Category: Breast Imaging

Health Inequity & Breast Cancer

Posted on by Brian Casey

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?

Posted on by Brian Casey

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. 

FDA Finally Moves on Breast Density

Posted on by Brian Casey

After a long wait, the FDA issued a final rule that adds details on breast density reporting to the Mammography Quality Standards Act. The rule takes effect in September 2024 and should go a long way toward clarifying the issue of breast density for patients. 

Breast tissue density is a risk factor for cancer, and dense breast tissue can make it more difficult for radiologists to identify tumors on conventional x-ray mammography. This shortcoming is often not communicated to women who receive “normal” mammograms, but later find out that a cancer was missed.

Prodded by a strong patient advocacy movement, individual states have been passing laws requiring women to be notified of their density status, creating a patchwork of regulation across the U.S. 

The FDA in 2018 agreed to set a national standard by rolling breast density reporting into an update of the MQSA. But the long wait has frustrated many in the breast density advocacy movement.

There are several major components to the new rule, which: 

  • Requires breast imaging facilities to provide patients with a summary of the mammography report written in lay terms that identifies whether patients have dense or non-dense breast tissue.
  • Instructs facilities to include a section in the mammography report explaining the significance of breast density. 
  • Establishes four categories for reporting breast tissue density in the mammography report. 
  • Sets the specific language to be used for reporting density. 

The new rules provide much-needed national consistency in breast density reporting, and will replace the patchwork of state regulation that has developed over the years. Developers of breast density software may also benefit from the new federal rules, as they simplify the number of regulations that need to be tracked. 

The Takeaway

Better late than never. While the FDA should have signed off on this years ago, now that the rules are issued the breast imaging community can move ahead with integrating them into clinical practice. The new rules should also help density reporting software developers by setting a national standard rather than a patchwork of state regulation. 

Multimodal AI Virtual Breast Biopsies

Posted on by Jake Fishman

Radiology Journal detailed a multimodal AI solution that can classify breast lesion subtypes using mammograms, potentially reducing unnecessary biopsies and improving biopsy interpretations. 

Researchers from Israel and IBM/Merative first pretrained a deep learning model with 26k digital mammograms to classify images (malignant, benign, or normal), and used these pretraining weights to develop a lesion subtype classification model trained with mammograms and clinical data. Finally, they trained a pair of lesion classification models using digital mammograms linked to biopsy results from 2,120 women in Israel and 1,642 women in the US. 

When the Israel AI model was tested against mammograms from 441 Israeli women it…

  • Predicted malignancy with an 0.88 AUC
  • Classified ductal carcinoma in situ, invasive carcinomas, or benign lesions with 0.76, 0.85, and 0.82 AUCs
  • Correctly interpreted 98.7% of malignant mammographic examinations and 74.6% of invasive carcinomas (matching three radiologists)
  • Would have prevented 13% of unnecessary biopsies and missed 1.3% of malignancies (at 99% sensitivity)

When the US AI model was tested against mammograms from 344 US women it…

  • Predicted malignancy with a lower 0.80 AUC
  • Classified ductal carcinoma in situ, invasive carcinomas, or benign lesions with lower 0.74, 0.83, and 0.72 AUCs 
  • Correctly interpreted 96.8% of malignant mammographic examinations and 63% of invasive carcinomas (matching three radiologists)

The authors attributed the US model’s lower accuracy to its smaller training dataset, and noted that the two models’ also had worse performance when tested against data from the other country (US model w/Israel data, Israel model w/ US data) or when classifying rare lesion types. 

However, they were still bullish about this approach with enough training data, and noted the future potential to add other imaging modalities and genetic information to further enhance multimodal breast cancer assessments.

The Takeaway 

We’ve historically relied on biopsy results to classify breast lesion subtypes, and that will remain true for quite a while. However, this study shows that multimodal-trained AI can extract far more information from mammograms, while potentially reducing unnecessary biopsies and improving the accuracy of the biopsies that are performed.

iSono Health’s Wearable Breast Ultrasound

Posted on by Jake Fishman

iSono Health announced the FDA clearance of its ATUSA automated wearable 3D breast ultrasound system, a first-of-its-kind device that taps into some of the biggest trends in imaging.

The wearable ATUSA system automatically captures the entire breast volume, producing standardized/repeatable breast ultrasound exams in two minutes without requiring a trained operator. The scanner combines with iSono’s ATUSA Software Suite to support real-time 2D visualization, advanced 3D visualization and localization, and AI integration (including iSono’s forthcoming AI tools). That positions the ATUSA for a range of interesting use cases:

  • Enhancing routine exams in primary care and women’s health clinics
  • Expanding breast imaging access in developing countries
  • Supporting longitudinal monitoring for higher-risk women
  • Allowing remote breast cancer monitoring

iSono might have to overcome some pretty big biases regarding how and where providers believe breast exams are supposed to take place. However, the ATUSA’s intended use cases and value propositions have already been gaining momentum across imaging.

  • The rapid expansion of handheld POCUS systems and AI guidance solutions has made ultrasound an everyday tool for far more clinicians than just a few years ago.
  • Wearable imaging continues to be an innovation hotspot, including a range of interesting projects that are developing imaging helmets, patches, and even a few other wearable breast ultrasound systems.
  • There’s a growing focus on addressing the developing world’s imaging gap with portable imaging systems.
  • We’re seeing greater momentum towards technology-enabled enhancements to routine breast exams, including Siemens Healthineers’ recent move to distribute UE LifeSciences’ iBreastExam device (uses vibrations, not imaging).
  • At-home imaging is becoming a far more realistic idea, with commercial initiatives from companies like Butterfly and Pulsenmore in place, and earlier-stage efforts from other breast ultrasound startups. 

The Takeaway

iSono Health has a long way to go before it earns an established role in breast cancer pathways. However, the ATUSA’s use cases and value proposition are well aligned with some of imaging’s biggest trends, and there’s still plenty of demand to improve breast imaging access and efficiency across the world.

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