Mammographic density assessment: comparison of radiologists, automated volumetric measurement, and artificial intelligence-based computer-assisted diagnosis

Abstract

Background Artificial intelligence-based computer-assisted diagnosis (AI-CAD) is increasingly used for mammographic exams, and its role in mammographic density assessment should be evaluated. Purpose To assess the inter-modality agreement between radiologists, automated volumetric density measurement program (Volpara), and AI-CAD system in breast density categorization using the Breast Imaging-Reporting and Data System (BI-RADS) density categories. Material and Methods A retrospective review was conducted on 1015 screening digital mammograms that were performed in Asian female patients (mean age = 56 years ± 10 years) in our health examination center between December 2022 and January 2023. Four radiologists with two different levels of experience (expert and general radiologists) performed density assessments. Agreement between the radiologists, Volpara, and AI-CAD (Lunit INSIGHT MMG) was evaluated using weighted kappa statistics and matched rates. Results Inter-reader agreement between expert and general radiologists was substantial (k = 0.65) with a matched rate of 72.8%. The agreement was substantial between expert or general radiologists and Volpara (k = 0.64–0.67) with a matched rate of 72.0% but moderate between expert or general radiologists and AI-CAD (k = 0.45–0.58) with matched rates of 56.7%–67.0%. The agreement between Volpara and AI-CAD was moderate (k = 0.53) with a matched rate of 60.8%. Conclusion The agreement in breast density categorization between radiologists and automated volumetric density measurement program (Volpara) was higher than the agreement between radiologists and AI-CAD (Lunit INSIGHT MMG).