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Development and validation of image quality scoring criteria (IQSC) for pediatric CT: a preliminary study

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ObjectiveTo develop and assess the value and limitations of an image quality scoring criteria (IQSC) for pediatric CT exams.MethodsIQSC was developed for subjective assessment of image quality using the scoring… Click to show full abstract

ObjectiveTo develop and assess the value and limitations of an image quality scoring criteria (IQSC) for pediatric CT exams.MethodsIQSC was developed for subjective assessment of image quality using the scoring scale from 0 to 4, with 0 indicating desired anatomy or features not seen, 3 for adequate image quality, and 4 depicting higher than needed image quality. Pediatric CT examinations from 30 separate patients were selected, five each for routine chest, routine abdomen, kidney stone, appendicitis, craniosynostosis, and ventriculoperitoneal (VP) shunt. Five board-certified pediatric radiologists independently performed image quality evaluation using the proposed IQSC. The kappa statistics were used to assess the interobserver variability.ResultsAll five radiologists gave a score of 3 to two-third (67%) of all CT exams, followed by a score of 4 for 29% of CT exams, and 2 for 4% exams. The median image quality scores for all exams were 3 and the interobserver agreement among five readers (acceptable image quality [scores 3 or 4] vs sub-optimal image quality ([scores 1 and 2]) was moderate to very good (kappa 0.4–1). For all five radiologists, the lesion detection was adequate for all CT exams.ConclusionsThe image quality scoring criteria covering routine and some clinical indication-based imaging scenarios for pediatric CT examinations has potential to offer a simple and practical tool for assessing image quality with a reasonable degree of interobserver agreement. A more extensive and multi-centric study is recommended to establish wider usefulness of these criteria.

Keywords: image; image quality; criteria iqsc; quality scoring; scoring criteria

Journal Title: Insights into Imaging
Year Published: 2019

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