Literature DB >> 15711987

Quantification of magnetization transfer rate and native T1 relaxation time of the brain: correlation with magnetization transfer ratio measurements in patients with multiple sclerosis.

Spyros Karampekios1, Nickolas Papanikolaou, Eufrosini Papadaki, Thomas Maris, Kai Uffman, Martha Spilioti, Andreas Plaitakis, Nicholas Gourtsoyiannis.   

Abstract

The purpose of this paper is to perform quantitative measurements of the magnetization transfer rate (Kfor) and native T1 relaxation time (T1free) in the brain tissue of normal individuals and patients with multiple sclerosis (MS) by means of multiple gradient echo acquisitions, and to correlate these measurements with the magnetization transfer ratio (MTR). Quantitative magnetization transfer imaging was performed in five normal volunteers and 12 patients with relapsing-remitting MS on a 1.5 T magnetic resonance (MR) scanner. The T1 relaxation time under magnetization transfer irradiation (T1sat) was calculated by means of fitting the signal intensity over the flip angle in several 3D spoiled gradient echo acquisitions (3 degrees , 15 degrees , 30 degrees , and 60 degrees ), while a single acquisition without MT irradiation (flip angle of 3 degrees ) was utilized to calculate the MTR. The Kfor and T1free constants were quantified on a pixel-by-pixel basis and parametric maps were reconstructed. We performed 226 measurements of Kfor, T1free, and the MTR on normal white matter (NWM) of healthy volunteers (n=50), and normal-appearing white matter (NAWM) and pathological brain areas of MS patients (n=120 and 56, respectively). Correlation coefficients between Kfor-MTR, T1free-MTR, and T1free-Kfor were calculated. Lesions were classified, according to their characteristics on T1-weighted images, into isointense (compared to white matter), mildly hypointense (showing signal intensity lower than white matter and higher than gray matter), and severely hypointense (revealing signal intensity lower than gray matter). "Dirty" white matter (DWM) corresponded to areas with diffused high signal, as identified on T2-weighted images. Strong correlation coefficients were obtained between MTR and Kfor for all lesions studied (r2=0.9, p<0.0001), for mildly hypointense plaques (r2=0.82, p<0.0001), and for DWM (r2=0.78, p=0.0007). In contrast, comparison between MTR and T1free values yielded rather low correlation coefficients for all groups assessed. In severely hypointense lesions, an excellent correlation was found between Kfor and T1free measurements (r2=0.98, p<0.0001). Strong correlations between Kfor and T1free were found for the rest of the subgroups, except for the NAWM, in which a moderate correlation was obtained (r2=0.5, p<0.0001). We conclude that Kfor and T1free measurements are feasible and may improve our understanding of the pathological brain changes that occur in MS patients.

Entities:  

Mesh:

Year:  2005        PMID: 15711987     DOI: 10.1007/s00234-005-1344-1

Source DB:  PubMed          Journal:  Neuroradiology        ISSN: 0028-3940            Impact factor:   2.804


  21 in total

1.  Tissue specificity of low-field-strength magnetization transfer contrast imaging.

Authors:  P T Niemi; M E Komu; S K Koskinen
Journal:  J Magn Reson Imaging       Date:  1992 Mar-Apr       Impact factor: 4.813

2.  Design and implementation of magnetization transfer pulse sequences for clinical use.

Authors:  J V Hajnal; C J Baudouin; A Oatridge; I R Young; G M Bydder
Journal:  J Comput Assist Tomogr       Date:  1992 Jan-Feb       Impact factor: 1.826

3.  Quantitative magnetization transfer imaging of pre-lesional white-matter changes in multiple sclerosis.

Authors:  F Fazekas; S Ropele; C Enzinger; T Seifert; S Strasser-Fuchs
Journal:  Mult Scler       Date:  2002-12       Impact factor: 6.312

4.  Determination of proton magnetization transfer rate constants in heterogeneous biological systems.

Authors:  D Brooks; K Kuwata; T Schleich
Journal:  Magn Reson Med       Date:  1994-03       Impact factor: 4.668

5.  Magnetization transfer contrast (MTC) and tissue water proton relaxation in vivo.

Authors:  S D Wolff; R S Balaban
Journal:  Magn Reson Med       Date:  1989-04       Impact factor: 4.668

6.  Magnetization transfer characterization of hypertensive cardiomyopathy: significance of tissue water content.

Authors:  T D Scholz; T L Ceckler; R S Balaban
Journal:  Magn Reson Med       Date:  1993-03       Impact factor: 4.668

7.  T2 relaxation time analysis in patients with multiple sclerosis: correlation with magnetization transfer ratio.

Authors:  Nickolas Papanikolaou; Eufrosini Papadaki; Spyros Karampekios; Martha Spilioti; Thomas Maris; Panos Prassopoulos; Nicholas Gourtsoyiannis
Journal:  Eur Radiol       Date:  2003-11-05       Impact factor: 5.315

