Literature DB >> 17326085

Reexamining the quantification of perfusion MRI data in the presence of bolus dispersion.

Linda Ko1, Marina Salluzzi, Richard Frayne, Michael Smith.   

Abstract

PURPOSE: To determine the true impact of dispersion upon cerebral blood flow (CBF) quantification by removing an algorithm implementation-induced systematic error.
MATERIALS AND METHODS: The impact of dispersion on the arterial input function (AIF) between measurement and entry into the tissue of interest on CBF estimates was simulated assuming: 1) contralateral circulation flow that introduces a true arterial tissue delay (ATD)-related dispersive component; and 2) the presence of an arterial stenosis that disperses and shifts the AIF peak entering the tissue; increasing the apparent ATD relative to the original AIF.
RESULTS: Previously reported CBF estimates for the stenosis dispersion model were found to be a mixture of true dispersive effects and an algorithm implementation-induced systematic error. The true CBF(MEASURED)/CBF(NO-DISPERSION) ratios for short mean transit times (MTT) (normal) and long MTT (infarcted) tissue were similar for both dispersion models evaluated; this was an unanticipated result. The CBF quantification inaccuracies induced through the dispersion model truly related to ATD were lower than for the local stenosis-based dispersion for small ATD values.
CONCLUSION: Correcting the systematic error present in a previous deconvolution study removes the reported ATD-related impact on CBF quantification. The impact of dispersion was smaller than half that reported in previous simulation studies.

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Year:  2007        PMID: 17326085     DOI: 10.1002/jmri.20781

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


  6 in total

1.  Correction for arterial-tissue delay and dispersion in absolute quantitative cerebral perfusion DSC MR imaging.

Authors:  Jessy J Mouannes-Srour; Wanyong Shin; Sameer A Ansari; Michael C Hurley; Parmede Vakil; Bernard R Bendok; John L Lee; Colin P Derdeyn; Timothy J Carroll
Journal:  Magn Reson Med       Date:  2011-12-12       Impact factor: 4.668

2.  Long-term impact of perfusion CT data after subarachnoid hemorrhage.

Authors:  Christian Mathys; Daniel Martens; Dorothea C Reichelt; Julian Caspers; Joel Aissa; Rebecca May; Daniel Hänggi; Gerald Antoch; Bernd Turowski
Journal:  Neuroradiology       Date:  2013-09-13       Impact factor: 2.804

Review 3.  Absolute quantification of perfusion using dynamic susceptibility contrast MRI: pitfalls and possibilities.

Authors:  Linda Knutsson; Freddy Ståhlberg; Ronnie Wirestam
Journal:  MAGMA       Date:  2009-12-04       Impact factor: 2.310

4.  A model-constrained Monte Carlo method for blind arterial input function estimation in dynamic contrast-enhanced MRI: II. In vivo results.

Authors:  Matthias C Schabel; Edward V R DiBella; Randy L Jensen; Karen L Salzman
Journal:  Phys Med Biol       Date:  2010-08-03       Impact factor: 3.609

5.  A model-constrained Monte Carlo method for blind arterial input function estimation in dynamic contrast-enhanced MRI: I. Simulations.

Authors:  Matthias C Schabel; Jacob U Fluckiger; Edward V R DiBella
Journal:  Phys Med Biol       Date:  2010-08-03       Impact factor: 3.609

6.  Microvascular perfusion based on arterial spin labeled perfusion MRI as a measure of vascular risk in Alzheimer's disease.

Authors:  Quan Zhang; Randall B Stafford; Ze Wang; Steven E Arnold; David A Wolk; John A Detre
Journal:  J Alzheimers Dis       Date:  2012       Impact factor: 4.472

  6 in total

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