ArticleLa Radiologia medica2019
Improving image quality with model-based iterative reconstruction algorithm for chest CT in children with reduced contrast concentration.
Article in La Radiologia medica, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Thoracic CT Angiographies in Children Using Automated Power Injection with Bolus Tracking Versus Manual Contrast Injection: Analysis of Contrast Enhancement, Image Quality and Radiation Exposure.Diagnostics (Basel, Switzerland) · 2025Article
- Radiomics as a New Frontier of Imaging for Cancer Prognosis: A Narrative Review.Diagnostics (Basel, Switzerland) · 2021Review
- Performance evaluation of a deep learning image reconstruction (DLIR) algorithm in "double low" chest CTA in children: a feasibility study.La Radiologia medica · 2021Article
- Radiomics in the Setting of Neoadjuvant Radiotherapy: A New Approach for Tailored Treatment.Cancers · 2021Review
- Lean body weight versus total body weight to calculate the iodinated contrast media volume in abdominal CT: a randomised controlled trial.Insights into imaging · 2020Article
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
Abstract
objectiveTo evaluate model-based iterative reconstruction (MBIR) in improving the image quality of chest CT in children with reduced concentration contrast medium (CM).
methodsFifty-six children (median age of 4 years) who received low-dose enhanced chest CT were enrolled as the study group and compared with the control group of 56 children. Both groups used the automatic tube current modulation to achieve age-based noise index values of 11-15 HU. The study group used 100 kVp and reduced CM concentration of 270 mgI/ml, and the images in this group were reconstructed with 50% adaptive statistical iterative reconstruction (ASIR) and MBIR. The control group used 120 kV and standard CM of 320 mgI/ml, and the images in this group were reconstructed with ASIR only. Subjective image quality and objective image quality of the three image sets were evaluated. The subjective quality included overall image noise, enhancement degree, lesion (including mediastinum mass, pulmonary space-occupying lesions, and parenchymal infiltrative lesions) conspicuity, and beam-hardening artifacts. The objective quality included the measurement of noise in the left ventricle and back muscle to calculate signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of ventricle.
resultsThere was no difference in radiation dose between the study (CTDIvol of 1.79 ± 1.45 mGy) and control (1.68 ± 0.92 mGy) groups (p = 0.65). However, the study group used 19.7% lower CM dose than the control group (5.84 ± 2.69 vs. 7.27 ± 3.80 gI), and the enhancement in all images met the diagnostic requirements. MBIR reduced image noise by 58.6% and increased SNR and CNR by 143.6% and 165.7%, respectively, compared to ASIR images in the control group. The two ASIR image sets had similar image quality.
conclusionMBIR improved the image quality of low-radiation-dose chest CT in children at 19.3% reduced CM dose.
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