Comparison of image quality between filtered back-projection and the adaptive statistical and novel model-based iterative reconstruction techniques in abdominal CT for renal calculi

OBJECTIVES: To compare image quality on computed tomographic (CT) images acquired with filtered back-projection (FBP), adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) techniques in CT kidney/ureter/bladder (KUB) examination. METHODS: Eighteen patients underwent standard protocol CT KUB at our institution. The same raw data were reconstructed using FBP, ASIR and MBIR. Objective [mean image noise, contrast-to-noise ratio (CNR) for kidney and mean attenuation values of subcutaneous fat] and subjective image parameters (image noise, image contrast, overall visibility of kidneys/ureters/bladder, visibility of small structures, and overall diagnostic confidence) were assessed using a scoring system from 1 (best) to 5 (worst). RESULTS: Objective image measurements revealed significantly less image noise and higher CNR and the same fat attenuation values for the MBIR technique (P < 0.05). MBIR scored best in all the subjective image parameters (P < 0.001) with averages ranging between 2.05–2.73 for MBIR, 2.95–3.10 for ASIR and 3.08–3.31 for FBP. No significant difference was observed between FBP and ASIR (P > 0.05), while there was a significant difference between ASIR vs. MBIR (P < 0.05). The mean effective dose was 3 mSv. CONCLUSION: MBIR shows superior reduction in noise and improved image quality (both objective and subjective analysis) compared with ASIR and FBP CT KUB examinations. MAIN MESSAGES: • There are many reconstruction options in CT. • Novel model-based iterative reconstruction (MBIR) showed the least noise and optimal image quality. • For CT of the kidneys/ureters/bladder, MBIR should be utilised, if available. • Further studies to reduce the dose while maintaining image quality should be pursued.