ArticleJapanese journal of radiology2017
Lung cancer screening with ultra-low dose CT using full iterative reconstruction.
Article in Japanese journal of radiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed, 33 citations in OpenAlex.
- Trial
- Utility of the virtual imaging trials methodology for objective characterization of AI systems and training data.Journal of medical imaging (Bellingham, Wash.) · 2026Article
- Structured narrative review on lung cancer screening: current evidence, clinical practice implications and implementation insights from a multidisciplinary task force and patient representatives.European respiratory review : an official journal of the European Respiratory Society · 2025Review
- Application of a pulmonary nodule detection program using AI technology to ultra-low-dose CT: differences in detection ability among various image reconstruction methods.Japanese journal of radiology · 2025Article
- Improved vascular depiction and image quality through deep learning reconstruction of CT hepatic arteriography during transcatheter arterial chemoembolization.Japanese journal of radiology · 2024Article
- Lung Cancer Screening with Low-Dose CT: What We Have Learned in Two Decades of ITALUNG and What Is Yet to Be Addressed.Diagnostics (Basel, Switzerland) · 2023Review
- Ultra-Low Dose CT Chest in Acute COVID-19 Pneumonia: A Pilot Study from India.Diagnostics (Basel, Switzerland) · 2023Article
- Can optimized model-based iterative reconstruction improve the contrast of liver lesions in CT?Acta radiologica (Stockholm, Sweden : 1987) · 2023Article
- Single CT Appointment for Double Lung and Colorectal Cancer Screening: Is the Time Ripe?Diagnostics (Basel, Switzerland) · 2022Review
- Dose estimation of ultra-low-dose chest CT to different sized adult patients.European radiology · 2019Article
- Implementation of lung cancer screening at the national level: Polish example.Translational lung cancer research · 2019Review
- Neointimal formation after carotid artery stenting: phantom and clinical evaluation of model-based iterative reconstruction (MBIR).European radiology · 2019Article
- Article
- Usefulness of model-based iterative reconstruction in semi-automatic volumetry for ground-glass nodules at ultra-low-dose CT: a phantom study.Radiological physics and technology · 2018Article
- Diagnostic accuracy of in-stent restenosis using model-based iterative reconstruction at coronary CT angiography: initial experience.The British journal of radiology · 2018Article
- Lung cancer screening with low dose CT and radiation harm-from prediction models to cancer incidence data.Annals of translational medicine · 2017Article
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo investigate the diagnostic capability of ultra-low-dose CT (ULDCT) with full iterative reconstruction (f-IR) for lung cancer screening. MATERIALS AND
methodsAll underwent ULDCT and/or low-dose CT (LD-CT) on a 320-detector scanner. ULDCT images were reconstructed with f-IR. We qualitatively and quantitatively studied 95 nodules in 69 subjects. Two radiologists classified the nodules on ULDCT images as solid-, part-solid-, and pure ground-glass (PGG) and recorded their mean size. Their findings were compared with the reference standard. The observer performance study included 7 other radiologists and 35 subjects with- and 15 without nodules. The results were analyzed by AFROC analysis.
resultsIn the qualitative study, the kappa values between observers 1 and 2, respectively, and the reference standard were 0.70 and 0.83; the intra-class correlation coefficients for the nodule diameter between the reference standard and their measurements were 0.84 and 0.90. The 95% confidence interval (CI) for the area under the curve (AUC) difference for nodule detection on LDCT and ULDCT was -0.03 to 0.07. The 95% CI crossed the 0 difference in the AUC but not the pre-defined non-inferiority margin of -0.08.
conclusionThe diagnostic ability of ULDCT using f-IR is comparable to LDCT.
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