Diagnostic Reference Levels in Computed Tomography in Switzerland
IFMBE ProceedingsWorld Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany(2009)
Abstract
Over the past few years the frequency of computed tomography (CT) examinations has dramatically increased. Simultaneously,
there has been also a significant increase in CT patient dose due to high-resolution imaging and application of more complex
scan techniques. Since no dose limit exists for patients, the International Commission on Radiological Protection introduced
the concept of diagnostic reference levels (DRL) as a means of dose optimization. The aim of this project is to collect patient
doses for the most frequently applied CT protocols and to provide a realistic basis for establishing DRL in CT in Switzerland.
Starting in 2007, patient doses of every Swiss radiological institute operating a CT scanner were going to be collected. Volume
computed tomography dose index (CTDIvol) and dose-length product (DLP) for standard patients was collected for selected clinical CT protocols. The 75th percentile of the CTDIvol and DLP distribution was calculated and compared to the proposed DRL which is partly based on the Swiss survey in 1998 and
recommendations of the European Union. For standard examination of the skull/brain the 75th percentiles are higher than the proposed DRL (72 mGy vs. 60 mGy; 1180 mGy∙cm vs. 1000 mGy∙cm). For examination of thorax
and abdomen/pelvis the 75th percentiles are close to the proposed DRL (thorax: 15 mGy vs. 15 mGy; 511 mGy∙cm vs. 450 mGy∙cm;
abdomen/ pelvis: 16 mGy vs. 15 mGy; 701 mGy∙cm vs. 700 mGy∙cm). In conclusion, there is always a trade-off between dose reduction
and diagnostic image quality. However, especially for skull/brain examinations, optimization is still feasible. The concept
of DRL provides a valuable means for practitioners and manufacturers in optimizing CT protocols.
MoreTranslated text
Key words
ctdi,switzerland,— diagnostic reference level,dlp.,computed tomo- graphy
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined