A quantitative method for estimating hepatic blood flow using a dual-input single-compartment model

S. Miyazaki, K. Murase, T. Yoshikawa, S. Morimoto, Y. Ohno, K. Sugimura

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)

Abstract

The purpose of this study was to investigate the accuracy of a quantitative method for estimating arterial hepatic blood flow and portal hepatic blood flow separately using a dual-input single-compartment model compared with the maximum slope method using computer simulations and clinical data. In computer simulations, the rate constants for the transfer of contrast agent (CA) from the hepatic artery to the liver (K1a), from the portal vein to the liver (K1p) and from the liver to the blood (k2) were estimated from simulated time-density curves with various transit times of CA from the aorta to the liver (τa) and from the portal vein to the liver (τp) using the linear leastsquares (LLSQ) method. In clinical studies, dynamic CT data were acquired from 27 patients, and parametric maps of K1a, K1p and K2 were generated by applying the LLSQ method pixel by pixel. In simulation studies, τa and τp were found to have a large and a small effect on the estimates of K1a and K1p, respectively. In clinical studies, the K1a and K1p values estimated with the maximum slope method were underestimated by 60 ± 29% and 37 ± 12%, respectively, compared with those estimated by the LLSQ method. In conclusion, our results suggest that correction of τa is necessary for accurately estimating K1a and K1p. Our method is therefore promising forthe evaluation of hepatic blood flow in various liver diseases because it allows us to evaluate arterial hepatic blood flow and portal hepatic blood flow separately and visually.

Original languageEnglish
Pages (from-to)790-800
Number of pages11
JournalBritish Journal of Radiology
Volume81
Issue number970
DOIs
Publication statusPublished - 10-2008
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging

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