Scinovex
article

The quantitative analysis of mammographic densities

Physics in Medicine and Biology · 1994 · Vol. 39(10) · pp. 1629–1638

Abstract

Quantitative classification of mammographic parenchyma based on radiological assessment has been shown to provide one of the strongest estimates of the risk of developing breast cancer. Existing classification schemes, however, are limited by coarse category scales. In addition, subjectivity can lead to sizeable interobserver and intraobserver variations. Here, we propose an interactive thresholding technique applied to digitized film-screen mammograms, which assesses the proportion of the mammographic image representing radiographically dense tissue. Observers viewed images on a CRT display and selected grey-level thresholds from which the breast and regions of dense tissue in the breast were identified. The proportion of radiographic density was then calculated from the image histogram. The technique was evaluated for the mammograms of 30 women and is well correlated (R > 0.91, Spearman coefficient) with a six-category subjective classification of radiographic density by radiologists. The technique was found to be very reliable with an intraclass correlation coefficient between observers typically R > 0.9. This technique may have a role in routine mammographic analysis for the purpose of assessing risk categories and as a tool in studies of the etiology of breast cancer, in particular for monitoring changes in breast parenchyma during potential preventive interventions.

Digital Radiography and Breast ImagingAI in cancer detectionBreast Lesions and CarcinomasMammographyMedicineThresholdingBreast cancerIntraclass correlationRadiologyMAMMOGRAPHIC DENSITYRadiographyNuclear medicineArtificial intelligence

MeSH terms

AdultBreast NeoplasmsFemaleHumansMammographyMiddle AgedPattern Recognition, AutomatedRadiographic Image EnhancementRadiographic Image Interpretation, Computer-AssistedSensitivity and SpecificityReproducibility of ResultsCohort StudiesAbsorptiometry, PhotonObserver Variation

Funding

  • Medical Research Council Canada
  • National Cancer Institute
Citations
612
FWCI
2.15
field-weighted impact
References
22
Percentile
87%
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Citations per year
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