Concordance Between Radiologist and AI-based Volumetric Breast Density Assessments: Clinical and Economic…

AI / informaticsSouth Dakota medicine : the journal of the South Dakota State Medical Association· Jun 2026

Concordance Between Radiologist and AI-based Volumetric Breast Density Assessments: Clinical and Economic Implications - A Retrospective Cohort Study.

Jacob R Devine, Alexander D M Withrow, Sabina Choudhry

Breast ImagingAI / informaticsDiagnosis

AI and radiologists agreed least often on extreme breast density categories A and D.

Concordance Between Radiologist and AI-based Volumetric Breast Density Assessments: Clinical and Economic Implications - A Retrospective Cohort Study.

Jacob R Devine … Sabina Choudhry

South Dakota medicine · Jun 2026

Background

Radiologists classify breast density using the Breast Imaging Reporting and Data System (BI-RADS) as required by the 2024 Mammography Quality Standards Act (Mammography Quality Standards Act), which mandates disclosure of breast density in all mammography reports.

Purpose

This study examines concordance between AI-based systems (Volumetric density measurement by Volpara/Lunit) and radiologist assessments and explores potential clinical and economic implications.

Methods

A retrospective cohort study with IRB approval was conducted at Avera Health using 54,819 mammograms between February 2024 and June 2025.

n = 54,819 mammograms

85-90%

Results

85-90%

AI matched radiologist density readings only 85-90% of the time for categories A and D.

n = 54,819 mammograms

More results

Most discrepancies involved BI-RADS B and C categories, leading to misclassification of breast density and potential repercussions for patient care.

Overestimation resulted in unnecessary procedures, radiation, costs, and anxiety, while underestimation risked delayed detection of aggressive cancers.

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Conclusion · 1 of 2

Current AI software demonstrates concordance with radiologist assessments, though notable variability persists at critical diagnostic thresholds.

Conclusion · 2 of 2

Utilizing standardized protocols, periodic AI model updates, and radiologist oversight are crucial to minimizing misclassification, enhancing workflow efficiency, optimizing patient outcomes, and fostering trust in AI-assisted breast imaging.

Concordance Between Radiologist and AI-based Volumetric Breast Density Assessments: Clinical and Economic Implications - A Retrospective Cohort Study.

Concordance Between Radiologist and AI-based Volumetric Breast Density Assessments: Clinical and Economic Implications - A Retrospective Cohort Study.

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