Assessment of a fully automated, high-throughput mammographic density measurement tool for use with processed digital mammograms

• Published in: Cancer causes & control 2014-08, Vol.25 (8), p.1037-1043
• Main Authors: Couwenberg, A. M., Verkooijen, H. M., Li, J., Pijnappel, R. M., Charaghvandi, K. R., Hartman, M., van Gils, C. H.
• Format: Article
• Language: English
• Subjects: Adult; Aged; Aged, 80 and over; Automation; Biomedical and Life Sciences; Biomedicine; Breast cancer; Breast Density; Breast Neoplasms; Cancer Research; Cancer screening; Clinical medicine; Correlation coefficients; Density; Density estimation; Density measurement; Digitization; Epidemiology; Female; Generalized linear models; Hematology; High-Throughput Screening Assays - methods; High-Throughput Screening Assays - standards; Humans; Image Processing, Computer-Assisted - methods; Image Processing, Computer-Assisted - standards; Mammary Glands, Human - abnormalities; Mammography; Mammography - methods; Mammography - standards; Medicin och hälsovetenskap; Methods; Middle Aged; Modeling; Oncology; Original Paper; Predisposing factors; Public Health; Radiology; Reproducibility of Results; Risk factors; Womens health
• ISSN: 0957-5243; 1573-7225; 1573-7225
• DOI: 10.1007/s10552-014-0404-4

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 0.09 [95 % confidence interval (CI) 0.86–0.93]. After application to the validation set, we observed a high correlation between ImageJ and the BIRADS 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.