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  • Title: Classification of fatty and dense breast parenchyma: comparison of automatic volumetric density measurement and radiologists' classification and their inter-observer variation.
    Author: Østerås BH, Martinsen AC, Brandal SH, Chaudhry KN, Eben E, Haakenaasen U, Falk RS, Skaane P.
    Journal: Acta Radiol; 2016 Oct; 57(10):1178-85. PubMed ID: 26792823.
    Abstract:
    BACKGROUND: Automatically calculated breast density is a promising alternative to subjective BI-RADS density assessment. However, such software needs a cutoff value for density classification. PURPOSE: To determine the volumetric density threshold which classifies fatty and dense breasts with highest accuracy compared to average BI-RADS density assessment, and to analyze radiologists' inter-observer variation. MATERIAL AND METHODS: A total of 537 full field digital mammography examinations were randomly selected from a population based screening program. Five radiologists assessed density using the BI-RADS density scale, where BI-RADS I-II were classified as fatty and III-IV as dense. A commercially available software (Quantra) calculated volumetric breast density. We calculated the cutoff (threshold) values in volumetric density that yielded highest accuracy compared to median and individual radiologists' classification. Inter-observer variation was analyzed using the kappa statistic. RESULTS: The threshold that best matched the median radiologists' classification was 10%, which resulted in 87% accuracy. Thresholds that best matched individual radiologist's classification had a range of 8-15%. A total of 191 (35.6 %) cases were scored both dense and fatty by at least one radiologist. Fourteen (2.6 %) cases were unanimously scored by the radiologists, yet differently using automatic assessment. The agreement (kappa) between reader's median classification and individual radiologists was 0.624 to 0.902, and agreement between median classification and Quantra was 0.731. CONCLUSION: The optimal volumetric threshold of 10% using automatic assessment would classify breast parenchyma as fatty or dense with substantial accuracy and consistency compared to radiologists' BI-RADS categorization, which suffers from high inter-observer variation.
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