ArticleBJR open2024
Detection, measurement, and diagnosis of lung nodules by ultra-low-dose CT in lung cancer screening: a systematic review.
Article in BJR open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Uncertainty-Aware Framework for CT Radiation Dose Optimization in the Active Surveillance of Small Renal Masses: Clinical and Radiological Considerations.Diagnostics (Basel, Switzerland) · 2026Article
- Clinical value of ultra-low-dose chest CT with deep learning image reconstruction in the detection and characterization of pulmonary nodules.Radiologie (Heidelberg, Germany) · 2026Article
- Early Detection of Lung Cancer: A Review of Innovative Milestones and Techniques.Journal of clinical medicine · 2025Review
- Lung Cancers Associated with Cystic Airspaces.Cancers · 2025Review
- Optimizing Chest Computed Tomography Imaging Protocols: A Narrative Review on Dose Reduction and Diagnostic Efficacy.Journal of medical physicsReview
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: There is a lack of recent meta-analyses and systematic reviews on the use of ultra-low-dose CT (ULDCT) for the detection, measurement, and diagnosis of lung nodules. This review aims to summarize the latest advances of ULDCT in these areas. Methods: A systematic review of studies in PubMed and Web of Science was conducted, using search terms specific to ULDCT and lung nodules. The included studies were published in the last 5 years (January 2019-August 2024). Two reviewers independently selected articles, extracted data, and assessed the risk of bias and concerns using the Quality Assessment of Diagnostic Accuracy Studies-II (QUADAS-II) tool. The standard-dose, low-dose, or contrast-enhanced CT served as the reference-standard CT to evaluate ULDCT. Results: The literature search yielded 15 high-quality articles on a total of 1889 patients, of which 10, 3, and 2 dealt with the detection, measurement, and diagnosis of lung nodules. QUADAS-II showed a generally low risk of bias. The mean radiation dose for ULDCT was 0.22 ± 0.10 mSv (7.7%) against 2.84 ± 1.80 mSv for reference-standard CT. Nodule detection rates ranged from 86.1% to 100%. The variability of diameter measurements ranged from 2.1% to 14.4% against contrast-enhanced CT and from 3.1% to 8.29% against standard CT. The diagnosis rate of malignant nodules ranged from 75% to 91%. Conclusions: ULDCT proves effective in detecting lung nodules while substantially reducing radiation exposure. However, the use of ULDCT for the measurement and diagnosis of lung nodules remains challenging and requires further research. Advances in knowledge: When ULDCT reduces radiation exposure to 7.7%, it detects lung nodules at a rate of 86.1%-100%, with a measurement variance of 2.1%-14.4% and a diagnostic accuracy for malignancy of 75%-91%, suggesting the potential for safe and effective lung cancer screening.
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