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It has been suggested that digitized mammographic images contain computer-extractable information within the parenchymal pattern, which may contribute to distinguishing between <jats:italic>BRCA1\/2<\/jats:italic> mutation carriers and non-carriers.<\/jats:p>\n                     <\/jats:sec><jats:sec>\n                        <jats:title>Methods<\/jats:title>\n                        <jats:p>We compared mammographic texture pattern features in digitized mammograms from women with deleterious <jats:italic>BRCA1\/2<\/jats:italic> mutations (<jats:italic>n<\/jats:italic> = 137) versus non-carriers (<jats:italic>n<\/jats:italic> = 100). Subjects were stratified into training (107 carriers, 70 non-carriers) and testing (30 carriers, 30 non-carriers) datasets. Masked to mutation status, texture features were extracted from a retro-areolar region-of-interest in each subject\u2019s digitized mammogram. Stepwise linear regression analysis of the training dataset identified variables to be included in a radiographic texture analysis (RTA) classifier model aimed at distinguishing <jats:italic>BRCA1\/2<\/jats:italic> carriers from non-carriers. The selected features were combined using a Bayesian Artificial Neural Network (BANN) algorithm, which produced a probability score rating the likelihood of each subject\u2019s belonging to the mutation-positive group. These probability scores were evaluated in the independent testing dataset to determine whether their distribution differed between <jats:italic>BRCA1\/2<\/jats:italic> mutation carriers and non-carriers. A receiver operating characteristic analysis was performed to estimate the model\u2019s discriminatory capacity.<\/jats:p>\n                     <\/jats:sec><jats:sec>\n                        <jats:title>Results<\/jats:title>\n                        <jats:p>In the testing dataset, a one standard deviation (SD) increase in the probability score from the BANN-trained classifier was associated with a two-fold increase in the odds of predicting <jats:italic>BRCA1\/2<\/jats:italic> mutation status: unadjusted odds ratio (OR) = 2.00, 95% confidence interval (CI): 1.59, 2.51, <jats:italic>P<\/jats:italic> = 0.02; age-adjusted OR = 1.93, 95% CI: 1.53, 2.42, <jats:italic>P<\/jats:italic> = 0.03. Additional adjustment for percent mammographic density did little to change the OR. The area under the curve for the BANN-trained classifier to distinguish between <jats:italic>BRCA1\/2<\/jats:italic> mutation carriers and non-carriers was 0.68 for features alone and 0.72 for the features plus percent mammographic density.<\/jats:p>\n                     <\/jats:sec><jats:sec>\n                        <jats:title>Conclusions<\/jats:title>\n                        <jats:p>Our findings suggest that, unlike percent mammographic density, computer-extracted mammographic texture pattern features are associated with carrying <jats:italic>BRCA1\/2<\/jats:italic> mutations. Although still at an early stage, our novel RTA classifier has potential for improving mammographic image interpretation by permitting real-time risk stratification among women undergoing screening mammography.<\/jats:p>\n                     <\/jats:sec>","DOI":"10.1186\/s13058-014-0424-8","type":"journal-article","created":{"date-parts":[[2014,8,21]],"date-time":"2014-08-21T23:36:03Z","timestamp":1408664163000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Relationships between computer-extracted mammographic texture pattern features and BRCA1\/2mutation status: a cross-sectional study"],"prefix":"10.1186","volume":"16","author":[{"given":"Gretchen L","family":"Gierach","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jennifer T","family":"Loud","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark H","family":"Greene","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Catherine K","family":"Chow","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Lan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sheila A","family":"Prindiville","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jennifer","family":"Eng-Wong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter W","family":"Soballe","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claudia","family":"Giambartolomei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Phuong L","family":"Mai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claudia E","family":"Galbo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kathryn","family":"Nichols","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kathleen A","family":"Calzone","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Olufunmilayo I","family":"Olopade","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mitchell H","family":"Gail","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maryellen L","family":"Giger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2014,8,23]]},"reference":[{"key":"424_CR1","first-page":"1133","volume":"7","author":"NF Boyd","year":"1998","unstructured":"Boyd NF, Lockwood GA, Byng JW, Tritchler DL, Yaffe MJ: Mammographic densities and breast cancer risk. 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