Suleiman Moayyad E, Brennan Patrick C, McEntee Mark F
The University of Sydney , Faculty of Health Sciences, M205, Cumberland Campus, 75 East Street, Lidcombe, New South Wales 2141, Australia.
J Med Imaging (Bellingham). 2017 Jan;4(1):013502. doi: 10.1117/1.JMI.4.1.013502. Epub 2017 Jan 24.
Our objective was to analyze the agreement between organ dose estimated by different digital mammography units and calculated dose for clinical data. Digital Imaging and Communication in Medicine header information was extracted from 52,405 anonymized mammograms. Data were filtered to include images with no breast implants, breast thicknesses 20 to 110 mm, and complete exposure and quality assurance data. Mean glandular dose was calculated using methods by Dance et al., Wu et al., and Boone et al. Bland-Altman analysis and regression were used to study the agreement and correlation between organ and calculated doses. Bland-Altman showed statistically significant bias between organ and calculated doses. The bias differed for different unit makes and models; Philips had the lowest bias, overestimating Dance method by 0.03 mGy, while general electric had the highest bias, overestimating Wu method by 0.20 mGy, the Hologic organ dose underestimated Boone method by 0.07 mGy, and the Fujifilm organ dose underestimated Dance method by 0.09 mGy. Organ dose was found to disagree with our calculated dose, yet organ dose is potentially beneficial for rapid dose audits. Conclusions drawn based on the organ dose alone come with a risk of over or underestimating the calculated dose to the patient and this error should be considered in any reported results.
我们的目标是分析不同数字乳腺摄影设备估算的器官剂量与临床数据计算剂量之间的一致性。从52405份匿名乳腺造影片中提取医学数字成像和通信(DICOM)头信息。对数据进行筛选,纳入没有乳房植入物、乳房厚度为20至110毫米且有完整曝光和质量保证数据的图像。使用丹斯等人、吴等人以及布恩等人的方法计算平均腺体剂量。采用布兰德-奥特曼分析和回归分析来研究器官剂量与计算剂量之间的一致性和相关性。布兰德-奥特曼分析显示器官剂量与计算剂量之间存在统计学上的显著偏差。不同设备品牌和型号的偏差有所不同;飞利浦的偏差最小,比丹斯方法高估0.03毫戈瑞,而通用电气的偏差最大,比吴方法高估0.20毫戈瑞,豪洛捷的器官剂量比布恩方法低估0.07毫戈瑞,富士胶片的器官剂量比丹斯方法低估0.09毫戈瑞。发现器官剂量与我们计算的剂量不一致,但器官剂量可能有助于快速进行剂量审核。仅基于器官剂量得出的结论存在高估或低估患者计算剂量的风险,任何报告结果都应考虑这一误差。