ArticleThe British journal of radiology2022
Radiation and iodine dose reduced thoraco-abdomino-pelvic dual-energy CT at 40 keV reconstructed with deep learning image reconstruction.
Article in The British journal of radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07305103 (Defining Dosimetric Reference Levels in Computed Tomography Spectral Scanning), which is not on this map. Cited by 20 papers, 2 of them syntheses that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Defining Dosimetric Reference Levels in Computed Tomography Spectral Scanning
Who cites it
20 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Exploring the impact of artificial intelligence on radiation dose reduction in urological imaging: a systematic review from EAU endourology.World journal of urology · 2026Pooled it
- Deep-learning CT reconstruction in clinical scans of the abdomen: a systematic review and meta-analysis.Abdominal radiology (New York) · 2023Pooled it
- Optimization of hypovascular liver lesion detectability in dual-energy CT using deep learning image reconstruction: a phantom study for potential iodine dose reduction.European radiology experimental · 2026Article
- The impact of a novel deep learning reconstruction algorithm on image quality in ultralow-dose CT: a quantitative phantom study.European radiology experimental · 2026Article
- Artificial intelligence iterative imaging reconstruction with low-dose CT scans for hepatic metastases.Scientific reports · 2026Article
- Double Boosting Strategy for Low-Iodine-Dose Dual-Source DECT Follow-Up CT After Intervention with Raw DICOM-Level Deep Learning Iodine Boosting and Low-keV Dual-Energy-Derived Images.Tomography (Ann Arbor, Mich.) · 2026Article
- Two Deep Image Reconstructions for a 320-Row CT: Review of Clinical ApplicationsCurrent medical imaging · 2026Review
- Contrast medium dose optimization in the era of multi-energy CT.Japanese journal of radiology · 2025Review
- Article
- Deep learning reconstruction enhances tophus detection in a dual-energy CT phantom study.Scientific reports · 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
- Contrast Volume Reduction in Oncologic Body Imaging Using Dual-Energy CT: A Comparison with Single-Energy CT.Diagnostics (Basel, Switzerland) · 2025Article
- Systematic Review on Learning-based Spectral CT.ArXiv · 2024Article
- A paradigm shift in oncology imaging: a prospective cross-sectional study to assess low-dose deep learning image reconstruction versus standard-dose iterative reconstruction for comprehensive lesion detection in dual-energy computed tomography.Quantitative imaging in medicine and surgery · 2024Article
- Deep learning image reconstruction generates thinner slice iodine maps with improved image quality to increase diagnostic acceptance and lesion conspicuity: a prospective study on abdominal dual-energy CT.BMC medical imaging · 2024Article
- Systematic Review on Learning-based Spectral CT.IEEE transactions on radiation and plasma medical sciences · 2024Article
- A Deep Learning Image Reconstruction Algorithm for Improving Image Quality and Hepatic Lesion Detectability in Abdominal Dual-Energy Computed Tomography: Preliminary Results.Journal of digital imaging · 2023Article
- Evaluation of Image Quality and Detectability of Deep Learning Image Reconstruction (DLIR) Algorithm in Single- and Dual-energy CT.Journal of digital imaging · 2023Article
- Improving lesion conspicuity in abdominal dual-energy CT with deep learning image reconstruction: a prospective study with five readers.European radiology · 2023Article
- Deep learning image reconstruction algorithm for carotid dual-energy computed tomography angiography: evaluation of image quality and diagnostic performance.Insights into imaging · 2022Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo evaluate the feasibility of a simultaneous reduction of radiation and iodine doses in dual-energy thoraco-abdomino-pelvic CT reconstructed with deep learning image reconstruction (DLIR).
methodsThoraco-abdomino-pelvic CT was prospectively performed in 111 participants; 52 participants underwent a standard-dose single-energy CT with a standard iodine dose (600 mgI/kg; SD group), while 59 underwent a low-dose dual-energy CT with a reduced iodine dose [300 mgI/kg; double low-dose (DLD) group]. CT data were reconstructed with a hybrid iterative reconstruction in the SD group and a high-strength level of DLIR at 40 keV in the DLD group. Two radiologists measured the CT numbers of the descending and abdominal aorta, portal vein, hepatic vein, inferior vena cava, liver, pancreas, spleen, and kidney, and background noise. Two other radiologists assessed diagnostic acceptability using a 5-point scale. The CT dose-index volume (CTDI
resultsThe median CTDI
conclusionVirtual monochromatic images at 40 keV reconstructed with DLIR could achieve half doses of radiation and iodine while maintaining diagnostic image quality. ADVANCES IN KNOWLEDGE: Virtual monochromatic images at 40 keV reconstructed with DLIR algorithm allowed to reduce the doses of radiation and iodine while maintaining diagnostic image quality.
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