Literature DB >> 16261569

Bolus dispersion issues related to the quantification of perfusion MRI data.

Fernando Calamante1.   

Abstract

Quantification of cerebral blood flow (CBF) using dynamic-susceptibility contrast (DSC) MRI relies on the deconvolution of the arterial input function (AIF). The AIF is commonly measured in a major artery (e.g., the middle cerebral artery), and the estimated function is used as a global AIF for the whole slice. However, the presence of bolus delay and dispersion between the artery and the tissue of interest can introduce significant errors in CBF quantification. While several methods have been introduced to minimize or eliminate the effects of bolus delay, the correction of bolus dispersion is more difficult to address because it requires a model for the vascular bed. This article summarizes how this dispersion effect can be incorporated into the model for CBF quantification, and discusses the magnitude of the errors introduced. Furthermore, alternative methods for correcting or minimizing the effects of bolus dispersion in the quantification of CBF are reviewed.

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Mesh:

Year:  2005        PMID: 16261569     DOI: 10.1002/jmri.20454

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


  23 in total

1.  SCALE-PWI: A pulse sequence for absolute quantitative cerebral perfusion imaging.

Authors:  Jessy Mouannes Srour; Wanyong Shin; Saurabh Shah; Anindya Sen; Timothy J Carroll
Journal:  J Cereb Blood Flow Metab       Date:  2010-12-15       Impact factor: 6.200

2.  Early time points perfusion imaging: theoretical analysis of correction factors for relative cerebral blood flow estimation given local arterial input function.

Authors:  Kenneth K Kwong; David A Chesler
Journal:  Neuroimage       Date:  2011-04-08       Impact factor: 6.556

3.  A fully automated method for quantitative cerebral hemodynamic analysis using DSC-MRI.

Authors:  Atle Bjørnerud; Kyrre E Emblem
Journal:  J Cereb Blood Flow Metab       Date:  2010-01-20       Impact factor: 6.200

4.  Use of dynamic susceptibility-contrast MRI (DSC-MRI) to assess perfusion changes in the ipsilateral brain parenchyma from glioblastoma.

Authors:  Stephan Ulmer; Carsten Liess; Santosh Kesari; Nadine Otto; Torsten Straube; Olav Jansen
Journal:  J Neurooncol       Date:  2008-09-21       Impact factor: 4.130

Review 5.  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

6.  Treatment assessment of radiotherapy using MR functional quantitative imaging.

Authors:  Zheng Chang; Chunhao Wang
Journal:  World J Radiol       Date:  2015-01-28

7.  Impact of the arterial input function on microvascularization parameter measurements using dynamic contrast-enhanced ultrasonography.

Authors:  Marianne Gauthier; Stéphanie Pitre-Champagnat; Farid Tabarout; Ingrid Leguerney; Mélanie Polrot; Nathalie Lassau
Journal:  World J Radiol       Date:  2012-07-28

8.  Emerging techniques and technologies in brain tumor imaging.

Authors:  Benjamin M Ellingson; Martin Bendszus; A Gregory Sorensen; Whitney B Pope
Journal:  Neuro Oncol       Date:  2014-10       Impact factor: 12.300

9.  Arterial input function in a dedicated slice for cerebral perfusion measurements in humans.

Authors:  Elias Kellner; Irina Mader; Marco Reisert; Horst Urbach; Valerij Gennadevic Kiselev
Journal:  MAGMA       Date:  2017-12-09       Impact factor: 2.310

10.  Comparison of Blood Oxygenation Level-Dependent fMRI and Provocative DSC Perfusion MR Imaging for Monitoring Cerebrovascular Reserve in Intracranial Chronic Cerebrovascular Disease.

Authors:  K R Thulborn; I C Atkinson; A Alexander; M Singal; S Amin-Hanjani; X Du; A Alaraj; F T Charbel
Journal:  AJNR Am J Neuroradiol       Date:  2018-01-25       Impact factor: 3.825

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