ArticleThe British journal of radiology2021
Low-dose whole-body CT using deep learning image reconstruction: image quality and lesion detection.
Article in The British journal of radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.
- Deep-learning CT reconstruction in clinical scans of the abdomen: a systematic review and meta-analysis.Abdominal radiology (New York) · 2023Pooled it
- Impact of arm position on low dose dual-source CT one-step aortic and cerebral-carotid artery angiography image quality and radiation dose.BMC medical imaging · 2025Trial
- A single-view-based electroacoustic tomography imaging using deep learning for electroporation monitoring.Medical physics · 2026Article
- 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
- Ultra-low-dose hepatic computed tomography with a novel real-time deep learning-based noise reduction algorithm: a prospective cross-sectional analysis of image quality and lesion detection.Quantitative imaging in medicine and surgery · 2025Article
- Usefulness of four-dimensional noise reduction filtering using a similarity algorithm in low-dose dynamic computed tomography for the evaluation of breast cancer: a preliminary study.Japanese journal of radiology · 2025Article
- Practical application of heart modularization based on Personalized Patient Protocol Technology combined with Sinogram-Affirmed Iterative Reconstruction technology in coronary angiography.American journal of translational research · 2025Article
- Coronary atherosclerotic plaque characterization with silicon-based photon-counting computed tomography (CT): A simulation-based feasibility study.Medical physics · 2024Article
- Systematic Review on Learning-based Spectral CT.ArXiv · 2024Article
- Article
- Deep learning reconstruction vs standard reconstruction for abdominal CT: the influence of BMI.European radiology · 2024Article
- Systematic Review on Learning-based Spectral CT.IEEE transactions on radiation and plasma medical sciences · 2024Article
- Deep learning reconstruction CT for liver metastases: low-dose dual-energy vs standard-dose single-energy.European radiology · 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
- Virtual Surgical Planning, 3D-Printing and Customized Bone Allograft for Acute Correction of Severe Genu Varum in Children.Journal of personalized medicine · 2022Article
- Article
- Impact of an artificial intelligence deep-learning reconstruction algorithm for CT on image quality and potential dose reduction: A phantom study.Medical physics · 2022Article
- Unenhanced abdominal low-dose CT reconstructed with deep learning-based image reconstruction: image quality and anatomical structure depiction.Japanese journal of radiology · 2022Article
- Radiation and iodine dose reduced thoraco-abdomino-pelvic dual-energy CT at 40 keV reconstructed with deep learning image reconstruction.The British journal of radiology · 2022Article
- Deep learning image reconstruction algorithm for pancreatic protocol dual-energy computed tomography: image quality and quantification of iodine concentration.European radiology · 2022Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo evaluate image quality and lesion detection capabilities of low-dose (LD) portal venous phase whole-body computed tomography (CT) using deep learning image reconstruction (DLIR).
methodsThe study cohort of 59 consecutive patients (mean age, 67.2 years) who underwent whole-body LD CT and a prior standard-dose (SD) CT reconstructed with hybrid iterative reconstruction (SD-IR) within one year for surveillance of malignancy were assessed. The LD CT images were reconstructed with hybrid iterative reconstruction of 40% (LD-IR) and DLIR (LD-DLIR). The radiologists independently evaluated image quality (5-point scale) and lesion detection. Attenuation values in Hounsfield units (HU) of the liver, pancreas, spleen, abdominal aorta, and portal vein; the background noise and signal-to-noise ratio (SNR) of the liver, pancreas, and spleen were calculated. Qualitative and quantitative parameters were compared between the SD-IR, LD-IR, and LD-DLIR images. The CT dose-index volumes (CTDI
resultsThe image quality and lesion detection rate of the LD-DLIR was comparable to the SD-IR. The image quality was significantly better in SD-IR than in LD-IR (
conclusionLD CT images reconstructed with DLIR enable radiation dose reduction of >75% while maintaining image quality and lesion detection rate and superior SNR in comparison to SD-IR. ADVANCES IN KNOWLEDGE: Deep learning image reconstruction algorithm enables around 80% reduction in radiation dose while maintaining the image quality and lesion detection compared to standard-dose whole-body CT.
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