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U.S. State Insurance Bill
Pennsylvania has introduced insurance bill S88  which would eliminate cost sharing for diagnostic breast imaging and supplemental screening MRI, and for ultrasound when indicated.  For details on existing state insurance laws, please visit HERE.

UK News
Dense breast online lecture: Dr Fiona Gilbert, consultant radiologist at Cambridge University Hospital, led the groundbreaking BRAID study involving over 9,000 women, 85 of whom were diagnosed with early-stage breast cancer.  In this lecture, “Breast cancer screening and what to know about dense breasts,” Dr Gllbert will discuss what it means to have dense breasts, the results of the trial, and how breast cancer risk can be reduced.

Details: Monday 7 July, 2025, 6:30–7:30pm (BST – British Summer Time). For information and registration:  Microsoft Virtual Events Powered by Teams

New State Insurance Law
Florida is the latest state to expand insurance coverage requirements for breast imaging. NOTE: this limited law applies only to Florida state employee health contracts or plans. For details, visit DBI’s legislative resources:

• State Law Insurance Map
• State Law Insurance Table

Australia INFORM!
Breaking news from research scientist and founder of InforMD Wendy Ingman, “In a landmark policy change, BreastScreen Australia now recommends that breast density be reported to women as part of routine mammography screening.”  Find the Position Statement HERE. Congratulations to the advocates who have fought for this for nearly a decade!

New Study
Winham et al report on development and validation of mammographic parenchymal textural features that predict increased risk for breast cancer and also predict masking risk/ increased risk of interval cancer. They analyzed full-field digital screening mammograms from over 29,000 women at multiple centers and identified six breast parenchymal feature/texture types. The extracted types were then applied to a separate nested case-control cohort that included mammograms on over 1000 women with cancer.

1. The feature/texture types were significantly associated with both risk of developing cancer¹ and risk of masking².
2. These texture types did not distinguish higher or lower risk among women with dense breasts.
3. One texture type distinguished lower risk among women with non-dense breasts³.
4. The authors conclude that parenchymal textural features have potential to improve risk prediction and personalized screening strategies for women with high or low breast cancer risk.

The magnitudes of risk in this study were generally less than those associated with breast density, though this may help identify women at lower risk among those with non-dense breasts. Other studies have shown that textural features complement density in risk assessment and adding textural features to AI models of risk does appear to improve performance.

¹The highest risk types had odds ratio (OR) of 1.17 (95%CI 1.08, 1.27) and 1.12 (95%CI 1.03, 1.21) and the lowest 0.87 (95%CI 0.78, 0.96).  The greatest impact on identifying a subset of women with reduced risk was observed in Black women.
² The highest masking risk types had OR of 1.60 (95%Ci 1.24, 2.07) for false negative findings and 1.65 (95%CI 1.21, 2.26) for symptomatic interval cancer, and the lowest 0.63 (95%CI 0.45, 0.88) for false negatives and 0.63 (95%CI 0.42, 0.94) for interval cancer.
³ Odds ratio for breast cancer risk was 0.78 (95%CI 0.68, 0.89) for one texture type in non-dense breasts.

State Insurance Bills
Newly introduced state insurance bills to cover expanded breast imaging include the following:

• New Jersey A5542
• Wisconsin AB263
• Wisconsin AB264

European News: Just Published
Prevalence supplemental screening results from the randomized UK BRAID trial were published 5/21/2025 in The Lancet.  More than 9300 women with dense breasts and negative 2D mammogram aged 50-70 years were randomized to one of four screening groups (over 2000 women in each group): supplemental screening with abbreviated MRI (AB-MRI), automated whole breast ultrasound (ABUS), contrast-enhanced mammography (CEM), or standard of care (no supplemental screening).

Finding: Supplemental screening in women with dense breasts results in earlier detection, with AB-MRI and CEM finding more cancers than ABUS with higher recall rates.

• Cancer detection rates were higher for AB-MRI and CEM than for ABUS, but all modalities significantly increased cancer detection.¹
• Recall rates were higher for AB-MRI and CEM than for ABUS.²
• Among those women invited to supplemental screening, participation rates were highest among women invited to have ABUS.³
• All cancers detected were small, but cancers seen with contrast methods were smaller.³
• All cancers detected by ABUS were invasive, as were 82% and 86% detected by CEM and AB-MRI, respectively.³
• Just over 1% of women having CEM experienced a contrast reaction.⁴

Note: Added cancer detection rates in this study were higher than most prior reports for AB-MRI, ABUS, or CEM, likely because of longer interval between the initial mammogram and the supplemental screening (median 3-4 months, but up to one year).  Added yields are expected to be somewhat lower after tomosynthesis and in incidence screening.  Normal cases were offered a second round of screening at 18 months; interval cancer rates are not yet known as there has not been sufficient follow-up.

¹ Added cancer detection rates for AB-MRI, ABUS, and CEM were 17.4/1000, 4.2/1000, and 19.2/1000, respectively.  Cancer detection rates were significantly higher for AB-MRI and CEM than for ABUS.  A control group at Cambridge having only digital mammography had a cancer detection rate of 8.4/1000: supplemental contrast-enhanced screening more than doubled cancer detection.

