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Quantifying the potential for dose reduction with visual grading regression
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.ORCID iD: 0000-0002-7750-1917
Linköping University, Department of Clinical and Experimental Medicine, Occupational and Environmental Medicine. Linköping University, Faculty of Health Sciences.
Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences.
Drammen Hospital, Norway .
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2013 (English)In: British Journal of Radiology, ISSN 0007-1285, E-ISSN 1748-880X, Vol. 86, no 1021Article in journal (Refereed) Published
Abstract [en]

Objectives To propose a method to study the effect of exposure settings on image quality and to estimate the potential for dose reduction when introducing dose-reducing measures.

Methods Using the framework of visual grading regression (VGR), a log(mAs) term is included in the ordinal logistic regression equation, so that the effect of reducing the dose can be quantitatively related to the effect of adding post-processing. In the ordinal logistic regression, patient and observer identity are treated as random effects using generalised linear latent and mixed models. The potential dose reduction is then estimated from the regression coefficients. The method was applied in a single-image study of coronary CT angiography (CTA) to evaluate two-dimensional (2D) adaptive filters, and in an image-pair study of abdominal CT to evaluate 2D and three-dimensional (3D) adaptive filters.

Results For five image quality criteria in coronary CTA, dose reductions of 16–26% were predicted when adding 2D filtering. Using five image quality criteria for abdominal CT, it was estimated that 2D filtering permits doses were reduced by 32–41%, and 3D filtering by 42–51%.

Conclusions VGR including a log(mAs) term can be used for predictions of potential dose reduction that may be useful for guiding researchers in designing subsequent studies evaluating diagnostic value. With appropriate statistical analysis, it is possible to obtain direct numerical estimates of the dose-reducing potential of novel acquisition, reconstruction or post-processing techniques.

Place, publisher, year, edition, pages
British Institute of Radiology , 2013. Vol. 86, no 1021
National Category
Medical and Health Sciences
URN: urn:nbn:se:liu:diva-90212DOI: 10.1259/bjr/31197714ISI: 000315266900029OAI: diva2:613160
Available from: 2013-04-02 Created: 2013-03-21 Last updated: 2014-04-01Bibliographically approved

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Smedby, ÖrjanFredrikson, Matsde Geer, JakobSandborg, Michael
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Center for Medical Image Science and Visualization (CMIV)Division of Radiological SciencesFaculty of Health SciencesDepartment of Radiology in LinköpingOccupational and Environmental MedicineRadiologyRadiation PhysicsDepartment of Radiation Physics
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