Breast Composition Measurements Using Retrospective Standard Mammogram Form (SMF)

Abstract

Standard Mammogram Form (SMF), is a standardized, quantitative representation of a breast x-ray that can be easily estimated. From SMF it is possible to compute the volume of non-fat tissue and measures of breast density, both of which are of significant interest in determining breast cancer risk. Previous theoretical analysis of SMF suggested that a complete and substantial set of calibration data (such as mAs and kVp) would be needed to generate realistic breast composition measures, which is problematical since there have been many interesting trials that have retrospectively collected images with no calibration data. In this paper, we show how implementations of SMF include self-compensation mechanisms, so that SMF can be applied retrospectively to data for which calibration parameters are not (or only partially) available. To illustrate our findings, the current implementation of SMF (version 2.2β) was run over 4,028 digitized film-screen mammograms taken from 6 sites during the years 1988-2002, both with and without using the known calibration data. Results show that the SMF implementation running with no calibration data generates results which display a strong relationship with those obtained using a complete set of calibration data. More importantly, they bear a close relationship to an expert’s visual assessment of breast composition using established techniques.