Interim insights into supplemental breast imaging for dense breasts: lessons from the BRAID trial

The management of women with mammographically dense breasts remains one of the most debated and unresolved challenges in contemporary breast cancer screening.

Breast density is not only a well-established risk factor for breast cancer, but also a major determinant of reduced mammographic sensitivity (1-3). Across organised European screening programmes, approximately 5-10% of women aged 50–70 years are classified as having extremely dense breasts [American College of Radiology Breast Imaging Reporting and Data System (ACR BI-RADS) category D], while 40-50% fall into categories ACR BI-RADS C or D combined (4).

Despite growing recognition of the dual role of breast density as both a risk factor and a limitation of mammography, however, consensus on the optimal use of supplemental imaging remains elusive, and many national screening programmes continue to adopt a uniform approach without systematic adaptation based on density. Over the past decade, a range of additional techniques, including ultrasound-based approaches and contrast-enhanced modalities, have been proposed, often supported by heterogeneous evidence and indirect comparisons (5-7). In this context, the results of the Breast Screening: Risk-Adaptive Imaging for Density (BRAID) randomised controlled trial, recently published in The Lancet (8), provide long-awaited comparative evidence about supplemental imaging strategies in this population, providing a direct comparison of abbreviated MRI (AB-MRI), automated whole-breast ultrasound (ABUS), and contrast-enhanced mammography (CEM) within a pragmatic screening framework.

The interim analysis of BRAID results delivers timely and clinically relevant data, offering the first head-to-head evaluation of three widely discussed supplemental imaging strategies in women with dense breasts and negative mammography. Interim results demonstrate the striking superiority of contrast-based techniques over ABUS, evidenced by substantially higher cancer detection rates, with smaller tumour size and predominantly node-negative disease, in line with prior observational studies and meta-analyses (5,6). AB-MRI and CEM achieved similarly high cancer detection rates (17.4 and 19.2 per 1,000 examinations, respectively), detecting comparable numbers of invasive cancers (15.0 vs. 15.7 per 1,000) compared with approximately 4 cancers per 1,000 examinations detected by ABUS. Median invasive tumour size was 10 mm for AB-MRI, 11 mm for CEM, and 22 mm for ABUS. Although CEM detected a slightly higher proportion of ductal carcinoma in situ, no statistically significant difference in overall cancer detection was observed between the two contrast-enhanced techniques.

These findings acquire particular relevance when interpreted within a randomised, real-world screening design. Notably, the study population largely reflects women at average risk, underscoring the potential applicability of the results beyond traditional high-risk cohorts.

The BRAID trial challenges the “one-size-fits-all” paradigm and strengthens the case for risk-adapted screening. If implemented at scale, contrast-based supplemental imaging in women with dense breasts could lead to the detection of thousands of additional cancers annually. The potential downstream effect on stage distribution and breast cancer mortality warrants serious consideration. However, enthusiasm must be tempered by a balanced appraisal of broader consequences.

The magnitude of the observed differences, both in detection rates and tumour size, provides a quantitative estimate of the diagnostic trade-offs associated with different supplemental imaging strategies at this interim stage.

As with any interim analysis, the BRAID results must be interpreted within their appropriate temporal and methodological context. The trial was not designed to address long-term outcomes such as interval cancer reduction, overdiagnosis, or breast cancer-specific mortality—endpoints that require extended follow-up and, in some cases, complementary modelling approaches. Interim detection metrics therefore represent necessary but insufficient indicators of screening benefit and should be viewed as an intermediate waypoint rather than a definitive assessment of modality effectiveness.

Beyond absolute differences in cancer detection, the BRAID interim data help clarify why contrast-enhanced techniques outperform ultrasound-based approaches in women with dense breasts. Both AB-MRI and CEM exploit tumour angiogenesis and vascular permeability, reducing reliance on morphological features alone and directly addressing the masking effect of fibroglandular tissue. This biological mechanism provides a plausible explanation for the smaller tumour size and early-stage disease observed with contrast-enhanced imaging and supports interpretation of these findings as modality-related rather than centre-specific effects.

