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Design and clinical validation of a software program for automated measurement of mammographic breast density

Authors :
Adriano L. C. Araújo
Heliana B. Soares
Daniel F. Carvalho
Roberto M. Mendonça
Antonio G. Oliveira
Source :
BMC Medical Informatics and Decision Making, Vol 20, Iss 1, Pp 1-7 (2020)
Publication Year :
2020
Publisher :
BMC, 2020.

Abstract

Abstract Background Mammographic breast density is an important predictor of breast cancer, but its measurement has limitations related to subjectivity of visual evaluation or to difficult access for automatic volumetric measurement methods. Herein, we describe the design and clinical validation of Aguida, a software program for automated quantification of breast density from flat mammography images. Materials and methods The software program was developed in MatLab. After image segmentation separating the background from the breast image, the operator positions a cursor defining a region of interest on the pectoralis major muscle from the mediolateral oblique view. Then, in the craniocaudal view, the threshold for separation of the dense tissue is based on the optical density of the pectoral muscle, and the proportion of dense tissue is calculated by the program. Mammograms obtained from 2 different occasions in 291 women were used for clinical evaluation. Results The intraclass correlation coefficient (ICC) between breast density measurements by the software and by a radiologist was 0.96, with a bias of only 0.67 percentage points and a 95% limit of agreement of 13.5 percentage points; the ICC was 0.94 in the interobserver reliability assessment by two radiologists with different experience; and the ICC was 0.98 in the intraobserver reliability assessment. The distribution among the density classes was close to the values obtained with the volumetric software. Conclusions Measurement of breast density with the Aguida program from flat mammography images showed high agreement with the visual determination by radiologists, and high inter- and intra-observer reliability.

Details

Language :
English
ISSN :
14726947
Volume :
20
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Medical Informatics and Decision Making
Publication Type :
Academic Journal
Accession number :
edsdoj.5487772f63cc4a9fb8d4657d0b9dd4f0
Document Type :
article
Full Text :
https://doi.org/10.1186/s12911-020-1062-y