ArticleEuropean radiology2017
Head CT: Image quality improvement with ASIR-V using a reduced radiation dose protocol for children.
Article in European radiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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21 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
- Advancements in radiation dose reduction for pediatric CT head Imaging: A scoping review of emerging Technologies, Protocols, and optimization strategies.Technical innovations & patient support in radiation oncology · 2026Review
- 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
- Pediatric low-dose head CT: Image quality improvement using iterative model reconstruction.The neuroradiology journal · 2023Article
- Deep learning-based reconstruction can improve the image quality of low radiation dose head CT.European radiology · 2023Article
- The value of using a deep learning image reconstruction algorithm of thinner slice thickness to balance the image noise and spatial resolution in low-dose abdominal CT.Quantitative imaging in medicine and surgery · 2023Article
- Adaptation of Deep Learning Image Reconstruction for Pediatric Head CT: A Focus on the Image Quality.Journal of the Korean Society of Radiology · 2023Article
- 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
- Deep learning image reconstruction algorithm for pancreatic protocol dual-energy computed tomography: image quality and quantification of iodine concentration.European radiology · 2022Article
- CT-based thermometry with virtual monoenergetic images by dual-energy of fat, muscle and bone using FBP, iterative and deep learning-based reconstruction.European radiology · 2022Article
- Application of a deep learning image reconstruction (DLIR) algorithm in head CT imaging for children to improve image quality and lesion detection.BMC medical imaging · 2021Article
- Impact of preset and postset adaptive statistical iterative reconstruction-V on image quality in nonenhanced abdominal-pelvic CT on wide-detector revolution CT.Quantitative imaging in medicine and surgery · 2021Article
- Image quality and dose reduction opportunity of deep learning image reconstruction algorithm for CT: a phantom study.European radiology · 2020Article
- Ultra-low-dose CT for extremities in an acute setting: initial experience with 203 subjects.Skeletal radiology · 2020Article
- Pediatric head computed tomography with advanced modeled iterative reconstruction: focus on image quality and reduction of radiation dose.Pediatric radiology · 2020Article
- Multicentre survey on patient dose in paediatric imaging and proposal for updated diagnostic reference levels for France. Part 1: computed tomography.European radiology · 2020Article
- Image Quality and Radiation Dose in CT Venography Using Model-Based Iterative Reconstruction at 80 kVp versus Adaptive Statistical Iterative Reconstruction-V at 70 kVp.Korean journal of radiology · 2019Article
- Comparison of Iterative Model Reconstruction versus Filtered Back-Projection in Pediatric Emergency Head CT: Dose, Image Quality, and Image-Reconstruction Times.AJNR. American journal of neuroradiology · 2019Article
- Potential value of the PixelShine deep learning algorithm for increasing quality of 70 kVp+ASiR-V reconstruction pelvic arterial phase CT images.Japanese journal of radiology · 2019Article
- Quantitative and qualitative evaluation of hybrid iterative reconstruction, with and without noise power spectrum models: A phantom study.Journal of applied clinical medical physics · 2018Article
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Abstract
objectiveTo investigate the quality of images reconstructed with adaptive statistical iterative reconstruction V (ASIR-V), using pediatric head CT protocols.
methodsA phantom was scanned at decreasing 20% mA intervals using our standard pediatric head CT protocols. Each study was then reconstructed at 10% ASIR-V intervals. After the phantom study, we reduced mA by 10% in the protocol for <3-year-old patients and applied 30% ASIR-V and by 30% in the protocol for 3- to 15-year-old patients and applied 40% ASIR-V.
resultsIncreasing the percentage of ASIR-V resulted in lower noise and higher contrast-to-noise ratio (CNR) and preserved spatial resolution in the phantom study. Compared to a conventional-protocol, reduced-dose protocol with ASIR-V achieved 12.8% to 34.0% of dose reduction and showed images of lower noise (9.22 vs. 10.73, P = 0.043) and higher CNR in different levels (centrum semiovale, 2.14 vs. 1.52, P = 0.003; basal ganglia, 1.46 vs. 1.07, P = 0.001; and cerebellum, 2.18 vs. 1.33, P < 0.001). Qualitative analysis showed higher gray-white matter differentiation and sharpness and preserved overall diagnostic quality in the images with ASIR-V.
conclusionsUse of ASIR-V allowed a 12.8% to 34.0% dose reduction in each age group with potential to improve image quality. KEY POINTS: • It is possible to reduce radiation dose and improve image quality with ASIR-V. • We improved noise and CNR and decreased radiation dose. • Sharpness improved with ASIR-V. • Total radiation dose was decreased by 12.8% to 34.0%.
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