Literature DB >> 24962023

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

A M Couwenberg1, H M Verkooijen, J Li, R M Pijnappel, K R Charaghvandi, M Hartman, C H van Gils.   

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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Year:  2014        PMID: 24962023     DOI: 10.1007/s10552-014-0404-4

Source DB:  PubMed          Journal:  Cancer Causes Control        ISSN: 0957-5243            Impact factor:   2.506


  7 in total

1.  Volumetric breast density measurement: sensitivity analysis of a relative physics approach.

Authors:  Susie Lau; Kwan Hoong Ng; Yang Faridah Abdul Aziz
Journal:  Br J Radiol       Date:  2016-07-25       Impact factor: 3.039

2.  Agreement between Breast Percentage Density Estimations from Standard-Dose versus Synthetic Digital Mammograms: Results from a Large Screening Cohort Using Automated Measures.

Authors:  Emily F Conant; Brad M Keller; Lauren Pantalone; Aimilia Gastounioti; Elizabeth S McDonald; Despina Kontos
Journal:  Radiology       Date:  2017-01-25       Impact factor: 11.105

Review 3.  Reproductive Factors and Mammographic Density: Associations Among 24,840 Women and Comparison of Studies Using Digitized Film-Screen Mammography and Full-Field Digital Mammography.

Authors:  Stacey E Alexeeff; Nnaemeka U Odo; Russell McBride; Valerie McGuire; Ninah Achacoso; Joseph H Rothstein; Jafi A Lipson; Rhea Y Liang; Luana Acton; Martin J Yaffe; Alice S Whittemore; Daniel L Rubin; Weiva Sieh; Laurel A Habel
Journal:  Am J Epidemiol       Date:  2019-06-01       Impact factor: 4.897

4.  Impact of childbirth history on dense breast in mammographic screening: a cross-sectional study.

Authors:  Tomohiro Ochi; Hiroko Tsunoda; Hideko Yamauchi; Osamu Takahashi
Journal:  BMC Womens Health       Date:  2022-05-26       Impact factor: 2.742

5.  Identification of two novel mammographic density loci at 6Q25.1.

Authors:  Judith S Brand; Jingmei Li; Keith Humphreys; Robert Karlsson; Mikael Eriksson; Emma Ivansson; Per Hall; Kamila Czene
Journal:  Breast Cancer Res       Date:  2015-06-03       Impact factor: 6.466

6.  Subjective Versus Quantitative Methods of Assessing Breast Density.

Authors:  Wijdan Alomaim; Desiree O'Leary; John Ryan; Louise Rainford; Michael Evanoff; Shane Foley
Journal:  Diagnostics (Basel)       Date:  2020-05-21

7.  Mammographic Breast Density in Chinese Women: Spatial Distribution and Autocorrelation Patterns.

Authors:  Christopher W K Lai; Helen K W Law
Journal:  PLoS One       Date:  2015-09-02       Impact factor: 3.240

  7 in total

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