PURPOSE: To evaluate the accuracy of scintimammography as an adjunct to physical examination and mammography in the detection of breast cancer in women with dense and fatty breasts. MATERIALS AND METHODS: A total of 558 women were prospectively enrolled from 42 centers in North America. Images were interpreted by readers blinded to the subjects' clinical history, mammographic findings, and other test results. The Breast Imaging Reporting and Data System classification was used to describe breast density. Parenchymal patterns of "heterogeneously dense" and "extremely dense" were used to classify breasts as dense, whereas "almost entirely fat" and "numerous vague densities" defined fatty breasts. Between-group differences were evaluated with the 2 test for categorical variables and Student t test for continuous variables. Accuracy of scintimammography was assessed against the core laboratory histopathologic evaluation, the standard. The 95% CIs around point estimates of sensitivity, specificity, and positive and negative predictive values were calculated with the normal approximation to the binomial distribution. RESULTS: The analyses were based on 580 breasts with an abnormality; 276 (48%) breasts were dense and 228 had a malignant lesion. Diagnostic properties for scintimammography of fatty versus dense breasts were, respectively, sensitivity, 72% versus 70%; specificity, 80% versus 78%; positive predictive value, 72% versus 67%; negative predictive value, 81% versus 81%; and accuracy, 77% versus 75% (all not significant). Scintimammography led to similar and significant changes in the posttest likelihood of cancer for both dense and fatty breasts. CONCLUSION: The diagnostic accuracy of scintimammography is not affected by breast density.
PURPOSE: To evaluate the accuracy of scintimammography as an adjunct to physical examination and mammography in the detection of breast cancer in women with dense and fatty breasts. MATERIALS AND METHODS: A total of 558 women were prospectively enrolled from 42 centers in North America. Images were interpreted by readers blinded to the subjects' clinical history, mammographic findings, and other test results. The Breast Imaging Reporting and Data System classification was used to describe breast density. Parenchymal patterns of "heterogeneously dense" and "extremely dense" were used to classify breasts as dense, whereas "almost entirely fat" and "numerous vague densities" defined fatty breasts. Between-group differences were evaluated with the 2 test for categorical variables and Student t test for continuous variables. Accuracy of scintimammography was assessed against the core laboratory histopathologic evaluation, the standard. The 95% CIs around point estimates of sensitivity, specificity, and positive and negative predictive values were calculated with the normal approximation to the binomial distribution. RESULTS: The analyses were based on 580 breasts with an abnormality; 276 (48%) breasts were dense and 228 had a malignant lesion. Diagnostic properties for scintimammography of fatty versus dense breasts were, respectively, sensitivity, 72% versus 70%; specificity, 80% versus 78%; positive predictive value, 72% versus 67%; negative predictive value, 81% versus 81%; and accuracy, 77% versus 75% (all not significant). Scintimammography led to similar and significant changes in the posttest likelihood of cancer for both dense and fatty breasts. CONCLUSION: The diagnostic accuracy of scintimammography is not affected by breast density.
Authors: Emilio Bombardieri; Cumali Aktolun; Richard P Baum; Angelika Bishof-Delaloye; John Buscombe; Jean François Chatal; Lorenzo Maffioli; Roy Moncayo; Luc Mortelmans; Sven N Reske Journal: Eur J Nucl Med Mol Imaging Date: 2003-12 Impact factor: 9.236
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Authors: Katja Pinker; Wolfgang Bogner; Stephan Gruber; Peter Brader; Siegfried Trattnig; Georgios Karanikas; Thomas H Helbich Journal: Breast Care (Basel) Date: 2011-04-29 Impact factor: 2.860
Authors: Caryl N Brzymialkiewicz; Martin P Tornai; Randolph L McKinley; James E Bowsher Journal: IEEE Trans Med Imaging Date: 2005-07 Impact factor: 10.048
Authors: B Bagni; A Franceschetto; A Casolo; M De Santis; I Bagni; F Pansini; C Di Leo Journal: Eur J Nucl Med Mol Imaging Date: 2003-08-09 Impact factor: 9.236
Authors: Zhonglin Liu; Gail D Stevenson; Harrison H Barrett; George A Kastis; Michel Bettan; Lars R Furenlid; Donald W Wilson; James M Woolfenden; Koon Yan Pak Journal: Nucl Med Commun Date: 2004-07 Impact factor: 1.690