In contrast, ABUS represents a different balance between feasibility and sensitivity. In BRAID, ABUS achieved a cancer detection rate of about 4 per 1,000 examinations (vs. 17–19 per 1,000 of contrast-enhanced techniques), slightly higher but within the same order of magnitude as prior reports (9-11). However, the lower detection yield and the larger median tumour size highlight an inherent trade-off that should not be interpreted as a limitation of ultrasound per se, but rather as evidence that supplemental modalities occupy distinct positions along a sensitivity-specificity-resource continuum. Such distinctions are critical when considering population-level implementation and reinforce the need for context-aware imaging strategies.

Beyond detection, the interim BRAID data provide quantitative insights into recall burden and safety profiles. Recall rates were higher for both contrast-enhanced modalities, with 9.7% of women recalled after AB-MRI and CEM, compared with 4.0% for ABUS. These differences translated into biopsy rates of 4.9%, 4.4%, and 1.5%, respectively, revealing the diagnostic trade-off associated with increased sensitivity.

Importantly, both recall and biopsy rates varied across centres, reflecting differences in reader experience and workflow rather than intrinsic modality performance alone. Evidence from prior screening trials (10,12) suggests that recall rates tend to decrease substantially in subsequent rounds as reader familiarity increases and prior examinations become available. The interim nature of BRAID therefore limits the interpretation of early recall and biopsy rates as stable indicators of long-term programme performance and highlights the importance of distinguishing intrinsic modality performance from implementation-dependent effects.

Safety profiles differed across modalities as well: as expected, no adverse events were reported with ABUS; AB-MRI was associated with a single contrast extravasation (approximately 0.5 per 1,000 examinations); and CEM was associated with iodinated contrast reactions in 11.8 per 1,000 examinations, predominantly minor, alongside rare moderate and severe events.

In spite of the undeniable value of the data provided by the BRAID trial, some critical considerations remain unaddressed. First, the acceptability of supplemental imaging from women's perspectives is unclear, particularly regarding their willingness to accept increased screening burdens for uncertain benefit. Real-world implementation must account for the fact that women's preferences regarding screening intensity and trade-offs may vary considerably: some women might prioritise maximising cancer detection, accepting higher recall rates, while others might value minimising anxiety and avoiding unnecessary procedures. Future implementation of supplemental imaging strategies, if pursued, should consider patient-reported outcomes and incorporate shared decision-making approaches that clearly communicate absolute benefits and harms. Policy recommendations would need to balance clinical effectiveness with acceptability to maintain adequate screening participation.

Second, the economic implications of scaling contrast-enhanced imaging within population-based programmes have not been evaluated, raising questions about sustainability and resource allocation. Cost implications are substantial, including direct costs (equipment, contrast agents, personnel), increased recall and biopsy workload, and downstream treatment expenses. Comprehensive health economic analyses incorporating long-term outcomes and system-wide resource implications would be needed before advocating for widespread adoption based on detection metrics alone.

A third possible concern regarding the potential implementation of supplemental imaging involves the risk of exacerbating existing inequalities in breast cancer outcomes through differential access to advanced breast imaging technologies.

In addition, even though the BRAID trial focuses on breast density as an isolated criterion, a more comprehensive approach should integrate density within multifactorial risk prediction models including family history, reproductive factors, polygenic risk scores, and prior breast malignancy, that may “interact” with density in determining optimal screening strategies.

A particularly informative context for interpreting the BRAID interim findings is the follow-up of women with a personal history of breast cancer (PHBC). Although distinct from population screening, post-treatment surveillance shares several defining features with screening, including asymptomatic imaging at regular intervals and a primary focus on early detection. In this setting, breast density remains a critical determinant of imaging performance, particularly in younger women and in those treated with breast-conserving therapy.

