 

In all, their study covered 5,027 women with breast cancer, and they categorized neighborhoods into three levels based on socioeconomic status. Findings included:

  • Patients living in the second most disadvantaged neighborhoods were 36% more likely to die of breast cancer (HR=1.36).  
  • Women living in the most disadvantaged neighborhoods were 77% more likely to die (HR=1.77).

The researchers pointed out that their results went beyond merely linking race to health outcomes, as they adjusted for race and ethnicity “as a proxy for structural racism.” They suggested that there could be “unaccounted,” biologic mechanisms related to neighborhood disadvantage that lead to shorter breast cancer survival. The findings echo other studies that have linked patient location to access to imaging.

The Takeaway

Over the past several decades, breast cancer’s dropping mortality rate has been a health policy success story. But the new studies indicate that progress has been uneven, and more attention is needed to ensure that the benefits of improved breast cancer diagnosis and treatment are distributed more equitably.

Breast Screening’s New Gold Standard?

A new study in Radiology on the use of digital breast tomosynthesis for breast screening makes the case that DBT has so many advantages over conventional 2D digital mammography that it should be considered the gold standard for breast screening. 

Unlike 2D mammography, DBT systems scan around the breast in an arc, acquiring multiple breast images that are combined into 3D volumes. The technique is believed to be more effective in revealing pathology that might be obscured on 2D projections.

Previous research already demonstrated the effectiveness of DBT for certain uses, but the new study is notable for its large patient population, as well as its focus on general screening rather than subgroups like women with cancer risk factors such as dense breast tissue.

Researchers led by Dr. Emily Conant of the University of Pennsylvania reviewed DBT’s performance in five large U.S. healthcare systems, with a total study population of over 1 million women. 

The advantages of DBT were notable:

  • Higher cancer detection rate: 5.5 vs. 4.5 per 1k women screened
  • Lower recall rate:  8.9% vs. 10.3%
  • Higher recall PPV: 5.9% vs. 4.3%.

On the negative side, DBT had higher biopsy rates, of 17.6 biopsies per 1,000 women versus 14.5 biopsies for 2D digital mammography. But PPV of biopsy for both techniques was largely the same. 

Researchers note that breast cancer mortality rates have fallen 41% since 1989, a development attributed to earlier diagnosis and better treatment. DBT could help accelerate this trend as it finds more cancers relative to 2D digital mammography.

The Takeaway

This study reinforces the idea that DBT is now the gold standard for breast screening. While mammography vendors have already seen high market penetration for DBT systems, the new study is likely to convince any remaining holdouts that 3D mammography is a necessary technology for any breast imaging facility. 

iCAD and Solis CVD Alliance

iCAD and major breast imaging center company Solis Mammography announced plans to develop and commercialize AI that quantifies breast arterial calcifications (BACs) in mammograms to identify women with high cardiovascular disease (CVD) risks.

Through the multi-year alliance, iCAD and Solis will expand upon iCAD’s flagship ProFound AI solution’s ability to detect and quantify BACs, with the goal of helping radiologists identify women with high CVD risks and guide them into care.

iCAD and Solis’ expansion into cardiovascular disease screening wasn’t exactly expected, but recent trends certainly suggest that commercial AI-based BAC detection could be on the way: 

  • There’s also mounting academic and commercial momentum behind using AI to “opportunistically” screen for incidental findings in scans that were performed for other reasons (e.g. analyzing CTs for CAC scores, osteoporosis, or lung nodules).
  • Despite being the leading cause of death in the US, it appears that we’re a long way from formal heart disease screening programs, making the already-established mammography screening pathway an unlikely alternative.
  • Volpara and Microsoft are also working on a mammography AI product that detects and quantifies BACs. In other words, three of the biggest companies in breast imaging (at least) and one of the biggest tech companies in the world are all currently developing AI-based BAC screening solutions.

The Takeaway

Widespread adoption of mammography AI-based cardiovascular disease screening might seem like a longshot to many readers who often view incidentals as a burden and have grown weary of early-stage AI announcements… and they might be right. That said, there’s plenty of evidence suggesting that a solution like this would help detect more early-stage heart disease using scans that are already being performed.

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