Literature DB >> 24395144

Quantitative hepatic perfusion modeling using DCE-MRI with sequential breathholds.

Eric M Bultman1, Ethan K Brodsky, Debra E Horng, Pablo Irarrazaval, William R Schelman, Walter F Block, Scott B Reeder.   

Abstract

PURPOSE: To develop and demonstrate the feasibility of a new formulation for quantitative perfusion modeling in the liver using interrupted DCE-MRI data acquired during multiple sequential breathholds.
MATERIALS AND METHODS: A new mathematical formulation to estimate quantitative perfusion parameters using interrupted data was developed. Using this method, we investigated whether a second degree-of-freedom in the tissue residue function (TRF) improves quality-of-fit criteria when applied to a dual-input single-compartment perfusion model. We subsequently estimated hepatic perfusion parameters using DCE-MRI data from 12 healthy volunteers and 9 cirrhotic patients with a history of hepatocellular carcinoma (HCC); and examined the utility of these estimates in differentiating between healthy liver, cirrhotic liver, and HCC.
RESULTS: Quality-of-fit criteria in all groups were improved using a Weibull TRF (2 degrees-of-freedom) versus an exponential TRF (1 degree-of-freedom), indicating nearer concordance of source DCE-MRI data with the Weibull model. Using the Weibull TRF, arterial fraction was greater in cirrhotic versus normal liver (39 ± 23% versus 15 ± 14%, P = 0.07). Mean transit time (20.6 ± 4.1 s versus 9.8 ± 3.5 s, P = 0.01) and arterial fraction (39 ± 23% versus 73 ± 14%, P = 0.04) were both significantly different between cirrhotic liver and HCC, while differences in total perfusion approached significance.
CONCLUSION: This work demonstrates the feasibility of estimating hepatic perfusion parameters using interrupted data acquired during sequential breathholds.
Copyright © 2013 Wiley Periodicals, Inc.

Entities:  

Keywords:  DCE-MRI; hepatic perfusion modeling; hepatocellular carcinoma; quantitative perfusion MRI; tumor perfusion modeling

Mesh:

Year:  2013        PMID: 24395144      PMCID: PMC3962525          DOI: 10.1002/jmri.24238

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


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