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Application of low-dose CT combined with model-based iterative reconstruction algorithm in oncologic patients during follow-up: dose reduction and image quality

Davide Ippolito, Cesare Maino, Anna Pecorelli, Ilaria Salemi, Davide Gandola, Luca Riva, Cammillo Talei Franzesi, Sandro Sironi

2021British Journal of Radiology15 citationsDOIOpen Access PDF

Abstract

Objectives: To compare image quality and radiation dose of CT images reconstructed with model-based iterative reconstruction (MBIR) and hybrid-iterative (HIR) algorithm in oncologic patients. Methods: 125 oncologic patients underwent both contrast-enhanced low- (100 kV), and standard (120 kV) dose CT, were enrolled. Image quality was assessed by using a 4-point Likert scale. CT attenuation values, expressed in Hounsfield unit (HU), were recorded within a regions of interest (ROI) of liver, spleen, paraspinal muscle, aortic lumen, and subcutaneous fat tissue. Image noise, expressed as standard deviation (SD), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were calculated. Radiation dose were analyzed. Paired Student’s t-test was used to compare all continuous variables. Results: The overall median score assessed as image quality for CT images with the MBIR algorithm was significantly higher in comparison with HIR [4 (range 3–4) vs 3 (3-4), p = 0.017]. CT attenuation values and SD were significantly higher and lower, respectively, in all anatomic districts in images reconstructed with MBIR in comparison with HIR ones (all p < 0.001). SNR and CNR values were higher in CT images reconstructed with MBIR, reaching a significant difference in all districts (all p < 0.001). Radiation dose were significantly lower in the MBIR group compared with the HIR group (p < 0.001). Conclusions: MBIR combined with low-kV setting allows an important dose reduction in whole-body CT imaging, reaching a better image quality both qualitatively and quantitatively. Advances in knowledge: MBIR with low-dose approach allows a reduction of dose exposure, maintaining high image quality, especially in patients which deserve a longlasting follow-up.

Topics & Concepts

Reduction (mathematics)Image qualityAlgorithmIterative reconstructionMedicineNuclear medicineComputed tomographyComputer scienceRadiologyMathematicsImage (mathematics)Artificial intelligenceGeometryRadiation Dose and ImagingAdvanced X-ray and CT ImagingMedical Imaging Techniques and Applications
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