ArticleBMC medical imaging2024
Comparison of different iterative reconstruction algorithms with contrast-enhancement boost technique on the image quality of CT pulmonary angiography for obese patients.
Article in BMC medical imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Deep learning reconstruction combined with contrast-enhancement boost in dual-low dose CT pulmonary angiography: a two-center prospective trial.European radiology · 2025Trial
- Impact of contrast enhancement boost and super-resolution deep learning reconstruction on pediatric congenital heart disease CTA scans: ultra-low contrast dose.BMC medical imaging · 2025Article
- Machine Learning-Based Objective Evaluation Model of CTPA Image Quality: A Multi-Center Study.International journal of general medicine · 2025Article
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7 authors.
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Abstract
objectiveTo evaluate the effect of the contrast-enhancement-boost (CE-boost) postprocessing technique on improving the image quality of obese patients in computed tomography pulmonary angiography (CTPA) compared to hybrid iterative reconstruction (HIR) and model-based iterative reconstruction (MBIR) algorithms.
methodsThis prospective study was conducted on 100 patients who underwent CTPA for suspected pulmonary embolism. Non-obese patients with a body mass index (BMI) under 25 were designated as group 1, while obese patients (group 2) had a BMI exceeding 25. The CE-boost images were generated by subtracting non-contrast HIR images from contrast-enhanced HIR images to improve the visibility of pulmonary arteries further. The CT value, image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were quantitatively assessed. Two chest radiologists independently reviewed the CT images (5, best; 1, worst) across three subjective characteristics including diagnostic confidence, subjective image noise, and vascular contrast. The Friedman test and Dunn-Bonferroni correction were used for statistical analysis.
resultsThe CE-boost had significantly higher CT values than HIR and MBIR in both groups (all p < 0.001). The MBIR yielded the lowest image noise compared with HIR and CE-boost (all p < 0.001). The SNR and CNR of main pulmonary artery (MPA) were significantly higher in CE-boost than in MBIR (all p < 0.05), with HIR showing the lowest values (all p < 0.001). Group 2 MBIR received significantly better subjective image noise scores, while the diagnostic confidence and vascular contrast scored highest with the group 2 CE-boost (all p < 0.05).
conclusionCompared to the HIR algorithm, both the CE-boost technique and the MBIR algorithm can improve the image quality of CTPA in obese patients. CE-boost had the greatest potential in increasing the visualization of pulmonary artery and its branches.
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