H. Schiabel, Eny Moreira Ruberti Filha, Oswaldo Jorge Neto, L. B. Verçosa
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引用次数: 0
摘要
国际原子能机构(IAEA)等负责 X 射线系统质量控制的国际监管组织已经实施了数字乳腺 X 射线照相术和乳腺断层合成术设备验收测试协议,旨在建立放射服务的质量标准。然而,这些指南通常都是基于具有标准化厚度和成分的乳房模型进行测试,而这些模型通常并不能代表这些服务机构的病人群体特征。在之前的一项研究中,我们开发了一个计算系统,用于自动跟踪和管理从数字乳腺 X 射线照相术和乳腺断层合成术图像采集过程中提取的数据,这些数据存储在 DICOM SCP(服务类提供商)服务器上。测试表明,乳腺成分和辐射剂量国际标准中列出的参考水平并不能准确反映实际患者群体的特征。因此,本研究描述了主要针对不同放射服务机构的三台数字乳腺 X 射线摄影系统的剂量跟踪过程的数据收集和相应分析。这些系统的大量图像数据集是通过之前介绍过的一种新应用软件获取的,重点是曝光过程中产生的剂量曲线。数据集生成的图表展示了皮肤入口剂量和平均腺体剂量分布、检查期间使用的平均 kV 和 mAs 以及目标/滤波器组合、放射密度分布,以及每个乳腺 X 射线照相服务机构接受照射人群的年龄和乳房厚度特征。此外,还讨论了数字乳腺 X 射线照相服务性能评估工具所提供信息的范围和获取的难易程度。
Radiation Dose Tracking in Digital Mammography: Evaluation of Population Profiles through Automatic Data Extraction from the DICOM Header
International regulatory organizations for quality control of X-ray systems, such as the International Atomic Energy Agency (IAEA), have implemented protocols for acceptance testing of digital mammography and breast tomosynthesis equipment, aiming to establish quality standards in radiology services. However, these guidelines are usually based on tests with breast phantoms with standardizedthicknesses and compositions, often not representative of the patient population profiles at those services. In a prior study, we developed a computational system designed to automatically tracking and managing data extracted from the image acquisition processes of digital mammography and breast tomosynthesis, stored on a DICOM SCP (Service Class Provider) server. This approach enables obtaining technical reports characterizing exposure parameters and tests have shown that the reference levels outlined in international standards for breast composition and radiation dose do not accurately reflect the characteristics of the actual patient population. Thus this study describes data collection and corresponding analysis for the dose tracking process primarily on three digital mammography systems of different radiological services. Extensive image datasets from these systems were obtained using a new application described previously, with a focus on dose profiles generated during exposures. Graphical representations resultingfrom the datasets are presented, along with analysis of skin entrance and mean glandular doses distributions, average kV and mAs applied during the exams together with the target/filter combinations, radiographic density distribution, as well as the age and breast thickness characteristic of the respective population submitted to exposures in each of those mammography services. Additionally, the extent of information and ease of acquisition provided by the tool for performance evaluation of digital mammography services is discussed