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Updated: May 9, 2025

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Published on: July 29, 2013
Intra- and inter-scanner CT variability and their impact on diagnostic tasks
Isabel Montero1, Saman Sotoudeh-Paima1, Ehsan Abadi1
1Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University, NC, United States.
Abstract:
The increased development and production of Computed Tomography (CT) scanner technology has expanded patient access to advanced and affordable medical imaging technologies but has also introduced sources of variability in the clinical imaging landscape, which may influence patient care. This study examines the impact of intra-scanner and inter-scanner variability on image quality and quantitative imaging tasks, with a focus on the detectability index (d') as a measure of patient-specific task performance. We evaluated 813 clinical phantom image sets from the COPDGene study, aggregated by CT scanner make, model, and acquisition and reconstruction protocol. Each phantom image set was assessed for image quality metrics, including the Noise Power Spectrum (NPS) and in-plane Modulation Transfer Function (MTF). The d' index was calculated for 12 hypothetical lesion detection tasks, emulating clinically relevant lung and liver lesions of varying sizes and contrast levels. Qualitatively, analysis showed intra-scanner variability in NPS and MTF curves measured for identical acquisition and reconstruction settings. Inter-scanner comparisons demonstrated variability in d' measurements across different scanner makes and models, of similar acquisition and reconstruction settings. The study showed an intra-scanner variability of up to 13.7% and an inter-scanner variability of up to 19.3% in the d' index. These findings emphasize the need for considering scanner variability in patient-centered care and indicate that CT technology may influence the reliability of imaging tasks. The results of this study further motivate the development of virtual scanner models to better model and mitigate the variability observed in the clinical imaging landscape.
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