² Recall rates were 9.7%, 4.0%, and 9.7%, for AB-MRI, ABUS, and CEM, respectively.

³ Approximately 95.5% of invited women completed ABUS vs. 91.8% AB-MRI and 91.1% CEM.

³ Median invasive cancer size for AB-MRI, ABUS, and CEM respectively was 10 mm (IQR: 8-15 mm), 22 mm (IQR: 14 – 35 mm) and 11 mm (7 – 15 mm). Invasive-only added cancer detection rates were: 15.0/1000, 4.2/1000, and 15.7/1000 for AB-MRI, ABUS, and CEM respectively.

⁴ Among 2035 women having CEM, 17 had minor contrast reactions (8.4 per 1000); 6 had moderate (2.9 per 1000) and 1 severe (0.5/1000).  There were no contrast reactions with MRI.  Another 3 women had contrast extravasation with CEM as did one (of 2130) with MRI).

State Insurance Bills

Two new state insurance bills for expanded breast imaging coverage have been introduced:

• New Jersey S4309
• Ohio HB271

Find It Early Act
As the 2025 Congressional session has begun, re-introduction of the federal Find it Early Act is scheduled. The Senate version has already been formally re-introduced (S1410), and the House bill re-introduction will follow soon.

New Study
Niu et al report on the effectiveness of primary screening with breast ultrasound among women in low-resource settings in rural China. 9100 women ages 35-64 underwent hand-held US (HHUS) and automated breast ultrasound (ABUS). Women over age 45 were also screened by mammography (MG).  All modalities were statistically equivalent but ABUS alone performed very well.

• The overall CDR was 2.7/1000 women screened and there were no statistical differences in sensitivity and specificity among the 3 screening methods, although the CDR of ABUS was greater than HHUS or MG.¹
• ABUS detected 2 cancers missed by HHUS and MG, and, in women with dense breasts, ABUS had the highest diagnostic performance of the 3 screening methods.²
• ABUS overall accuracy in women with non-dense breasts was comparable to HHUS and mammography.³
• The proportion of women with dense breasts among women aged 45-64 was 67.5%.

¹ There were 25 cancers among 9100 women screened, with CDR of 3.0 for ABUS, 2.3 for HHUS and 2.0 for MG per 1000 women screened.

² Note: BI-RADS 3 was considered “negative” in this analysis, but typically represents a “positive” screening test; 9.9% of ABUS examinations were assessed as BI-RADS 3 in women with dense breasts (as were 12.6% of HHUS and 13.1% of MG examinations). Among women with dense breasts, ABUS sensitivity was 81.8%, specificity (with BI-RADS 3 considered negative) was 98.5%, PPV3 16.7%, NPV 99.9%, and AUC 0.902.  Sensitivity of HHUS was 63.6% and of MG 54.6%, but differences were not significant.

³ Among women with non-dense breasts, sensitivity of all three modalities was 100%. ABUS specificity was 99.5%, PPV3 41.7%, NPV nearly 100% and AUC 0.998.

U.S. State Insurance Legislation Update

• New Law: Arkansas has amended its existing insurance law to include supplemental screening modalities, CEM, MRI, US and MBI and to eliminate cost sharing on diagnostic examinations.  For more details, please visit the DBI Legislation Map.
• New Bill: Colorado has introduced a new insurance bill for expanded breast imaging coverage, SB296.

New Study
In a single-center analysis from the United Kingdom, Payne et al reported results on 49,948 digital screening mammograms showing that increasing Volpara-based assessed breast density adversely affects screening mammography performance. They verified that the current quantitative Volpara threshold between category B, scattered fibroglandular density and C, heterogeneously dense, is appropriate, with worse performance in dense breasts.  Overall, 205/614 (33.4%) of cancers were symptomatically detected.

• Symptomatic interval cancer rates increased with each density category.¹
• Sensitivity decreased with each density category.²
• Recall rates were higher in dense breasts.³
• Cancer rates increased with increasing breast density.⁴

The authors suggest consideration of supplemental screening in women with extremely dense breasts and stress that the 3-year screening interval contributes to delayed diagnosis.  Currently, most women in the UK are not informed of their breast density, and supplemental screening is not widely available.

¹ Interval cancer rates at 3 year follow-up were: 1.8/1000 for category A, fatty breasts; 3.2/1000 for category B, scattered fibroglandular density; 5.7/1000 for category C, heterogeneously dense; and 7.9/1000 for extremely dense breasts.

² Sensitivity was: 75% in category A, fatty breasts; 73.5% in category B, scattered fibroglandular density; 59.8% in category C, heterogeneously dense breasts; and 51.3% in category D, extremely dense breasts (significantly worse in category C or D compared to B).

³ Recall rates were: 3% for category A; 4.5% for category B; 5.5% for category C; and 5.3% for category D.

⁴ Total cancer rates (screen-detected plus interval cancers) were: 7.4/1000 for category A; 12.2/1000 for category B; 14.2/1000 for category C; and 16.1/1000 for category D.