ArticleEuropean radiology2017
Impact of model-based iterative reconstruction on low-contrast lesion detection and image quality in abdominal CT: a 12-reader-based comparative phantom study with filtered back projection at different tube voltages.
Article in European radiology, 2017. 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 21 papers.
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Who cites it
21 citing papers in PubMed.
- Multi-Energy Low-Kiloelectron Volt versus Single-Energy Low-Kilovolt Images for Endoleak Detection at CT Angiography of the Aorta.Radiology. Cardiothoracic imaging · 2024Trial
- Detection of hypodense hepatic and renal lesions on abdominal CT reconstructed with deep learning image reconstruction technique in patients with large body habitus: A multi-reader study.Abdominal radiology (New York) · 2026Article
- Image quality, diagnostic performance of reduced-dose abdominal CT with artificial intelligence model-based iterative reconstruction for colorectal liver metastasis: a prospective cohort study.Quantitative imaging in medicine and surgery · 2025Article
- Ultra-low dose dual-layer detector spectral CT for pulmonary nodule screening: image quality and diagnostic performance.Insights into imaging · 2025Article
- Improved vascular depiction and image quality through deep learning reconstruction of CT hepatic arteriography during transcatheter arterial chemoembolization.Japanese journal of radiology · 2024Article
- Detectability of Hypoattenuating Liver Lesions with Deep Learning CT Reconstruction: A Phantom and Patient Study.Radiology · 2024Article
- Article
- Can 1.25 mm thin-section images generated with Deep Learning Image Reconstruction technique replace standard-of-care 5 mm images in abdominal CT?Abdominal radiology (New York) · 2023Article
- Can deep learning improve image quality of low-dose CT: a prospective study in interstitial lung disease.European radiology · 2022Article
- Iterative reconstruction with multifrequency signal recognition technology to improve low-contrast detectability: A phantom study.Acta radiologica open · 2022Article
- Comparison of low-contrast detectability between uniform and anatomically realistic phantoms-influences on CT image quality assessment.European radiology · 2022Article
- IMAGE QUALITY AND POTENTIAL DOSE REDUCTION USING ADVANCED MODELED ITERATIVE RECONSTRUCTION (ADMIRE) IN ABDOMINAL CT - A REVIEW.Radiation protection dosimetry · 2021Review
- Image quality improvement with deep learning-based reconstruction on abdominal ultrahigh-resolution CT: A phantom study.Journal of applied clinical medical physics · 2021Article
- Diagnostic value of deep learning reconstruction for radiation dose reduction at abdominal ultra-high-resolution CT.European radiology · 2021Article
- Deep Learning-based CT Image Reconstruction: Initial Evaluation Targeting Hypovascular Hepatic Metastases.Radiology. Artificial intelligence · 2019Article
- Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT.European radiology · 2019Article
- Full model-based iterative reconstruction (MBIR) in abdominal CT increases objective image quality, but decreases subjective acceptance.European radiology · 2019Article
- Can Realistic Liver Tissue Surrogates Accurately Quantify the Impact of Reduced-kV Imaging on Attenuation and Contrast of Parenchyma and Lesions?Academic radiology · 2019Article
- Prospective evaluation of ultra-low-dose contrast-enhanced 100-kV abdominal computed tomography with tin filter: effect on radiation dose reduction and image quality with a third-generation dual-source CT system.European radiology · 2019Article
- Estimating detectability indexJournal of medical imaging (Bellingham, Wash.) · 2018Article
Corrections and comments
- Erratum issued
Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo evaluate the impact of model-based iterative reconstruction (MBIR) on image quality and low-contrast lesion detection compared with filtered back projection (FBP) in abdominal computed tomography (CT) of simulated medium and large patients at different tube voltages.
methodsA phantom with 45 hypoattenuating lesions was placed in two water containers and scanned at 70, 80, 100, and 120 kVp. The 120-kVp protocol served as reference, and the volume CT dose index (CTDI
resultsMBIR decreased the image noise by 24% and 27%, and increased the CNR by 30% and 29% for the medium and large phantoms, respectively. Lower tube voltages increased the CNR by 58%, 46%, and 16% at 70, 80, and 100 kVp, respectively, compared with 120 kVp in the medium phantom and by 9%, 18% and 12% in the large phantom. No significant difference in lesion detection rate was observed (medium: 79-82%; large: 57-65%; P > 0.37).
conclusionsAlthough MBIR improved quantitative image quality compared with FBP, it did not result in increased low-contrast lesion detection in abdominal CT at different tube voltages in simulated medium and large patients. KEY POINTS: • MBIR improved quantitative image quality but not lesion detection compared with FBP. • Increased CNR by low tube voltages did not improve lesion detection. • Changes in image noise and CNR do not directly influence diagnostic accuracy.
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