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Diagnostic Reference Levels based on clinical indications in computed tomography: a literature review

BACKGROUND: In August 2017, the European Commission awarded the “European Study on Clinical Diagnostic Reference levels for X-ray Medical Imaging” project to the European Society of Radiology, to provide up-to-date Diagnostic Reference Levels based on clinical indications. The aim of this work was t...

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Detalles Bibliográficos
Autores principales: Paulo, Graciano, Damilakis, John, Tsapaki, Virginia, Schegerer, Alexander A., Repussard, Jacques, Jaschke, Werner, Frija, Guy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7431477/
https://www.ncbi.nlm.nih.gov/pubmed/32804275
http://dx.doi.org/10.1186/s13244-020-00899-y
Descripción
Sumario:BACKGROUND: In August 2017, the European Commission awarded the “European Study on Clinical Diagnostic Reference levels for X-ray Medical Imaging” project to the European Society of Radiology, to provide up-to-date Diagnostic Reference Levels based on clinical indications. The aim of this work was to conduct an extensive literature review by analysing the most recent studies published and the data provided by the National Competent Authorities, to understand the current situation regarding Diagnostic Reference Levels based on clinical indications for computed tomography. RESULTS: The literature review has identified 23 papers with Diagnostic Reference Levels based on clinical indications for computed tomography from 15 countries; 12 of them from Europe. A total of 28 clinical indications for 6 anatomical areas (head, cervical spine/neck, chest, abdomen, abdomen-pelvis, chest-abdomen-pelvis) have been identified. CONCLUSIONS: In all the six anatomical areas for which Diagnostic Reference Levels based on clinical indications were found, a huge variation of computed tomography dose descriptor values was identified, providing evidence for a need to develop strategies to standardise and optimise computed tomography protocols.