Iterative reconstruction algorithm improves the image quality without affecting quantitative measurements of computed tomography perfusion in the upper abdomen

Mischa Woisetschläger; Lilian Henriksson; Wolf Bartholomae; Thomas Gasslander; Bergthor Björnsson; Per Sandström

doi:10.1016/j.ejro.2020.100243

Iterative reconstruction algorithm improves the image quality without affecting quantitative measurements of computed tomography perfusion in the upper abdomen

Eur J Radiol Open. 2020 Jul 3:7:100243. doi: 10.1016/j.ejro.2020.100243. eCollection 2020.

Authors

Mischa Woisetschläger^{1

2}, Lilian Henriksson^{1

2}, Wolf Bartholomae^{1

2}, Thomas Gasslander³, Bergthor Björnsson³, Per Sandström³

Affiliations

¹ Department of Radiology in Linköping, and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.
² Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
³ Department of Surgery in Linköping, and Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden.

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.

Keywords: 4D computed tomography; ADMIRE, advanced modelled iterative reconstruction; ALP, arterial liver perfusion; AUC, area under the curve; Abdomen; BF, blood flow; BMI, body mass index; BV, blood volume; CTP, computed tomography perfusion; FBP, filtered back projection; GFR, glomerular filtration rate; HCC, hepatocellular carcinoma; HPI, hepatic perfusion index; Image reconstruction; LI-RADS-5, liver imaging reporting and data system; Liver; PVP, portal venous liver perfusion; Perfusion; Radiation dosage; SNR, signal to noise ratio; TAC, time attenuation curve; TACE, transarterial chemoembolization; TTP, time to peak.