Literature DB >> 24631714

Renal perfusion in acute kidney injury with DCE-MRI: deconvolution analysis versus two-compartment filtration model.

Frank G Zöllner1, Fabian Zimmer2, Sarah Klotz3, Simone Hoeger3, Lothar R Schad2.   

Abstract

PURPOSE: To investigate the results of different pharmacokinetic models of a quantitative analysis of renal blood flow (RBF) in acute kidney injury using deconvolution analysis and a two-compartment renal filtration model.
MATERIALS AND METHODS: MRI data of ten male Lewis rats were analyzed retrospectively. Six animals were subjected to unilateral acute kidney injury and underwent perfusion imaging by dynamic contrast-enhanced MRI (DCE-MRI). Renal blood flow was estimated from regions-of-interest depicting the cortex in the DCE-MRI perfusion maps. The perfusion models were compared by a paired t-test and Bland-Altman plots.
RESULTS: No significant difference was found between the two compartment model and the deconvolution analysis (P=0.2807). Differences between healthy and diseased kidney in the AKI model were significant for both methods (P<0.05). A Bland-Altman plot showed no systematic errors, and values were equally distributed around the mean difference between the methods lying within the range of 1.96 standard deviations.
CONCLUSION: Both quantification strategies could detect the kidneys that were impaired by AKI. When just aiming at RBF as a marker, a deconvolution analysis can provide similar values as the 2CFM. If functional parameters beyond RBF like glomerular filtration rate are needed, the 2CFM should be employed.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Acute kidney injury; Comparison; DCE-MRI; Quantification; Renal blood flow

Mesh:

Year:  2014        PMID: 24631714     DOI: 10.1016/j.mri.2014.02.014

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  8 in total

Review 1.  [Functional magnetic resonance imaging of the kidneys].

Authors:  R S Lanzman; M Notohamiprodjo; H J Wittsack
Journal:  Radiologe       Date:  2015-12       Impact factor: 0.635

2.  Dynamic Contrast Enhanced (DCE) MRI-Derived Renal Perfusion and Filtration: Experimental Protocol.

Authors:  Pietro Irrera; Lorena Consolino; Walter Dastrù; Michael Pedersen; Frank G Zöllner; Dario Livio Longo
Journal:  Methods Mol Biol       Date:  2021

3.  Measurement of murine kidney functional biomarkers using DCE-MRI: A multi-slice TRICKS technique and semi-automated image processing algorithm.

Authors:  Kai Jiang; Hui Tang; Prasanna K Mishra; Slobodan I Macura; Lilach O Lerman
Journal:  Magn Reson Imaging       Date:  2019-08-20       Impact factor: 2.546

4.  Dynamic Contrast Enhancement (DCE) MRI-Derived Renal Perfusion and Filtration: Basic Concepts.

Authors:  Michael Pedersen; Pietro Irrera; Walter Dastrù; Frank G Zöllner; Kevin M Bennett; Scott C Beeman; G Larry Bretthorst; Joel R Garbow; Dario Livio Longo
Journal:  Methods Mol Biol       Date:  2021

5.  Mitochondria-targeted antioxidant MitoQ reduced renal damage caused by ischemia-reperfusion injury in rodent kidneys: Longitudinal observations of T2 -weighted imaging and dynamic contrast-enhanced MRI.

Authors:  Xiaoge Liu; Michael P Murphy; Wei Xing; Huanhuan Wu; Rui Zhang; Haoran Sun
Journal:  Magn Reson Med       Date:  2017-06-12       Impact factor: 4.668

6.  Modified dixon-based renal dynamic contrast-enhanced MRI facilitates automated registration and perfusion analysis.

Authors:  Anneloes de Boer; Tim Leiner; Eva E Vink; Peter J Blankestijn; Cornelis A T van den Berg
Journal:  Magn Reson Med       Date:  2017-11-13       Impact factor: 4.668

7.  Quantifying MRI T1 relaxation in flowing blood: implications for arterial input function measurement in DCE-MRI.

Authors:  Matthew N Gwilliam; David J Collins; Martin O Leach; Matthew R Orton
Journal:  Br J Radiol       Date:  2021-01-28       Impact factor: 3.039

8.  Hyperpolarized [1-13C]-acetate Renal Metabolic Clearance Rate Mapping.

Authors:  Emmeli F R Mikkelsen; Christian Østergaard Mariager; Thomas Nørlinger; Haiyun Qi; Rolf F Schulte; Steen Jakobsen; Jørgen Frøkiær; Michael Pedersen; Hans Stødkilde-Jørgensen; Christoffer Laustsen
Journal:  Sci Rep       Date:  2017-11-22       Impact factor: 4.379

  8 in total

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