ArticleThe British journal of radiology2019
Clinical value of a new generation adaptive statistical iterative reconstruction (ASIR-V) in the diagnosis of pulmonary nodule in low-dose chest CT.
Article in The British journal of radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed, 20 citations in OpenAlex.
- Comparison of DLIR-H and ASIR algorithms for image reconstruction in low-dose chest CT of pediatric mycoplasma pneumoniae pneumonia: a cross-sectional study.Translational pediatrics · 2026Article
- Study on the combined application of selected virtual monoenergetic imaging, virtual non-contrast imaging, and adaptive statistical iterative reconstruction-V in head and neck CT angiography using 256-slice wide-body CT.Frontiers in medicine · 2026Article
- Impact of Combined Deep Learning Image Reconstruction and Metal Artifact Reduction Algorithm on CT Image Quality in Different Scanning Conditions for Maxillofacial Region with Metal Implants: A Phantom Study.Journal of imaging informatics in medicine · 2025Article
- Dual-layer spectral detector CT electron density imaging: impressive technology for imaging characteristics of ground-glass nodules.Quantitative imaging in medicine and surgery · 2025Article
- Deep learning reconstruction improves computer-aided pulmonary nodule detection and measurement accuracy for ultra-low-dose chest CT.BMC medical imaging · 2025Article
- Assessing the effect of scanning parameter on the size and density of pulmonary nodules: a phantom study.BMC medical imaging · 2024Article
- The Value of Deep Learning Image Reconstruction in Improving the Quality of Low-Dose Chest CT Images.Diagnostics (Basel, Switzerland) · 2022Article
- 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
- Deep learning image reconstruction in pediatric abdominal and chest computed tomography: a comparison of image quality and radiation dose.Quantitative imaging in medicine and surgery · 2022Article
- Application of deep learning image reconstruction in low-dose chest CT scan.The British journal of radiology · 2022Article
- The Application Value of CT Three-Dimensional Microscope Reconstruction Technology in the Diagnosis of Cervical Cancer.Scanning · 2022Article
- Deep learning image reconstruction algorithm for pancreatic protocol dual-energy computed tomography: image quality and quantification of iodine concentration.European radiology · 2022Article
- Low keV portal venous phase as a surrogate for pancreatic phase in a pancreatic protocol dual-energy CT: feasibility, image quality, and lesion conspicuity.European radiology · 2021Article
- Value of low-dose and optimized-length computed tomography (CT) scan in CT-guided percutaneous transthoracic needle biopsy of pulmonary nodules.Journal of interventional medicine · 2021Article
- Cycle-Consistent Generative Adversarial Network: Effect on Radiation Dose Reduction and Image Quality Improvement in Ultralow-Dose CT for Evaluation of Pulmonary Tuberculosis.Korean journal of radiology · 2021Article
- A study of using a deep learning image reconstruction to improve the image quality of extremely low-dose contrast-enhanced abdominal CT for patients with hepatic lesions.The British journal of radiology · 2021Article
- Image quality and dose reduction opportunity of deep learning image reconstruction algorithm for CT: a phantom study.European radiology · 2020Article
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8 authors at 1 institution in 1 country.
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Abstract
objectiveTo evaluate the clinical value of low-dose chest CT combined with the new generation adaptive statistical iterative reconstruction (ASIR-V) algorithm in the diagnosis of pulmonary nodule.
methods30 patients with pulmonary nodules underwent chest CT using Revolution CT. The patients were first scanned with standard-dose at a noise index (NI) of 14, and the images were reconstructed with filtered back projection (FBP) algorithm. If pulmonary nodules were found, a low-dose targeted scan, with NI of 24, was performed localized on the nodules, and the images were reconstructed with 60% ASIR-V. The detection rate of pulmonary nodules in the two scanning modes was recorded. The size of nodules, CT value and standard deviation of nodules were measured. The signal-to-noise ratio and contrast-to-noise ratio were also calculated. Two experienced radiologists used a 5-point method to score the image quality. The volumetric CT dose index, and dose-length product were recorded and the effective dose (ED) was calculated of the two scanning modes.
resultsVolumetric CT dose index (ED) of the standard-dose scan covering the entire lungs was 7.29 ± 2.38 mGy (3.52 ± 1.09 mSv), and that of low-dose targeted scan was 2.56 ± 1.87 mGy (0.51 ± 0.32 mSv). However, the ED of the virtual low-dose scan for the entire lungs was 1.44 ± 0.15 mSv, which would mean a dose reduction of 59.1% compared with the standard-dose scan. 85 of the 87 pulmonary nodules were detected in the low-dose targeted scan, with 2 of the ground-glass density nodules with size less than 1 cm missed, resulting in 97.7% overall detection rate. There was no difference between the low-dose ASIR-V images and standard-dose FBP images for the size (1.49 ± 0.74 cm
conclusionThe low-dose CT scan combined with ASIR-V algorithm is of comparable value in the detection and the display of pulmonary nodules when compared with the FBP images obtained by standard-dose scan. ADVANCES IN KNOWLEDGE: This is a clinical study to evaluate the clinical value of pulmonary nodules using ASIR-V algorithm in the same patients in the low-dose chest CT scans. It suggests that ASIR-V provides similar image quality and detection rate for pulmonary nodules at much reduced radiation dose.
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