Literature DB >> 12541232

Can dynamic susceptibility contrast magnetic resonance imaging perfusion data be analyzed using a model based on directional flow?

N A Thacker1, M L J Scott, A Jackson.   

Abstract

PURPOSE: To examine the implications of a physiological model of cerebral blood that uses the contradictory assumption that blood flow in all voxels of DSCE-MRI data sets is directional in nature. Analysis of dynamic susceptibility contrast-enhanced magnetic resonance imaging (DSCE-MRI) uses techniques based on indicator dilution theory. Underlying this approach is an assumption that blood flow through pixels of gray and white matter is entirely random in direction.
MATERIALS AND METHODS: We have used a directional flow model to estimate theoretical blood flow velocities that would be observed through normal cerebral tissues. Estimates of flow velocities from individual pixels were made by measuring the mean transit time for net flow (nMTT). Measurements of nMTT were made for each voxel by estimating the mean difference in contrast arrival time between each of the adjacent six voxels.
RESULTS: Examination of the spatial distribution of contrast arrival time from DSCE-MRI data sets in normal volunteers demonstrated clear evidence of directional flow both in large vessels and in gray and white matter. The mean velocities of blood flow in gray and white matter in 12 normal volunteers were 0.25 +/- 0.013 and 0.21 +/- 0.014 cm/second, respectively, compared to predicted values of 0.25 and 0.18 cm/second. These values give measured nMTT for a 1-mm isotropic voxel of gray and white matter of 0.45 +/- 0.12 and 0.52 +/- 0.11 seconds, respectively, compared to predicted values of 0.47 and 0.55 seconds.
CONCLUSION: A directional model of blood flow provides an alternative approach to the calculation of cerebral blood flow from (CBF) DSCE-MRI data. Copyright 2003 Wiley-Liss, Inc.

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Year:  2003        PMID: 12541232     DOI: 10.1002/jmri.10240

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


  4 in total

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2.  Assessment of Blood-Brain Barrier Permeability by Dynamic Contrast-Enhanced MRI in Transient Middle Cerebral Artery Occlusion Model after Localized Brain Cooling in Rats.

Authors:  Eun Soo Kim; Seung-Koo Lee; Mi Jung Kwon; Phil Hye Lee; Young-Su Ju; Dae Young Yoon; Hye Jeong Kim; Kwan Seop Lee
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3.  Magnetic resonance perfusion imaging in neuro-oncology.

Authors:  Alan Jackson; James O'Connor; Gerard Thompson; Samantha Mills
Journal:  Cancer Imaging       Date:  2008-10-13       Impact factor: 3.909

4.  Automated Determination of Arterial Input Function for Dynamic Susceptibility Contrast MRI from Regions around Arteries Using Independent Component Analysis.

Authors:  Sharon Chen; Yu-Chang Tyan; Jui-Jen Lai; Chin-Ching Chang
Journal:  Radiol Res Pract       Date:  2016-07-28
  4 in total

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