Accumulating evidence and expert consensus have highlighted the limitations of mammography alone in the follow-up of women with PHBC and dense breasts (13-16). Contrast-enhanced techniques, in particular MRI and, more recently, CEM, have demonstrated improved sensitivity for detecting ipsilateral recurrence and contralateral disease, often at an earlier stage than conventional imaging. These advantages have been observed in populations that, similar to those enrolled in BRAID, are not necessarily characterised by high genetic risk but remain vulnerable to delayed diagnosis due to tissue density and post-treatment changes. European expert recommendations have begun to reflect this evolving evidence base (17), acknowledging the role of contrast-enhanced imaging in selected follow-up scenarios and positioning CEM as a pragmatic alternative to MRI where resource or patient-related constraints limit access.

Seen in a broader clinical perspective, the BRAID interim findings move beyond the boundaries of screening alone, strengthening a biologically coherent narrative spanning screening, surveillance, and diagnostic problem solving, in which contrast-enhanced imaging adds value wherever breast density limits morphology-based assessment. In doing so, the BRAID trial provides timely and meaningful evidence to the ongoing debate on the role of supplemental imaging for women with dense breasts.

By allowing a pragmatic randomised comparison of AB-MRI, ABUS, and CEM, the study moves the field beyond indirect comparisons and single-modality evaluations. At this stage, the data quantify the magnitude of diagnostic differences between modalities while highlighting the limitations of detection-based endpoints. Crucially, BRAID should not be interpreted as an exercise in declaring winners and losers among imaging techniques. Instead, the preliminary findings support a shift away from binary decision-making toward a more nuanced, risk- and context-sensitive use of supplemental imaging.

The consistent performance of contrast-enhanced techniques across screening, PHBC surveillance, and diagnostic settings suggests that breast density should be considered not merely a modifier of imaging performance, but a defining factor that actively informs imaging strategy selection along the clinical continuum. At the same time, the interpretation of the BRAID interim results requires careful consideration of feasibility and sustainability at a global level. While it may appear intuitively appealing to extend contrast-enhanced imaging to all women with dense breasts, such an approach must be evaluated against the uneven worldwide availability of imaging infrastructure, the economic implications for health systems, and the risk of widening disparities in access and outcomes. Access to MRI scanners and, to a lesser extent, CEM remains highly variable across regions, particularly in low- and middle-income countries, where screening resources are already constrained. In addition, contrast-enhanced examinations entail higher consumption of materials, energy, and personnel time compared with non-contrast techniques, raising legitimate concerns regarding environmental impact and long-term sustainability. These factors underscore that the ultimate value of supplemental imaging strategies cannot be judged solely by incremental cancer detection. Instead, final evaluations will need to integrate diagnostic benefit with availability, resource utilisation, environmental footprint, and health system resilience, ensuring that evidence-based advances in breast imaging translate into equitable and sustainable screening practices worldwide.

Women's perspectives on the acceptability of different screening modalities—including their willingness to accept potential harms in exchange for incremental benefits—must be systematically evaluated and integrated into policy development through shared decision-making frameworks. Moreover, a more comprehensive and equitable pathway forward may lie in integrated risk-based screening approaches that incorporate breast density alongside other risk factors to personalise screening intensity. Such strategies offer the potential to optimise resource allocation, align screening with individual benefit-harm profiles, and ensure that advances in imaging technology translate into meaningful and equitable improvements in population health.

Ultimately, the full impact of BRAID will depend on the maturation of the dataset and the integration of longer-term outcomes, including interval cancer rates, overdiagnosis estimates, patient-centred measures, and cost-effectiveness analyses. Until definitive data become accessible, the available findings represent a constructive interim step, shaping future trial design, informing policy deliberations, and guiding modelling efforts while highlighting the need to interpret supplemental imaging strategies within an integrated numerical, methodological, and system-level framework.

Acknowledgments

None.

Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, AME Clinical Trials Review. The article has undergone external peer review.

Peer Review File: Available at https://actr.amegroups.com/article/view/10.21037/actr-26-0034/prf

Funding: None.

Conflicts of Interest: The author has completed the ICMJE uniform disclosure form (available at https://actr.amegroups.com/article/view/10.21037/actr-26-0034/coif). The author has no conflicts of interest to declare.

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