Literature DB >> 20373392

Validation of quantitative estimation of tissue oxygen extraction fraction and deoxygenated blood volume fraction in phantom and in vivo experiments by using MRI.

Jan Sedlacik1, Jürgen R Reichenbach.   

Abstract

The blood oxygenation level dependent signal of cerebral tissue can be theoretically derived using a network model formed by randomly oriented infinitely long cylinders. The validation of this model by phantom and in vivo experiments is still an object of research. A network phantom was constructed of solid polypropylene strings immersed in silicone oil, which essentially eliminated the effect of spin diffusion. The volume fraction and magnetic property of the string network was predetermined by independent methods. Ten healthy volunteers were measured for in vivo demonstration. The gradient echo sampled spin echo signal was evaluated with the cylinder network model. We found a strong interdependency between the two network characterizing parameters deoxygenated blood volume and oxygen extraction fraction. Here, different sets of deoxygenated blood volume/oxygen extraction fraction values were able to describe the measured signal equally well. However, by setting one parameter constant to a predetermined value, reasonable estimates of the other parameter were obtained. The same behavior was found for the in vivo demonstration. The signal theory of the cylinder network was validated by a well-characterized phantom. However, the found interdependency that was found between deoxygenated blood volume and oxygen extraction fraction requires an independent estimation of one variable to determine reliable values of the other parameter.

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Year:  2010        PMID: 20373392     DOI: 10.1002/mrm.22274

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  18 in total

1.  Is T2* enough to assess oxygenation? Quantitative blood oxygen level-dependent analysis in brain tumor.

Authors:  Thomas Christen; Benjamin Lemasson; Nicolas Pannetier; Regine Farion; Chantal Remy; Greg Zaharchuk; Emmanuel L Barbier
Journal:  Radiology       Date:  2011-12-09       Impact factor: 11.105

2.  Optimization strategies for evaluation of brain hemodynamic parameters with qBOLD technique.

Authors:  Xiaoqi Wang; Alexander L Sukstanskii; Dmitriy A Yablonskiy
Journal:  Magn Reson Med       Date:  2012-05-23       Impact factor: 4.668

Review 3.  The physics of functional magnetic resonance imaging (fMRI).

Authors:  Richard B Buxton
Journal:  Rep Prog Phys       Date:  2013-09-04

Review 4.  Imaging brain oxygenation with MRI using blood oxygenation approaches: methods, validation, and clinical applications.

Authors:  T Christen; D S Bolar; G Zaharchuk
Journal:  AJNR Am J Neuroradiol       Date:  2012-08-02       Impact factor: 3.825

5.  Comparison of R2' measurement methods in the normal brain at 3 Tesla.

Authors:  Wendy Ni; Thomas Christen; Zungho Zun; Greg Zaharchuk
Journal:  Magn Reson Med       Date:  2014-04-18       Impact factor: 4.668

6.  Separation of cellular and BOLD contributions to T2* signal relaxation.

Authors:  Xialing Ulrich; Dmitriy A Yablonskiy
Journal:  Magn Reson Med       Date:  2015-03-10       Impact factor: 4.668

7.  A generalized procedure for calibrated MRI incorporating hyperoxia and hypercapnia.

Authors:  Claudine J Gauthier; Richard D Hoge
Journal:  Hum Brain Mapp       Date:  2012-01-16       Impact factor: 5.038

8.  MR vascular fingerprinting: A new approach to compute cerebral blood volume, mean vessel radius, and oxygenation maps in the human brain.

Authors:  T Christen; N A Pannetier; W W Ni; D Qiu; M E Moseley; N Schuff; G Zaharchuk
Journal:  Neuroimage       Date:  2013-12-07       Impact factor: 6.556

9.  Oxygen metabolism in ischemic stroke using magnetic resonance imaging.

Authors:  Hongyu An; Qingwei Liu; Yasheng Chen; Katie D Vo; Andria L Ford; Jin-Moo Lee; Weili Lin
Journal:  Transl Stroke Res       Date:  2011-12-13       Impact factor: 6.829

Review 10.  MRI techniques to measure arterial and venous cerebral blood volume.

Authors:  Jun Hua; Peiying Liu; Tae Kim; Manus Donahue; Swati Rane; J Jean Chen; Qin Qin; Seong-Gi Kim
Journal:  Neuroimage       Date:  2018-02-16       Impact factor: 6.556

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