层析合成
技术
数字乳腺摄影术
乳腺摄影术
医学
标准差
医学物理学
放射科
计算机科学
召回率
人工智能
乳腺癌
统计
数学
癌症
内科学
作者
Andrew P. Smith,Elizabeth A. Rafferty,Loren Niklason
标识
DOI:10.1007/978-3-540-70538-3_9
摘要
This study reports the performance of breast tomosynthesis (3D images) combined with digital mammography (2D images), compared to digital mammography alone, as a function of the experience of the radiologist. In this trial, twelve readers analyzed 316 image sets, giving BIRADS (and other) scores first for the digital mammograms, and subsequently for the combined datasets of tomosynthesis and digital mammograms. Clinical performance was measured using two metrics: area under the ROC curve (AUROC) and recall rate, and was analyzed as a function of the experience level. The study found that all radiologists AUROC improved when using 3D+2D compared to 2D, with no correlation with experience level, increasing by 0.077 ± 0.058 (mean ± 1 standard deviation) for the 5 least experienced and increasing by 0.078 ± 0.029 for the 5 most experienced. Similarly, the use of 3D+2D compared to 2D imaging showed a mean decrease in recall rate of 39.2% for the most experienced and a decrease of 39.6% for the least experienced, again with no correlation found with experience level. In summary, radiologists with a range of experience demonstrated improved performance using tomosynthesis in combination with digital mammography (3D+2D), as measured using recall rate reduction and AUROC metrics.
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