Impact of type of full-field digital image on mammographic density assessment and breast cancer risk estimation: a case-control study

Marta Cecilia Busana, Amanda Eng, Rachel Denholm, Mitch Dowsett, Sarah Vinnicombe, Steve Allen, Isabel Dos-Santos-Silva

Research output: Contribution to journalArticle (Academic Journal)peer-review

13 Citations (Scopus)
264 Downloads (Pure)


BACKGROUND: Full-field digital mammography, which is gradually being introduced in most clinical and screening settings, produces two types of images: raw and processed. However, the extent to which mammographic density measurements, and their ability to predict breast cancer risk, vary according to type of image is not fully known.

METHODS: We compared the performance of the semi-automated Cumulus method on digital raw, "analogue-like" raw and processed images, and the performance of a recently developed method - Laboratory for Breast Radiodensity Assessment (LIBRA) - on digital raw and processed images, in a case-control study (414 patients (cases) and 684 controls) by evaluating the extent to which their measurements were associated with breast cancer risk factors, and by comparing their ability to predict breast cancer risk.

RESULTS: Valid Cumulus and LIBRA measurements were obtained from all available images, but the resulting distributions differed according to the method and type of image used. Both Cumulus and LIBRA percent density were inversely associated with age, body mass index (BMI), parity and postmenopausal status, regardless of type of image used. Cumulus percent density was strongly associated with breast cancer risk, but with the magnitude of the association slightly stronger for processed (risk increase per one SD increase in percent density (95 % CI): 1.55 (1.29, 1.85)) and "analogue-like" raw (1.52 (1.28, 1.80)) than for raw (1.35 (1.14, 1.60)) images. LIBRA percent density produced weaker associations with risk, albeit stronger for processed (1.32 (1.08, 1.61)) than raw images (1.17 (0.99, 1.37)). The percent density values yielded by the various density assessment/type of image combinations had similar ability to discriminate between patients and controls (area under the receiving operating curve values for percent density, age, BMI, parity and menopausal status combined ranged from 0.61 and 0.64).

CONCLUSIONS: The findings showed that Cumulus can be used to measure density on all types of digital images. They also indicate that LIBRA may provide a valid fully automated alternative to the more labour-intensive Cumulus. However, the same digital image type and assessment method should be used when examining mammographic density across populations, or longitudinal changes in density within a single population.

Original languageEnglish
Article number96
Number of pages12
JournalBreast Cancer Research
Publication statusPublished - 26 Sept 2016


  • Aged
  • Breast Density
  • Breast Neoplasms
  • Case-Control Studies
  • Female
  • Humans
  • Image Processing, Computer-Assisted
  • Mammography
  • Middle Aged
  • Odds Ratio
  • Risk Assessment
  • Risk Factors
  • Journal Article


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