Østerås Bjørn Helge, Martinsen Anne Catrine T, Brandal Siri Helene B, Chaudhry Khalida Nasreen, Eben Ellen, Haakenaasen Unni, Falk Ragnhild Sørum, Skaane Per
The Intervention Centre, Oslo University Hospital, Oslo, Norway Institute of Clinical Medicine, University of Oslo, Oslo, Norway
The Intervention Centre, Oslo University Hospital, Oslo, Norway Institute of Physics, University of Oslo, Oslo, Norway.
Acta Radiol. 2016 Oct;57(10):1178-85. doi: 10.1177/0284185115626469. Epub 2016 Jan 20.
Automatically calculated breast density is a promising alternative to subjective BI-RADS density assessment. However, such software needs a cutoff value for density classification.
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.
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.
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.
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.
自动计算的乳房密度是主观的BI-RADS密度评估的一个有前景的替代方法。然而,此类软件需要一个密度分类的临界值。
确定与平均BI-RADS密度评估相比,能以最高准确率对脂肪型和致密型乳房进行分类的体积密度阈值,并分析放射科医生之间的观察者间差异。
从一项基于人群的筛查项目中随机选取了537例全视野数字乳腺摄影检查。五名放射科医生使用BI-RADS密度量表评估密度,其中BI-RADS I-II类被分类为脂肪型,III-IV类为致密型。一款商用软件(Quantra)计算乳房体积密度。我们计算了与中位数和个体放射科医生分类相比,在体积密度方面产生最高准确率的临界(阈值)值。使用kappa统计量分析观察者间差异。
与放射科医生中位数分类最匹配的阈值是10%,准确率为87%。与个体放射科医生分类最匹配的阈值范围为8%-15%。共有191例(35.6%)病例被至少一名放射科医生同时评为致密型和脂肪型。14例(2.6%)病例被放射科医生一致评分,但自动评估的结果不同。读者中位数分类与个体放射科医生之间的一致性(kappa)为0.624至0.902,中位数分类与Quantra之间的一致性为0.731。
与放射科医生的BI-RADS分类相比,使用自动评估的最佳体积阈值10%能够以较高的准确率和一致性将乳腺实质分类为脂肪型或致密型,而放射科医生的分类存在较高的观察者间差异。