OBJECTIVE: To investigate the effect of reconstruction slice thickness on image quality at CT virtual cystoscopy (VC). METHODS: Pelvic CT examinations in bladder cancer patients were reconstructed at different slice thicknesses (0.6-5 mm) and intervals, and resulting VC images assessed. Quality indicators were ridging, holes, floaters and dimpling artefacts, tumour definition, and an overall score, ranked 1 (best) to 7 (worst). CT number and standard deviation (SD) for bladder contents and bladder wall were recorded. The mean SD was used as a measure of noise, and the contrast-to-noise ratio (CNR) was calculated as the CT number difference between them divided by the average image noise. The mean CNR across the three levels was used for analysis. Each qualitative image quality measure was compared with CT number, noise and CNR measurements. RESULTS: Dimpling artefacts increased with thinner slice reconstruction and correlated with increased noise, often resulting in poor tumour definition. The best overall image quality score was seen for VC images reconstructed at 1.2 mm slice thickness, probably because of the competing effects of spatial resolution and CNR. CONCLUSION: A slice thickness reconstruction <1.2 mm does not provide for better image quality at VC owing to the presence of increased noise.
OBJECTIVE: To investigate the effect of reconstruction slice thickness on image quality at CT virtual cystoscopy (VC). METHODS: Pelvic CT examinations in bladder cancer patients were reconstructed at different slice thicknesses (0.6-5 mm) and intervals, and resulting VC images assessed. Quality indicators were ridging, holes, floaters and dimpling artefacts, tumour definition, and an overall score, ranked 1 (best) to 7 (worst). CT number and standard deviation (SD) for bladder contents and bladder wall were recorded. The mean SD was used as a measure of noise, and the contrast-to-noise ratio (CNR) was calculated as the CT number difference between them divided by the average image noise. The mean CNR across the three levels was used for analysis. Each qualitative image quality measure was compared with CT number, noise and CNR measurements. RESULTS: Dimpling artefacts increased with thinner slice reconstruction and correlated with increased noise, often resulting in poor tumour definition. The best overall image quality score was seen for VC images reconstructed at 1.2 mm slice thickness, probably because of the competing effects of spatial resolution and CNR. CONCLUSION: A slice thickness reconstruction <1.2 mm does not provide for better image quality at VC owing to the presence of increased noise.
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