A method to analyse observer disagreement in visual grading studies: example of assessed image quality in paediatric cerebral multidetector CT images
Abstract
The purpose was to demonstrate a non-parametric statistical method that can identify and explain the components of observer disagreement in terms of systematic disagreement as well as additional individual variability, in visual grading studies. As an example, the method was applied to a study where the effect of reduced tube current on diagnostic image quality in paediatric cerebral multidetector CT (MDCT) images was investigated. Quantum noise, representing dose reductions equivalent to steps of 20 mA, was artificially added to the raw data of 25 retrospectively selected paediatric cerebral MDCT examinations. Three radiologists, blindly and randomly, assessed the resulting images from two different levels of the brain with regard to the reproduction of high- and low-contrast structures and overall image quality. Images from three patients were assessed twice for the analysis of intra-observer disagreement. The intra-observer disagreement in test-retest assessments could mainly be explained by a systematic change towards lower image quality the second time the image was reviewed. The inter-observer comparisons showed that the paediatric radiologist was more critical of the overall image quality, while the neuroradiologists were more critical of the reproduction of the basal ganglia. Differences between the radiologists regarding the extent to which they used the whole classification scale were also found. The statistical method used was able to identify and separately…
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Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence.
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