Quantitative analysis of breast parenchymal density: correlation with women's age.

RATIONALE AND OBJECTIVES The authors evaluated the relationship between a woman's breast parenchymal density and her age by means of a quantitative method for measuring density from digitized mammograms. MATERIALS AND METHODS The percentage of the breast considered to be dense was evaluated from mammograms of 50 women stratified by age. Quantitative analysis based on the computer segmentation of tissue in digitized mammograms was performed by three expert mammographers. The results of this analysis were compared with results from a review of the film mammograms by three expert mammographers. RESULTS A slight decrease in the percentage of breast considered to be dense with increased age was observed. The average difference in the percentage of dense breast tissue between the youngest and the oldest age groups was 6.4% based on the digital review and 14.6% based on the film review. Within each age group, the total variability was on the order of 75%. CONCLUSION The difference in mean magnitude between the youngest and oldest age groups was small and may not be clinically important. The variability within an age group was large, which suggests that age is not a reliable indicator of percentage of dense breast tissue.

[1]  D R Dance,et al.  Segmentation of mammograms using multiple linked self-organizing neural networks. , 1995, Medical physics.

[2]  F Merletti,et al.  The relation of mammographic features of the breast to breast cancer risk factors. , 1982, American journal of epidemiology.

[3]  N. Boyd,et al.  Analysis of mammographic density and breast cancer risk from digitized mammograms. , 1998, Radiographics : a review publication of the Radiological Society of North America, Inc.

[4]  J. Wolfe,et al.  Mammographic parenchymal patterns and quantitative evaluation of mammographic densities: a case-control study. , 1987, AJR. American journal of roentgenology.

[5]  G. Whitehouse,et al.  The variation of breast parenchymal patterns with age. , 1985, The British journal of radiology.

[6]  P. Stomper,et al.  Analysis of parenchymal density on mammograms in 1353 women 25-79 years old. , 1996, AJR. American journal of roentgenology.

[7]  J. Wolfe.  Breast patterns as an index of risk for developing breast cancer. , 1976, AJR. American journal of roentgenology.

[8]  Radiographic patterns of the mammary parenchyma: variation with age at examination and age at first birth. , 1981, Radiology.

[9]  S. Rubin,et al.  Efficacy of screening mammography. A meta-analysis. , 1995, JAMA.

[10]  Michael H. Kutner.  Applied Linear Statistical Models , 1974 .

[11]  M J Yaffe,et al.  Current status of digital mammography. , 1996, Seminars in ultrasound, CT, and MR.

[12]  E. Fishell,et al.  Bias and the association of mammographic parenchymal patterns with breast cancer. , 1982, British Journal of Cancer.

[13]  A. Morrison,et al.  Mammographic Parenchymal Features and Breast Cancer in the Breast Cancer Detection Demonstration Project , 1988 .

[14]  J Whitehead,et al.  The relationship between Wolfe's classification of mammograms, accepted breast cancer risk factors, and the incidence of breast cancer. , 1985, American journal of epidemiology.

[15]  J. Grove,et al.  Factors associated with mammographic pattern. , 1985, The British journal of radiology.

[16]  Mammographic screening in women younger than 50 years. , 1995, JAMA.

[17]  Josef Kittler,et al.  Minimum error thresholding , 1986, Pattern Recognit..

[18]  N. Boyd,et al.  The quantitative analysis of mammographic densities. , 1994, Physics in medicine and biology.

[19]  I H Gravelle,et al.  Changes in Wolfe mammographic patterns with aging. , 1987, The British journal of radiology.

[20]  B. Hart,et al.  Age and race related changes in mammographic parenchymal patterns , 1989, Cancer.

[21]  A. Morrison,et al.  Height and weight, mammographic features of breast tissue, and breast cancer risk. , 1984, American journal of epidemiology.

[22]  N. Boyd,et al.  Effects at two years of a low-fat, high-carbohydrate diet on radiologic features of the breast: results from a randomized trial. Canadian Diet and Breast Cancer Prevention Study Group. , 1997, Journal of the National Cancer Institute.

[23]  J. Hayward,et al.  The relation between radiological patterns of the breast and body weight and height. , 1982, The British journal of radiology.

[24]  R N Hoover,et al.  Mammographic densities and risk of breast cancer , 1991, Cancer.

[25]  J. Fleiss,et al.  Intraclass correlations: uses in assessing rater reliability. , 1979, Psychological bulletin.

[26]  John D. Austin,et al.  Adaptive histogram equalization and its variations , 1987 .

[27]  D. Thompson,et al.  Reproducibility and consistency in classification of breast parenchymal patterns. , 1983, AJR. American journal of roentgenology.

[28]  J. Wolfe.  Breast parenchymal patterns and their changes with age. , 1976, Radiology.

[29]  G H Whitehouse,et al.  Factors associated with mammographic parenchymal patterns. , 1988, Clinical radiology.