Christine N Damases1, Patrick C Brennan2, Claudia Mello-Thoms2, Mark F McEntee2. 1. Faculty of Health Sciences, Discipline of Medical Radiation Sciences and Brain and Mind Research Institute, M205, Cumberland Campus, The University of Sydney, 75 East St, Room M205, Lidcombe, Sydney, NSW 2141, Australia; Faculty of Health Sciences, Department of Radiography, University of Namibia, M-Block, Room M-105, Mandume Ndemufayo Avenue, Private Bag 13310, Windhoek 9000, Namibia. Electronic address: cdam2504@uni.sydney.edu.au. 2. Faculty of Health Sciences, Discipline of Medical Radiation Sciences and Brain and Mind Research Institute, M205, Cumberland Campus, The University of Sydney, 75 East St, Room M205, Lidcombe, Sydney, NSW 2141, Australia.
Abstract
RATIONALE AND OBJECTIVES: To investigate agreement on mammographic breast density (MD) assessment between automated volumetric software and Breast Imaging Reporting and Data System (BIRADS) categorization by expert radiologists. MATERIALS AND METHODS: Forty cases of left craniocaudal and mediolateral oblique mammograms from 20 women were used. All images had their volumetric density classified using Volpara density grade (VDG) and average volumetric breast density percentage. The same images were then classified into BIRADS categories (I-IV) by 20 American Board of Radiology examiners. RESULTS: The results demonstrated a moderate agreement (κ = 0.537; 95% CI = 0.234-0.699) between VDG classification and radiologists' BIRADS density assessment. Interreader agreement using BIRADS also demonstrated moderate agreement (κ = 0.565; 95% CI = 0.519-0.610) ranging from 0.328 to 0.669. Radiologists' average BIRADS was lower than average VDG scores by 0.33, with their mean being 2.13, whereas the mean VDG was 2.48 (U = -3.742; P < 0.001). VDG and BIRADS showed a very strong positive correlation (ρ = 0.91; P < 0.001) as did BIRADS and average volumetric breast density percentage (ρ = 0.94; P < 0.001). CONCLUSIONS: Automated volumetric breast density assessment shows moderate agreement and very strong correlation with BIRADS; interreader variations still exist within BIRADS. Because of the increasing importance of MD measurement in clinical management of patients, widely accepted, reproducible, and accurate measures of MD are required.
RATIONALE AND OBJECTIVES: To investigate agreement on mammographic breast density (MD) assessment between automated volumetric software and Breast Imaging Reporting and Data System (BIRADS) categorization by expert radiologists. MATERIALS AND METHODS: Forty cases of left craniocaudal and mediolateral oblique mammograms from 20 women were used. All images had their volumetric density classified using Volpara density grade (VDG) and average volumetric breast density percentage. The same images were then classified into BIRADS categories (I-IV) by 20 American Board of Radiology examiners. RESULTS: The results demonstrated a moderate agreement (κ = 0.537; 95% CI = 0.234-0.699) between VDG classification and radiologists' BIRADS density assessment. Interreader agreement using BIRADS also demonstrated moderate agreement (κ = 0.565; 95% CI = 0.519-0.610) ranging from 0.328 to 0.669. Radiologists' average BIRADS was lower than average VDG scores by 0.33, with their mean being 2.13, whereas the mean VDG was 2.48 (U = -3.742; P < 0.001). VDG and BIRADS showed a very strong positive correlation (ρ = 0.91; P < 0.001) as did BIRADS and average volumetric breast density percentage (ρ = 0.94; P < 0.001). CONCLUSIONS: Automated volumetric breast density assessment shows moderate agreement and very strong correlation with BIRADS; interreader variations still exist within BIRADS. Because of the increasing importance of MD measurement in clinical management of patients, widely accepted, reproducible, and accurate measures of MD are required.
Authors: Hamed Samavat; Giske Ursin; Tim H Emory; Eunjung Lee; Renwei Wang; Carolyn J Torkelson; Allison M Dostal; Karen Swenson; Chap T Le; Chung S Yang; Mimi C Yu; Douglas Yee; Anna H Wu; Jian-Min Yuan; Mindy S Kurzer Journal: Cancer Prev Res (Phila) Date: 2017-09-13
Authors: Aimilia Gastounioti; Christine Damases Kasi; Christopher G Scott; Kathleen R Brandt; Matthew R Jensen; Carrie B Hruska; Fang F Wu; Aaron D Norman; Emily F Conant; Stacey J Winham; Karla Kerlikowske; Despina Kontos; Celine M Vachon Journal: Radiology Date: 2020-05-12 Impact factor: 11.105