Breast composition measurements using retrospective standard mammogram form (SMF)

Abstract

The standard mammogram form (SMF) representation of an x-ray mammogram is a standardized, quantitative representation of the breast from which the volume of non-fat tissue and breast density can be easily estimated, both of which are of significant interest in determining breast cancer risk. Previous theoretical analysis of SMF had suggested that a complete and substantial set of calibration data (such as mAs and kVp) would be needed to generate realistic breast composition measures and yet there are many interesting trials that have retrospectively collected images with no calibration data. The main contribution of this paper is to revisit our previous theoretical analysis of SMF with respect to errors in the calibration data and to show how and why that theoretical analysis did not match the results from the practical implementations of SMF. In particular, we show how by estimating breast thickness for every image we are, effectively, compensating for any errors in the calibration data. To illustrate our findings, the current implementation of SMF (version 2.2beta) was run over 4028 digitized film-screen mammograms taken from six sites over the years 1988-2002 with and without using the known calibration data. Results show that the SMF implementation running without any calibration data at all generates results which display a strong relationship with when running with a complete set of calibration data, and, most importantly, to an expert's visual assessment of breast composition using established techniques. SMF shows considerable promise in being of major use in large epidemiological studies related to breast cancer which require the automated analysis of large numbers of films from many years previously where little or no calibration data is available.

Breast cancer risk factors and a novel measure of volumetric breast density: cross-sectional study

“…If these parameters are not present then the SMF algorithm attempts to estimate them. Errors in these parameters will inevitably cause errors in the SMF values and a sensitivity analysis to investigate such errors has been reported previously (Highnam et al, 1996;Highnam and Brady, 1999).…”

“…The aim of this study was to explore the use of the Standard Mammogram Form (SMFt) tool (Highnam et al, 1996(Highnam et al, , 1999Jeffreys et al, 2006;McCormack et al, 2007) to investigate relationships between breast cancer risk factors and volumetric breast density.…”

Untitled

“…These include methods based on ultrasound tomography (87) and magnetic resonance imaging (88). In addition some investigators have developed methods that use digitized film mammograms (89)(90)(91)(92). However, so far these automated methods have yielded weaker associations with breast cancer risk and with risk factors than the standard two dimensional mammographic density methods (93)(94)(95).…”

Model Driven Engineering for Science Gateways

“…By doing so, MammoGrid made it possible for the first time to accumulate rare data samples into a common, secure and distributed repository needed to validate new breast cancer Computer Aided Detection (CAD) algorithms using the Standard Mammogram Format or SMF [11], while testing the actual feasibility and overall impact of providing automated radiographer second opinion in the cancer screening practice.…”