European Journal of Radiology Open (Jan 2020)
Iterative reconstruction algorithm improves the image quality without affecting quantitative measurements of computed tomography perfusion in the upper abdomen
Abstract
Objective: To investigate differences between reconstruction algorithms in quantitative perfusion values and time-attenuation curves in computed tomography perfusion (CTP) examinations of the upper abdomen. Methods: Twenty-six CTP examinations were reconstructed with filtered back projection and an iterative reconstruction algorithm, advanced modeled iterative reconstruction (ADMIRE), with different levels of noise-reduction strength. Using the maximum-slope model, quantitative measurements were obtained: blood flow (mL/min/100 mL), blood volume (mL/100 mL), time to peak (s), arterial liver perfusion (mL/100 mL/min), portal venous liver perfusion (mL/100 mL/min), hepatic perfusion index (%), temporal maximum intensity projection (Hounsfield units (HU)) and temporal average HU. Time-attenuation curves for seven sites (left liver lobe, right liver lobe, hepatocellular carcinoma, spleen, gastric wall, pancreas, portal vein) were obtained. Mixed-model analysis was used for statistical evaluation. Image noise and the signal:noise ratio (SNR) were compared between four reconstructions, and statistical analysis of these reconstructions was made with a related-samples Friedman’s two-way analysis of variance by ranks test. Results: There were no significant differences for quantitative measurements between the four reconstructions for all tissues. There were no significant differences between the AUC values of the time-attenuation curves between the four reconstructions for all tissues, including three automatic measurements (portal vein, aorta, spleen). There was a significant difference in image noise and SNR between the four reconstructions. Conclusions: ADMIRE did not affect the quantitative measurements or time-attenuation curves of tissues in the upper abdomen. The image noise was lower, and the SNR higher, for iterative reconstructions with higher noise-reduction strengths.