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

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Abstract

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.

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Acknowledgments

This work was supported by the Agency for Science, Technology, and Research (A-STAR), Singapore under the 2nd Joint Council Office (JCO) Career Development Grant (13302EG065). We thank Mariette Lokate (M.L.) for providing a cohort of images with Cumulus density estimations for this study.

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Authors and Affiliations

  1. University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands

    A. M. Couwenberg

  2. Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands

    H. M. Verkooijen & R. M. Pijnappel

  3. Human Genetics Lab, Genome Institute of Singapore, Singapore, Singapore

    J. Li

  4. Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands

    K. R. Charaghvandi

  5. Department of Surgery, National University of Singapore and National University Health System, Singapore, Singapore

    M. Hartman

  6. Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands

    C. H. van Gils

Authors
  1. A. M. Couwenberg
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  2. H. M. Verkooijen
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  3. J. Li
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  4. R. M. Pijnappel
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  5. K. R. Charaghvandi
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  6. M. Hartman
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  7. C. H. van Gils
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Corresponding author

Correspondence to C. H. van Gils.

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Couwenberg, A.M., Verkooijen, H.M., Li, J. et al. Assessment of a fully automated, high-throughput mammographic density measurement tool for use with processed digital mammograms. Cancer Causes Control 25, 1037–1043 (2014). https://doi.org/10.1007/s10552-014-0404-4

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  • DOI: https://doi.org/10.1007/s10552-014-0404-4

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