Literature DB >> 8350719

Spin-spin relaxation in experimental allergic encephalomyelitis. Analysis of CPMG data using a non-linear least squares method and linear inverse theory.

W A Stewart1, A L MacKay, K P Whittall, G R Moore, D W Paty.   

Abstract

We have used the CPMG pulse sequence to measure proton T2 values and water content in spinal cord and brain samples from Hartley guinea pigs inoculated to produce experimental allergic encephalomyelitis (EAE). Relaxation data were fitted using minuit, a non-linear curve fitting routine. Three exponentials provided the best fit to spinal cord data (10 ms (13%), 76 ms (57%), 215 ms (30%)) and two exponentials for brain tissue (10 ms (4%), 92 ms (96%)). Least squares algorithms were also used to analyse the spinal cord data in terms of discrete and smooth distributions of relaxation times. The discrete least squares solutions consisted of three to five isolated spikes between 0.010 and 0.300 s. This type of solution was difficult to interpret in terms of water reservoirs. Smooth solutions consisted of two broad peaks, a small peak with a T2 near 0.010 s and a larger peak near 0.100 s. The integral ratio of the larger to the smaller peak was 7.092 +/- 1.782 for normal tissue, and increased to a maximum of 16 with increasing parenchymal cellular infiltration and demyelination. The short T2 peak has been assigned to water in the hydration layers of the myelin sheath. The width of the longer T2 peak was sensitive to tissue heterogeneity. The least squares and smooth distribution analysis models could be used to distinguish samples with extensive parenchymal infiltration from normal tissue, even though only a maximum of 60% of the tissue was affected.(ABSTRACT TRUNCATED AT 250 WORDS)

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Year:  1993        PMID: 8350719     DOI: 10.1002/mrm.1910290608

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


  31 in total

1.  Limitations of rapid myelin water quantification using 3D bSSFP.

Authors:  C Lenz; M Klarhöfer; K Scheffler
Journal:  MAGMA       Date:  2010-04-28       Impact factor: 2.310

Review 2.  Magnetic resonance imaging of myelin.

Authors:  Cornelia Laule; Irene M Vavasour; Shannon H Kolind; David K B Li; Tony L Traboulsee; G R Wayne Moore; Alex L MacKay
Journal:  Neurotherapeutics       Date:  2007-07       Impact factor: 7.620

3.  Development, simulation, and validation of NMR relaxation-based exchange measurements.

Authors:  R D Dortch; R A Horch; M D Does
Journal:  J Chem Phys       Date:  2009-10-28       Impact factor: 3.488

Review 4.  Inferring brain tissue composition and microstructure via MR relaxometry.

Authors:  Mark D Does
Journal:  Neuroimage       Date:  2018-01-02       Impact factor: 6.556

5.  Amyloid oligomer formation probed by water proton magnetic resonance spectroscopy.

Authors:  J H Walton; R S Berry; F Despa
Journal:  Biophys J       Date:  2011-05-04       Impact factor: 4.033

6.  Simulations on the influence of myelin water in diffusion-weighted imaging.

Authors:  K D Harkins; M D Does
Journal:  Phys Med Biol       Date:  2016-06-08       Impact factor: 3.609

7.  Assessment of the myelin water fraction in rodent spinal cord using T2-prepared ultrashort echo time MRI.

Authors:  Tim Klasen; Cornelius Faber
Journal:  MAGMA       Date:  2016-07-09       Impact factor: 2.310

8.  Impact of the acquisition protocol on the sensitivity to demyelination and axonal loss of clinically feasible DWI techniques: a simulation study.

Authors:  Stefania Oliviero; Cosimo Del Gratta
Journal:  MAGMA       Date:  2021-01-08       Impact factor: 2.310

Review 9.  Characterization of cerebral white matter properties using quantitative magnetic resonance imaging stains.

Authors:  Andrew L Alexander; Samuel A Hurley; Alexey A Samsonov; Nagesh Adluru; Ameer Pasha Hosseinbor; Pouria Mossahebi; Do P M Tromp; Elizabeth Zakszewski; Aaron S Field
Journal:  Brain Connect       Date:  2012-01-27

10.  Water mobility spectral imaging of the spinal cord: Parametrization of model-free Laplace MRI.

Authors:  Dan Benjamini; Peter J Basser
Journal:  Magn Reson Imaging       Date:  2018-12-22       Impact factor: 2.546

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