Breast composition measurements using retrospective standard mammogram form (SMF)

被引:68
作者
Highnam, R.
Pan, X.
Warren, R.
Jeffreys, M.
Smith, G. Davey
Brady, M.
机构
[1] Siemes Mol Imaging Ltd, Oxford, England
[2] Addenbrookes Hosp, Cambridge, England
[3] Massey Univ, Wellington, New Zealand
[4] Univ Bristol, Bristol BS8 1TH, Avon, England
[5] Univ Oxford, Oxford OX1 2JD, England
关键词
D O I
10.1088/0031-9155/51/11/001
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
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 2.2 beta) 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.
引用
收藏
页码:2695 / 2713
页数:19
相关论文
共 22 条
[1]  
[Anonymous], BREAST IM REP DAT SY
[2]   A volumetric approach to glandularity estimation in mammography: a feasibility study [J].
Blot, L ;
Zwiggelaar, R .
PHYSICS IN MEDICINE AND BIOLOGY, 2005, 50 (04) :695-708
[3]  
Boyd NF, 1998, CANCER EPIDEM BIOMAR, V7, P1133
[4]   A METHOD FOR ESTIMATING COMPRESSED BREAST THICKNESS DURING MAMMOGRAPHY [J].
BURCH, A ;
LAW, J .
BRITISH JOURNAL OF RADIOLOGY, 1995, 68 (808) :394-399
[5]   THE QUANTITATIVE-ANALYSIS OF MAMMOGRAPHIC DENSITIES [J].
BYNG, JW ;
BOYD, NF ;
FISHELL, E ;
JONG, RA ;
YAFFE, MJ .
PHYSICS IN MEDICINE AND BIOLOGY, 1994, 39 (10) :1629-1638
[6]   Mammographic tissue, breast cancer risk, serial image analysis, and digital mammography part 1. Tissue and related risk factors [J].
Heine, JJ ;
Malhotra, P .
ACADEMIC RADIOLOGY, 2002, 9 (03) :298-316
[7]  
Highnam R, 1996, Med Image Anal, V1, P1, DOI 10.1016/S1361-8415(01)80002-5
[8]  
HIGHNAM R, 1998, BRIT J RADIOL, P646
[9]  
Highnam R., 1999, Mammographic Image Analysis
[10]   COMPUTING THE SCATTER COMPONENT OF MAMMOGRAPHIC IMAGES [J].
HIGHNAM, RP ;
BRADY, JM ;
SHEPSTONE, BJ .
IEEE TRANSACTIONS ON MEDICAL IMAGING, 1994, 13 (02) :301-313