ArticleJournal of clinical imaging science2025
A multireader, multicase study comparing ultra-high-resolution and conventional-resolution computed tomography for lung nodule characterization.
Article in Journal of clinical imaging science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
8 authors.
Funding
Abstract
Objectives: The objective of the study was to evaluate the efficacy of ultra-high-resolution computed tomography (UHRCT) in comparison to conventional resolution computed tomography (CT) for the characterization of lung nodules. Material and Methods: 104 non-contrast chest UHRCT scans (mean age of 66 years, 57 females) with pulmonary nodules were retrospectively collected (February-November 2022), and corresponding normal-resolution (NR) reconstructions were synthesized using a validated algorithm. Five blinded radiologists scored the following for each localized nodule in the ultra-high-resolution (UHR) and NR datasets: Margin clarity (5-point Likert scale), image quality "IQ" (3-point), density confidence (0-100%), and size (long/short axes). Image noise (voxel standard deviation) was calculated within the trachea. Differences between UHR and NR were tested using the Wilcoxon signed-rank test. Intrareader agreement was quantified with intraclass correlation coefficient (ICC), and ordinal association between margin clarity and IQ was quantified with Kendall's Results: Margin clarity, IQ, and density confidence were significantly higher for UHR ( Conclusion: UHRCT offers significant improvements in the visualization of lung nodules compared to conventional resolution CT, albeit with an increase in image noise.
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