Hepatic computed tomography perfusion: comparison of maximum slope and dual-input single-compartment methods

Abstract

Purpose. The aim of the study was to compare two analytical methods-maximum slope (MS) and the dualinput single-compartment model (CM)-in computed tomography (CT) measurements of hepatic perfusion and to assess the effects of extrahepatic systemic factors. Materials and methods. A total of 109 patients underwent hepatic CT perfusion. The scans were conducted at the hepatic hilum 7-77 s after administration of contrast material. Hepatic arterial perfusion (HAP) and portal perfusion (HPP) (ml/min/100 ml) and the arterial perfusion fraction (APF, %) were calculated with the two methods, followed by correlation assessment. Partial correlation analysis was used to assess the effects on hepatic perfusion values by various factors, including age, sex, risk of cardiovascular disease, compensation for respiratory misregistration, arrival time of contrast material at the abdominal aorta, transit time from abdominal aorta to hepatic parenchyma, and liver dysfunction. Results. The mean HAPs, HPPs, and APFs were, respectively, 31.4, 104.2, and 23.9 for MS and 27.1, 141.3, and 22.1 for CM. HAP and APF showed signifi cant (P < 0.0001) and moderate correlation (γ = 0.417 and 0.548) and HPP showed poor correlation (γ = 0.172) between the two methods. While MS showed weak correlations (γ = −0.39 to 0.34; P < 0.001 to <0.02) between multiple extrahepatic factors and perfusion values, CM showed weak correlation only between the patients' sex and HAP (γ = 0.31, P = 0.001). Conclusion. Hepatic perfusion values estimated by the two methods are not interchangeable. CM is less susceptible to extrahepatic systemic factors.

Comparison of Quantitatively Analyzed Dynamic Area-Detector CT Using Various Mathematic Methods With FDG PET/CT in Management of Solitary Pulmonary Nodules

“…For the dual-input maximum slope method, which is a modification of the theories presented in previous publications [25][26][27][28] where C n is the concentration of contrast medium within the nodule, C a is the concentration of contrast medium within the main trunk of the pulmonary artery, C s is the concentration of contrast medium within the descending aorta, t is the time after contrast medium injection, and t max is the time at maximized C a or C s . According to articles in the literature [14][15][16][17][18], lung tumors are supplied by both bronchial and pulmonary circulations.…”

“…For the dual-input maximum slope method, which was modified from a model described in the literature [25][26][27][28], total perfusion, pulmonary arterial perfusion, and systemic perfusion were calculated on the basis of bronchial circulation within each nodule and expressed in mL/100 mL/min.…”

Compartment model analysis of intravenous contrast‐enhanced dynamic computed tomography in hepatic hemodynamics: A validation study using intra‐arterial contrast‐enhanced computed tomography

“…Our findings suggest that the upper k 2 limit should be set to between 0.03 and 0.07, because the mean correlation coefficient between the perfusion parameters and IA‐CT contrasts are significantly high in both hepatic arterial and portal venous flow evaluation. Furthermore, our results showed that hepatic arterial and portal venous hemodynamics could be evaluated to some extent using CMA even when using relatively low temporal resolution TCC data obtained from IV‐CT, compared to the findings of previous studies This may imply that the proposed method can be an alternative to an additional dedicated perfusion study, thereby reducing the patient's additional burden and radiation exposure.…”

Anatomically and physiologically informed computational model of hepatic contrast perfusion for virtual imaging trials

“…There is also a need to include the dynamics associated with contrast media; as such media are widely used in CT imaging 10,11 aiming to discern anatomy and physiology processes 12,13 . Inter‐organ contrast concentration as a function of time has also been previously simulated for the XCAT population 14 using single and multi‐compartment models 15–19 . These models are useful in determining the total quantity of contrast in an organ as a function of time.…”

“…12,13 Inter-organ contrast concentration as a function of time has also been previously simulated for the XCAT population 14 using single and multi-compartment models. [15][16][17][18][19] These models are useful in determining the total quantity of contrast in an organ as a function of time. However, they do not provide spatiotemporal distribution of contrast within the organ.…”