How the COVID-19 Pandemic Led to Updated BI-RADS Guidance on Addressing Axillary Lymphadenopathy
How the COVID-19 Pandemic Led to Updated BI-RADS Guidance on Addressing Axillary Lymphadenopathy
Breast Imaging Reporting and Data System
BI-RADS is the standardized vocabulary and reporting framework breast radiologists use to describe findings and assign a final assessment with a recommended next step. Maintained by the American College of Radiology, it spans the breast across mammography (including tomosynthesis), ultrasound, MRI, and contrast-enhanced mammography, so a report means the same thing to anyone who reads it. Its hallmark is a numbered assessment scale that ties each imaging conclusion to a management recommendation. It is the dominant breast-imaging lexicon worldwide and, in the United States, is woven into federal mammography reporting requirements.
The first major overhaul in over a decade and the largest expansion yet (the illustrated guide was rebranded from 'Atlas' to 'Manual'). Breast-density reporting became a mandatory standalone section across all modalities, tomosynthesis was formally folded into how masses are characterized, and contrast-enhanced mammography was elevated to a full core modality. The lexicons were modernized — ultrasound gained a 'non-mass' concept, several ambiguous MRI terms were retired and new descriptors added (with recognition of abbreviated MRI protocols), and categories 0 and 6 were clarified rather than renumbered. It matters because reporting now better matches how breast imaging is practiced today.
The reference standard until v2025. It delivered a comprehensive update across mammography, ultrasound, and MRI, sharpened breast-density language toward a composition/masking emphasis, and strengthened management and outcome-monitoring guidance.
A major expansion that added dedicated lexicons for breast ultrasound and breast MRI for the first time, moving BI-RADS beyond mammography, and introduced the 4A/4B/4C subdivision to better stratify biopsy risk.
Broadened the illustrated atlas with feature illustrations and added practice-auditing guidance and sample reports to support quality assurance.
A refinement update that improved descriptor clarity and consistency over the original.
The original, mammography-only release that established standardized terminology, a structured report format, and the numbered assessment-category concept to cut interpretive variability.
At its core, BI-RADS sorts every study into a small set of numbered final assessment categories, conventionally 0 through 6, where each number bundles a level of suspicion with the action it implies — from 'more imaging needed' through 'benign' and 'probably benign' to escalating degrees of cancer concern and, finally, already-proven cancer. The scale is ordered so a higher number broadly signals greater concern or a more definitive next step, and the 'suspicious' tier is further split into low/intermediate/high sub-levels. Separately, the system standardizes how findings are described (shape, margin, density, calcifications, enhancement, breast density). Consult the official ACR BI-RADS v2025 Manual for the exact criteria, definitions, and management language.
These are our plain-language summaries. For the exact criteria, thresholds, and management rules, see the official source.
How the COVID-19 Pandemic Led to Updated BI-RADS Guidance on Addressing Axillary Lymphadenopathy
Ultrasound Nonmass Lesion in BI-RADS v2025: A Primer.
In 279 excised breast lesions in patients under 20, none were malignant and 87% were fibroadenomas, yet 55% were Breast Imaging Reporting and Data System (BI-RADS) 4—adult estimates overpredict pediatric cancer risk.
Ikonopedia updates breast reporting platform for BI-RADS v2025
Ikonopedia Announces New Release Supporting BI-RADS® v2025 (6th Edition)
A 'Wake-Up Call' for BI-RADS 3 Audits
Video: Stamatia Destounis, MD, FACR, Discusses Key Changes for the Updated BI-RADS System
<![CDATA[Video: Stamatia Destounis, MD, FACR, Discusses Key Changes for the Updated BI-RADS System]]>
BI-RADS v2025 formally incorporates nonmass lesions (NMLs) on breast ultrasound, which have a high malignancy rate. A pictorial review classifies NMLs by distribution—segmental, linear, focal, regional—showing benign/malignant cases, descriptors, and multimodality correlation.
In 539 triple-negative breast cancers, HER2-low vs HER2-0 tumors showed different ultrasound vascularity (avascular: 6.3% vs 12.0%) and radiomics features; overall survival was similar, but HER2-low was associated with improved event-free survival in non-pCR patients.
Reasoning large language models (LLMs) scored higher than conventional ones for BI-RADS educational questions (median 3.7 vs 2.7, P<0.001). Performance fell for multifaceted clinical scenarios (reasoning models Δmedian -1.3). ChatGPT-o1 and Deepseek-R1 led. Language affected som…
Bringing BI-RADS Into the Current Era of Breast Imaging.
Multichannel deep learning MRI model predicted axillary lymph node metastasis with AUC 0.908 (95% CI 0.862-0.954) in external validation, comparable to Node-RADS (AUC 0.909, P=0.971).
In 1847 breast MRI exams, a DINOv2-based medical slice transformer triaged cases without suspicious findings (BI-RADS ≥4) at 97.5% sensitivity. Specificity was 19% for contrast-enhanced (T1sub+T2w) and 17% for non-contrast-enhanced (DWI1500+T2w) MRI. External validation AUC 0.77.
