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The Detection of Change in Mammographic Density

Division of Epidemiology and Statistics, Ontario Cancer Institute, Toronto, Ontario, M5G 1K9 Canada [J. S., A. G., L. J. M., S. M., N. F. B.] and Imaging Research, Sunnybrook and Women’s College Hospital Health Sciences Centre, Toronto, Ontario, M4N 3M5 Canada [A. G., M. Y.]

Mammographic density is associated with risk of breast cancer, and factors that change density may also change risk. There has, however, been little research into how change in serial mammograms is best detected. The purpose of the work described here was to examine the effects of different reading conditions on the detection of change in mammographic features. Mammograms were selected from women who had participated in a randomized controlled trial of screening for breast cancer. We selected two age-matched groups of subjects, one had undergone menopause after entry (n = 202) and another who had not (n = 202). Serial mammograms from these subjects were then measured four times using a computer-assisted method under different conditions: (a) films were randomized; (b) subjects were randomized (i.e., pairs of films from individuals were read one after the other), but the order of films was random and unknown to the reader; (c) subjects were randomized, and the order of films was sequential and known to the reader; and (d) subjects were randomized, and the order of films was random and unknown to the reader, but both films in each pair were read simultaneously on separate computer screens. The mean effect of the menopause on change in the mammographic measures of total, dense and nondense areas, percent density, and the associated variances were then compared. With one exception, all of the randomization and viewing methods confirmed a change in all mammographic measures at menopause and produced very similar overall results, suggesting that mammographic density is a robust measure. Compared with randomization of all films, the method in which subjects were randomized and paired films read one after the other in random and unknown order was associated with a slightly smaller mean difference and achieved a substantial reduction in variability, suggesting that it is the most sensitive method of randomization and viewing for the detection of change.

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