PURPOSE: To retrospectively evaluate whether microcalcification descriptors and the categorization of microcalcification descriptors in the Breast Imaging Reporting and Data System (BI-RADS) 4th edition help stratify the risk of malignancy, by using biopsy and clinical follow-up as reference standards. MATERIALS AND METHODS: The institutional review board approved this HIPAA-compliant study and waived informed consent. The study included 115 women (age range, 26-82 years; mean age, 55.8 years +/- 10.5 [standard deviation]) who consecutively underwent image-guided biopsy of microcalcifications between November 2001 and October 2002. Screening and diagnostic mammograms (including magnification views) obtained before biopsy were analyzed in a blinded manner by a subspecialty-trained breast imager who recorded BI-RADS descriptors on a checklist. The proportion of malignant cases was used as the outcome variable to evaluate the ability of the descriptors to help capture the risk of malignancy. Fisher exact test was used to calculate the difference among the individual descriptors and descriptor categories. RESULTS: The positive predictive value of biopsy for malignancy was 21.7%. Each calcification morphologic descriptor was able to help stratify the probability of malignancy as follows: coarse heterogeneous, one (7%) of 14; amorphous, four (13%) of 30; fine pleomorphic, 10 (29%) of 34; and fine linear, 10 (53%) of 19. Fisher exact test results revealed a significant difference among these descriptor categories (P = .005). Significant differences among the risks suggested by microcalcification distribution descriptors (P = .004) and between that of stability descriptors (P = .001) were found. CONCLUSION: The microcalcification descriptors and categories in BI-RADS 4th edition help predict the risk of malignancy for suspicious microcalcifications. (c) RSNA, 2007.
PURPOSE: To retrospectively evaluate whether microcalcification descriptors and the categorization of microcalcification descriptors in the Breast Imaging Reporting and Data System (BI-RADS) 4th edition help stratify the risk of malignancy, by using biopsy and clinical follow-up as reference standards. MATERIALS AND METHODS: The institutional review board approved this HIPAA-compliant study and waived informed consent. The study included 115 women (age range, 26-82 years; mean age, 55.8 years +/- 10.5 [standard deviation]) who consecutively underwent image-guided biopsy of microcalcifications between November 2001 and October 2002. Screening and diagnostic mammograms (including magnification views) obtained before biopsy were analyzed in a blinded manner by a subspecialty-trained breast imager who recorded BI-RADS descriptors on a checklist. The proportion of malignant cases was used as the outcome variable to evaluate the ability of the descriptors to help capture the risk of malignancy. Fisher exact test was used to calculate the difference among the individual descriptors and descriptor categories. RESULTS: The positive predictive value of biopsy for malignancy was 21.7%. Each calcification morphologic descriptor was able to help stratify the probability of malignancy as follows: coarse heterogeneous, one (7%) of 14; amorphous, four (13%) of 30; fine pleomorphic, 10 (29%) of 34; and fine linear, 10 (53%) of 19. Fisher exact test results revealed a significant difference among these descriptor categories (P = .005). Significant differences among the risks suggested by microcalcification distribution descriptors (P = .004) and between that of stability descriptors (P = .001) were found. CONCLUSION: The microcalcification descriptors and categories in BI-RADS 4th edition help predict the risk of malignancy for suspicious microcalcifications. (c) RSNA, 2007.
Authors: Elizabeth S Burnside; Jie Liu; Yirong Wu; Adedayo A Onitilo; Catherine A McCarty; C David Page; Peggy L Peissig; Amy Trentham-Dietz; Terrie Kitchner; Jun Fan; Ming Yuan Journal: Acad Radiol Date: 2015-10-26 Impact factor: 3.173
Authors: Lars J Grimm; David Y Johnson; Karen S Johnson; Jay A Baker; Mary Scott Soo; E Shelley Hwang; Sujata V Ghate Journal: Eur Radiol Date: 2016-10-17 Impact factor: 5.315
Authors: Elizabeth S Burnside; Edward A Sickles; Lawrence W Bassett; Daniel L Rubin; Carol H Lee; Debra M Ikeda; Ellen B Mendelson; Pamela A Wilcox; Priscilla F Butler; Carl J D'Orsi Journal: J Am Coll Radiol Date: 2009-12 Impact factor: 5.532