AI combining mammography and tomosynthesis radiomics+deep learning (DL) improved breast microcalcification differentiation: test AUC 0.835, significantly better than BI-RADS (0.809) or single-modality models (P<0.05).
In a blinded evaluation, Gemini outperformed DeepSeek and ChatGPT for patient-friendly Arabic translation of BI-RADS breast imaging reports (mean rating 3.73 vs 3.54 vs 3.03, p<0.001). No laterality errors occurred in any model.
Thirteen Takeaways on BI-RADS v2025 Changes for Mammography, Ultrasound and Breast MRI Reporting
Thirteen Takeaways on BI-RADS v2025 Changes for Mammography, Ultrasound and Breast MRI Reporting
<![CDATA[Thirteen Takeaways on BI-RADS v2025 Changes for Mammography, Ultrasound and Breast MRI Reporting]]>
BI-RADS v2025 brings mammographic density alignment with Mammography Quality Standards Act, nonmass lesions on ultrasound, revised MRI enhancing lesion terminology, and first dedicated contrast-enhanced mammography section, harmonizing lexicon across modalities.
LLM for breast ultrasound report quality control: 80% accuracy for margins (vs 64% manual), 74% for echo patterns (56%), 50 reports in 13 min (vs 213 min), suggesting time-saving automation.
For BI-RADS 4 breast lesions, Kaiser score AUC 0.901 (95% CI 0.856-0.941) outperformed ADC alone (AUC 0.733) and combination (0.890). ADC had high false-positive rate (66.1%) in benign cellular lesions. DCIS and mucinous carcinoma were often false negatives.
Objective and subjective evaluation of a mammogram-reporting AI found BI-RADS agreement 58.1%, mass 76.7%, calcification 81.4%, ROUGE-L F1 0.672, but some cases with high objective scores were rated low subjectively, flagged as over/underestimation.
An AI-assisted decision-support model using patient-level variables reduced categorization disagreement by 26% for breast density and background parenchymal enhancement on contrast-enhanced mammography, achieving AUC 0.75, precision 0.72, and recall 0.69, with greatest benefit i…
Combining cfDNA tumor mutation burden and gene mutation score with age and BI-RADS classification yielded an AUC of 0.923, 88.1% sensitivity, 89.1% specificity for predicting malignancy in 212 patients with BI-RADS 4 breast nodules.
In a 5-year review of BI-RADS 4C and 5 lesions, radiologist-determined radiology-pathology (rad-path) discordance carried a 47.3% upgrade to malignancy versus 9.4% for concordant benign biopsies, supporting its role in guiding surgical excision.
A 2.5D ABUS deep learning model with BI-RADS shape and margin auxiliary tasks achieved an external test AUC of 0.91 (95% CI 0.83-0.96) for breast lesion classification, outperforming 3D Swin Transformer (0.76) and other benchmarks.
A new AJR article guides radiologists on adopting the BI-RADS 2025 lexicon in clinical breast imaging reports, covering updated terminology and structured reporting recommendations.
ACR BI-RADS v2025 adds new descriptors like "lobulated" and "non-mass lesion," renames MRI kinetics to "early phase," and separates assessment from management. It formally integrates contrast-enhanced mammography and supports surgical excision as definitive treatment under a rev…
Older age and larger tumor size independently predicted malignancy in 104 women with BI-RADS 4/5 breast lesions (aOR 1.13/yr, 1.10/mm). BI-RADS 5 was not significant after adjustment, but the small subgroup (n=11) limited power.
BI-RADS is effectively the universal lexicon for breast imaging, with little real competition — it is the template that later 'RADS' systems (PI-RADS, LI-RADS, and others) were modeled on. In the United States its use is reinforced by federal mammography regulation, which cements its dominance over ad hoc reporting. Where alternatives exist they tend to be complementary rather than rival: automated/volumetric breast-density software, for example, maps its output back onto BI-RADS density classes rather than replacing the framework.
BI-RADS underpins large national audit datasets, and its predictive value rises steeply across the suspicious sub-tiers — reported positive predictive values climb from roughly a third for 4A to the high-80s–90s percent for 4B/4C and category 5 — which validates the stratification while exposing that sub-categorizing category 4 is subjective and reader-dependent. Inter-reader reproducibility is generally substantial but imperfect, with breast-density assignment in particular showing meaningful variability between editions and experience levels. Historical analyses credit BI-RADS with materially reducing reporting ambiguity and enabling outcomes monitoring since the 1990s. Recurring criticisms — interpretive variability in the probably-benign and suspicious zones, and density-assessment subjectivity — are explicitly among the issues the 2025 6th edition set out to address.
RadPigeon is an independent radiology news digest and is not affiliated with or endorsed by American College of Radiology (ACR). “BI-RADS” is a trademark of its owner and is named here only to refer to the system. Always consult the official source for the exact, current criteria.