8.  Determination of magnetization transfer contrast in tissue: an MR imaging study of brain tumors.

Authors:  N Lundbom
Journal:  AJR Am J Roentgenol       Date:  1992-12       Impact factor: 3.959

9.  Characterization of multiple sclerosis plaques with T1-weighted MR and quantitative magnetization transfer.

Authors:  L A Loevner; R I Grossman; J C McGowan; K N Ramer; J A Cohen
Journal:  AJNR Am J Neuroradiol       Date:  1995-08       Impact factor: 3.825

Review 10.  The contribution of magnetic resonance imaging to the diagnosis of multiple sclerosis.

Authors:  F Fazekas; F Barkhof; M Filippi; R I Grossman; D K Li; W I McDonald; H F McFarland; D W Paty; J H Simon; J S Wolinsky; D H Miller
Journal:  Neurology       Date:  1999-08-11       Impact factor: 9.910

View more
  10 in total

1.  Diffusely abnormal white matter in progressive multiple sclerosis: in vivo quantitative MR imaging characterization and comparison between disease types.

Authors:  H Vrenken; A Seewann; D L Knol; C H Polman; F Barkhof; J J G Geurts
Journal:  AJNR Am J Neuroradiol       Date:  2009-10-22       Impact factor: 3.825

Review 2.  MRI in multiple sclerosis: what's inside the toolbox?

Authors:  Mohit Neema; James Stankiewicz; Ashish Arora; Zachary D Guss; Rohit Bakshi
Journal:  Neurotherapeutics       Date:  2007-10       Impact factor: 7.620

3.  Macromolecule content influences proton diffusibility in gliomas.

Authors:  Einar Goebell; Jens Fiehler; Susanne Siemonsen; Ole Vaeterlein; Oliver Heese; Christian Hagel; Xiao-Qi Ding; Jan-Hendrik Buhk; Michael Groth; Thomas Kucinski
Journal:  Eur Radiol       Date:  2011-07-16       Impact factor: 5.315

4.  Chronic multiple sclerosis lesions: characterization with high-field-strength MR imaging.

Authors:  Bing Yao; Francesca Bagnato; Eiji Matsuura; Hellmut Merkle; Peter van Gelderen; Fredric K Cantor; Jeff H Duyn
Journal:  Radiology       Date:  2011-11-14       Impact factor: 11.105

5.  Evolution of MS lesions to black holes under DNA vaccine treatment.

Authors:  Athina Papadopoulou; Stefanie von Felten; Stefan Traud; Amena Rahman; Joanne Quan; Robert King; Hideki Garren; Lawrence Steinman; Gary Cutter; Ludwig Kappos; Ernst Wilhelm Radue
Journal:  J Neurol       Date:  2012-01-06       Impact factor: 4.849

Review 6.  Quantitative magnetization transfer imaging in relapsing-remitting multiple sclerosis: a systematic review and meta-analysis.

Authors:  Elizabeth N York; Michael J Thrippleton; Rozanna Meijboom; David P J Hunt; Adam D Waldman
Journal:  Brain Commun       Date:  2022-04-04

7.  Fast magnetization transfer and apparent T1 imaging using a short saturation pulse with and without inversion preparation.

Authors:  Tae Kim; Wanyong Shin; Seong-Gi Kim
Journal:  Magn Reson Med       Date:  2014-03       Impact factor: 4.668

8.  The use of multiparametric quantitative magnetic resonance imaging for evaluating visually assigned lesion groups in patients with multiple sclerosis.

Authors:  Christian Thaler; Tobias D Faizy; Jan Sedlacik; Maxim Bester; Jan-Patrick Stellmann; Christoph Heesen; Jens Fiehler; Susanne Siemonsen
Journal:  J Neurol       Date:  2017-11-20       Impact factor: 4.849

9.  Deficient MWF mapping in multiple sclerosis using 3D whole-brain multi-component relaxation MRI.

Authors:  Hagen H Kitzler; Jason Su; Michael Zeineh; Cynthia Harper-Little; Andrew Leung; Marcelo Kremenchutzky; Sean C Deoni; Brian K Rutt
Journal:  Neuroimage       Date:  2011-09-02       Impact factor: 6.556

10.  A Novel Classification Method using Effective Neural Network and Quantitative Magnetization Transfer Imaging of Brain White Matter in Relapsing Remitting Multiple Sclerosis.

Authors:  M Fooladi; H Sharini; S Masjoodi; E Khodamoradi
Journal:  J Biomed Phys Eng       Date:  2018-12-01
  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.