ArticleRadiology2020
Observer Performance for Detection of Pulmonary Nodules at Chest CT over a Large Range of Radiation Dose Levels.
Article in Radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Development and validation of a CT-based comprehensive nomogram for differentiating benign from malignant subcentimeter solid nodules.Journal of thoracic disease · 2025Article
- Lung Cancers Associated with Cystic Airspaces.Cancers · 2025Review
- Development and validation of a noise insertion algorithm for photon-counting-detector CT.Medical physics · 2024Article
- Image quality evaluation in deep-learning-based CT noise reduction using virtual imaging trial methods: Contrast-dependent spatial resolution.Medical physics · 2024Article
- Impact of Simulated Reduced-Dose Chest CT on Diagnosing Pulmonary T1 Tumors and Patient Management.Diagnostics (Basel, Switzerland) · 2024Article
- Influence of CT dose reduction on AI-driven malignancy estimation of incidental pulmonary nodules.European radiology · 2024Article
- Tips and Tricks in Thoracic Radiology for Beginners: A Findings-Based Approach.Tomography (Ann Arbor, Mich.) · 2023Review
- Evaluation of deep-learning image reconstruction for chest CT examinations at two different dose levels.Journal of applied clinical medical physics · 2023Article
- Innovations in thoracic imaging: CT, radiomics, AI and x-ray velocimetry.Respirology (Carlton, Vic.) · 2022Review
- An interactive eye-tracking system for measuring radiologists' visual fixations in volumetric CT images: Implementation and initial eye-tracking accuracy validation.Medical physics · 2021Article
- Reproducibility of lung nodule radiomic features: Multivariable and univariable investigations that account for interactions between CT acquisition and reconstruction parameters.Medical physics · 2021Article
- Low-dose CT image and projection dataset.Medical physics · 2021Article
- Deep-learning lesion and noise insertion for virtual clinical trial in Chest CT.Proceedings of SPIE--the International Society for Optical Engineering · 2021Article
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14 authors.
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Abstract
Background There is a wide variation in radiation dose levels that can be used with chest CT in order to detect indeterminate pulmonary nodules. Purpose To compare the performance of lower-radiation-dose chest CT with that of routine dose in the detection of indeterminate pulmonary nodules 5 mm or greater. Materials and Methods In this retrospective study, CT projection data from 83 routine-dose chest CT examinations performed in 83 patients (120 kV, 70 quality reference mAs [QRM]) were collected between November 2013 and April 2014. Reference indeterminate pulmonary nodules were identified by two nonreader thoracic radiologists. By using validated noise insertion, five lower-dose data sets were reconstructed with filtered back projection (FBP) or iterative reconstruction (IR; 30 QRM with FBP, 10 QRM with IR, 5 QRM with FBP, 5 QRM with IR, and 2.5 QRM with IR). Three thoracic radiologists circled pulmonary nodules, rating confidence that the nodule was a 5-mm-or-greater indeterminate pulmonary nodule, and graded image quality. Analysis was performed on a per-nodule basis by using jackknife alternative free-response receiver operating characteristic figure of merit (FOM) and noninferiority limit of -0.10. Results There were 66 indeterminate pulmonary nodules (mean size, 8.6 mm ± 3.4 [standard deviation]; 21 part-solid nodules) in 42 patients (mean age, 51 years ± 17; 21 men and 21 women). Compared with the FOM for routine-dose CT (size-specific dose estimate, 6.5 mGy ± 1.8; FOM, 0.86 [95% confidence interval: 0.80, 0.91]), FOM was noninferior for all lower-dose configurations except for 2.5 QRM with IR. The sensitivity for subsolid nodules at 70 QRM was 60% (range, 48%-72%) and was significantly worse at a dose of 5 QRM and lower, whether or not IR was used (
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