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PMID: 12409590 已发表 · ppublish 英语

Computerized analysis of digitized mammograms of BRCA1 and BRCA2 gene mutation carriers.

Radiology ·第 225 卷 ·第 2 期 ·2002-11-19

Huo Zhimin, Giger Maryellen L, Olopade Olufunmilayo I, Wolverton Dulcy E, Weber Barbara L, Metz Charles E, Zhong Weiming, Cummings Shelly A

摘要

To evaluate, by using computer image analysis, the mammographic density patterns of women with germ-line mutations in BRCA1 and BRCA2 genes in comparison with those of women at low risk of developing breast cancer.,Mammograms from 30 carriers of BRCA1 and BRCA2 mutations and from 142 low-risk women were collected retrospectively and digitized. In addition, 60 of the 142 low-risk women were randomly selected and age matched at 5-year intervals with the 30 mutation carriers. Mammographic features were extracted from the central regions of the breast images to characterize the mammographic density and heterogeneity of dense portions of the breast. These features were then merged into a single value related to the risk of breast cancer by using linear discriminant analysis. The applicability of these computer-extracted features and the output from linear discriminant analysis to differentiate between the carriers of BRCA1 and BRCA2 mutations and the low-risk women in the entire database and in an age-matched group were evaluated by using receiver operating characteristic analysis.,Quantitative analysis of mammograms demonstrated that carriers of BRCA1 and BRCA2 mutations tended to have dense breast tissue, and their mammographic patterns tended to be low in contrast, with a coarse texture. Linear discriminant analysis resulted in values of the areas under the receiver operating characteristic curve of 0.91 and 0.92 in distinguishing between the BRCA1 and BRCA2 mutation carriers and the low-risk women in the entire database and the age-matched group, respectively.,The computerized analysis of mammograms suggests that mammographic patterns in carriers of BRCA1 and BRCA2 mutations differ from those of women at low risk for breast cancer. Our computer-extracted features may be useful as radiographic markers for identifying women at high risk for breast cancer.

文献信息
期刊
Radiology
期刊简称
Radiology
发表日期
2002-11-19
收录日期
2002-10-31
更新日期
2016-11-24
语言
英语
国家/地区
United States
NLM ID
0401260
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