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Patient dose and image quality in low-dose abdominal CT: a comparison between iterative reconstruction and filtered back projection
Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Medicine and Health Sciences. Östergötlands Läns Landsting, Local Health Care Services in East Östergötland.
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.ORCID iD: 0000-0002-7750-1917
2013 (English)In: Acta Radiologica, ISSN 0284-1851, E-ISSN 1600-0455, Vol. 54, no 5, 540-548 p.Article in journal (Refereed) Published
Abstract [en]

Background In computed tomography (CT), there is increasing concern for potential CT radiation hazards. Several raw-data-based iterative reconstruction techniques attempt to facilitate low-dose imaging without compromising image quality, which raises the question whether these techniques may allow further dose reduction.

Purpose To compare image quality of iterative reconstruction and filtered back projection in low-dose abdominal CT and study the potential for further dose reduction.

Material and Methods Forty-five patients underwent CT of the abdomen twice: with standard low-dose technique and with 30% reduced dose, using both iterative reconstruction and filtered back projection. Four radiologists made pair-wise image quality assessment using five visual criteria. Visual grading regression (VGR) and weighted kappa (κ w) were used to analyze the data.

Results There were significant effects of log(mAs) (P <0.001) and reconstruction algorithm (P <0.01) on all image quality criteria with an estimated potential dose reduction of 5–9%. Inter-observer agreement ranged from 70% to 91% and κ w from −0.01 to 0.57.

Conclusion An iterative reconstruction algorithm improved image quality in abdominal CT, but the estimated dose reduction was rather small. The full potential of the algorithm remains unclear.

Place, publisher, year, edition, pages
2013. Vol. 54, no 5, 540-548 p.
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:liu:diva-90019DOI: 10.1177/0284185113476019ISI: 000322323400014PubMedID: 23474768OAI: oai:DiVA.org:liu-90019DiVA: diva2:611219
Available from: 2013-03-15 Created: 2013-03-15 Last updated: 2017-12-06Bibliographically approved

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Kataria, BhartiSmedby, Örjan
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Department of Medical and Health SciencesFaculty of Medicine and Health SciencesLocal Health Care Services in East ÖstergötlandCenter for Medical Image Science and Visualization (CMIV)RadiologyFaculty of Health SciencesDepartment of Radiology in Linköping
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