Assessment of a fully automated, high-throughput mammographic density measurement tool for use with processed digital mammograms. - Couwenberg, A M; Verkooijen, H M; Li, J; Pijnappel, R M; Charaghvandi, K R; Hartman, M; van Gils, C H (Cancer Causes & Control, 2014)
Purpose: The ImageJ model is a recently developed automated breast density measurement tool based on analysis of Cumulus outcomes. It has been validated on digitized film-screen mammograms. In this study, the ImageJ model was assessed on processed full-field digital mammograms and correlated with the Breast Imaging Reporting and Data System (BI-RADS) density classification. Also, the association with breast cancer risk factors is observed.Methods: Women with mammographies between 2001 and 2011 at the University Medical Center Utrecht, The Netherlands were included. We composed a training set, read with Cumulus, for building the ImageJ model [n = 100 women, 331 images; craniocaudal (CC) and mediolateral oblique (MLO) views, left and right] and a validation set for model assessment and correlation with the BI-RADS classification [n = 530 women, 1,977 images; average of available CC and MLO views, left and right]. Pearson product-moment correlation coefficient was used to compare Cumulus with ImageJ, Spearman correlation coefficient for ImageJ with BI-RADS density, and generalized linear models for association with breast cancer risk factors.Results: The correlation between ImageJ and Cumulus in the training set was 0.90 [95 % confidence interval (CI) 0.86-0.93]. After application to the validation set, we observed a high correlation between ImageJ and the BI-RADS readings (Spearman r = 0.86, 95 % CI 0.84-0.88). Women with higher density were significantly younger, more often premenopausal, had lower parity, more often a benign breast lesion or family history of breast cancer.Conclusions: The ImageJ model can be used on processed digital mammograms. The measurements strongly correlate with Cumulus, the BI-RADS density classification, and breast cancer risk factors.