Calderoni Francesca, Campanaro Federica, Colombo Paola Enrica, Campoleoni Mauro, De Mattia Cristina, Rottoli Federica, Galetta Giannicola, Zucconi Fabio, Pola Andrea, Righini Andrea, Triulzi Fabio, Vanzulli Angelo, Torresin Alberto
Department of Medical Physics, ASST Grande Ospedale Metropolitano Niguarda, Piazza Ospedale Maggiore 3, 20162, Milan, Italy.
Medical Physics Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Pace 9, 20122, Milan, Italy.
Eur Radiol Exp. 2019 Jul 16;3(1):27. doi: 10.1186/s41747-019-0105-6.
To manage and analyse dosimetric data provided by computed tomography (CT) scanners from four Italian hospitals.
A radiation dose index monitoring (RDIM) software was used to collect anonymised exams stored in a cloud server. Since hospitals use different names for the same procedure, digital imaging and communications in medicine (DICOM) tags more appropriate to describe exams were selected and associated to study common names (SCNs) from a radiology playbook according to scan region and use of contrast media. Retrospective analysis was carried out to describe population and to evaluate dosimetric indexes and inaccuracies associated with SCNs.
More than 400 procedures were clustered into 95 SCNs, but 78% of exams on adults were described with only 10 SCNs. Median values of dose-length product (DLP) and volumetric CT dose index (CTDI) for three analysed SCNs were in agreement with those previously published. The percentage of inaccuracies does not heavily affect the dosimetric analysis on the whole cloud, since variations in median values reached at most 8%.
Implementation of a cloud-based RDIM software and related issues were described, showing the strength of the chosen playbook-based clustering and its usefulness for homogeneous data analysis. This approach may allow for optimisation actions, accurate assessment of the risk associated with radiation exposure, comparison of different facilities, and, last but not least, collection of information for the implementation of the 2013/59 Euratom Directive.
管理和分析来自四家意大利医院的计算机断层扫描(CT)扫描仪提供的剂量数据。
使用辐射剂量指数监测(RDIM)软件收集存储在云服务器中的匿名检查数据。由于医院对同一检查使用不同名称,因此根据扫描区域和造影剂的使用情况,选择了更适合描述检查的医学数字成像和通信(DICOM)标签,并将其与放射学手册中的研究通用名称(SCN)相关联。进行回顾性分析以描述人群,并评估与SCN相关的剂量指数和误差。
400多个检查程序被归类为95个SCN,但78%的成人检查仅用10个SCN描述。三个分析的SCN的剂量长度乘积(DLP)和容积CT剂量指数(CTDI)的中位数与先前发表的值一致。误差百分比对整个云的剂量分析影响不大,因为中位数的变化最多达到8%。
描述了基于云的RDIM软件的实施及相关问题,展示了所选的基于手册的聚类方法的优势及其在同类数据分析中的有用性。这种方法可能允许采取优化措施,准确评估与辐射暴露相关的风险,比较不同设施,以及最后但同样重要的是,收集信息以实施2013/59号欧盟原子指令。