ArticleThe British journal of radiology2015
The adaptive statistical iterative reconstruction-V technique for radiation dose reduction in abdominal CT: comparison with the adaptive statistical iterative reconstruction technique.
Article in The British journal of radiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 41 papers.
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41 citing papers in PubMed.
- Low-dose CT angiography using ASiR-V for potential living renal donors: a prospective analysis of image quality and diagnostic accuracy.European radiology · 2020Trial
- Improving image quality with model-based iterative reconstruction at quarter of nominal dose in upper abdominal CT.The British journal of radiology · 2019Trial
- Evaluation of image quality between hybrid iterative reconstruction and deep learning reconstruction in low dose abdominopelvic CT in low body mass index individuals.Scientific reports · 2026Article
- Effect of Deep Learning-Based Image Reconstruction on Lesion Conspicuity of Liver Metastases in Pre- and Post-contrast Enhanced Computed Tomography.Journal of imaging informatics in medicine · 2026Article
- Super-Resolution Deep Learning Reconstruction Improves Image Quality of Dynamic Myocardial Computed Tomography Perfusion Imaging.Tomography (Ann Arbor, Mich.) · 2026Article
- Optimization of image quality and diagnostic accuracy for vascular stenosis in computed tomography perfusion-reconstructed cerebral computed tomography angiography using deep learning reconstruction.Journal of clinical imaging science · 2026Article
- Improved CTA imaging for stroke evaluation - deep learning and iterative reconstruction comparative study.Neuroradiology · 2025Article
- Comparative evaluation of deep learning-based and conventional reconstruction techniques for image quality enhancement in low-dose chest computed tomography.Journal of thoracic disease · 2025Article
- Computed tomography dose index determination in dose modulation prospectively involving the third-generation iterative reconstruction and noise index.Journal of applied clinical medical physics · 2024Article
- Preoperative diagnostic value of multimodal spectral CT for patients with atrial fibrillation undergoing radiofrequency ablation.Frontiers in medicine · 2024Article
- Application of Deep Learning-Based Denoising Technique for Radiation Dose Reduction in Dynamic Abdominal CT: Comparison with Standard-Dose CT Using Hybrid Iterative Reconstruction Method.Journal of digital imaging · 2023Article
- A feasibility study of different GSI noise indexes and concentrations of contrast medium in hepatic CT angiography of overweight patients: image quality, radiation dose, and iodine intake.Japanese journal of radiology · 2023Article
- How Worrying Is the Impact of COVID-19 Pandemic on the Population Radiation Risk from Increased Number of CT-Scans?Journal of biomedical physics & engineering · 2023Article
- Assessment of low-dose paranasal sinus CT imaging using a new deep learning image reconstruction technique in children compared to adaptive statistical iterative reconstruction V (ASiR-V).BMC medical imaging · 2022Article
- Image Quality and Lesion Detectability of Lower-Dose Abdominopelvic CT Obtained Using Deep Learning Image Reconstruction.Korean journal of radiology · 2022Article
- An automated quantification method for the Agatston coronary artery calcium score on coronary computed tomography angiography.Quantitative imaging in medicine and surgery · 2022Article
- Deep Learning-Based Image Reconstruction for CT Angiography of the Aorta.Diagnostics (Basel, Switzerland) · 2021Article
- Deep learning image reconstruction for improvement of image quality of abdominal computed tomography: comparison with hybrid iterative reconstruction.Japanese journal of radiology · 2021Article
- Influence of Adaptive Statistical Iterative Reconstructions on CT Radiomic Features in Oncologic Patients.Diagnostics (Basel, Switzerland) · 2021Article
- Article
Corrections and comments
- Erratum issued
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8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo investigate whether reduced radiation dose abdominal CT images reconstructed with adaptive statistical iterative reconstruction V (ASIR-V) compromise the depiction of clinically competent features when compared with the currently used routine radiation dose CT images reconstructed with ASIR.
methods27 consecutive patients (mean body mass index: 23.55 kg m(-2) underwent CT of the abdomen at two time points. At the first time point, abdominal CT was scanned at 21.45 noise index levels of automatic current modulation at 120 kV. Images were reconstructed with 40% ASIR, the routine protocol of Dong-A University Hospital. At the second time point, follow-up scans were performed at 30 noise index levels. Images were reconstructed with filtered back projection (FBP), 40% ASIR, 30% ASIR-V, 50% ASIR-V and 70% ASIR-V for the reduced radiation dose. Both quantitative and qualitative analyses of image quality were conducted. The CT dose index was also recorded.
resultsAt the follow-up study, the mean dose reduction relative to the currently used common radiation dose was 35.37% (range: 19-49%). The overall subjective image quality and diagnostic acceptability of the 50% ASIR-V scores at the reduced radiation dose were nearly identical to those recorded when using the initial routine-dose CT with 40% ASIR. Subjective ratings of the qualitative analysis revealed that of all reduced radiation dose CT series reconstructed, 30% ASIR-V and 50% ASIR-V were associated with higher image quality with lower noise and artefacts as well as good sharpness when compared with 40% ASIR and FBP. However, the sharpness score at 70% ASIR-V was considered to be worse than that at 40% ASIR. Objective image noise for 50% ASIR-V was 34.24% and 46.34% which was lower than 40% ASIR and FBP.
conclusionAbdominal CT images reconstructed with ASIR-V facilitate radiation dose reductions of to 35% when compared with the ASIR. ADVANCES IN KNOWLEDGE: This study represents the first clinical research experiment to use ASIR-V, the newest version of iterative reconstruction. Use of the ASIR-V algorithm decreased image noise and increased image quality when compared with the ASIR and FBP methods. These results suggest that high-quality low-dose CT may represent a new clinical option.
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