Literature DB >> 11844733

Brain atrophy in clinically early relapsing-remitting multiple sclerosis.

D T Chard1, C M Griffin, G J M Parker, R Kapoor, A J Thompson, D H Miller.   

Abstract

Brain atrophy measured by MRI is a potentially useful tool for monitoring disease progression in multiple sclerosis. The location, extent and mechanisms of brain atrophy in early disease are not well documented. Using quantitative MRI, this study investigated whole brain, grey and white matter atrophy in clinically early relapsing-remitting multiple sclerosis and its relationship to lesion measures. Data came from 27 normal control subjects (14 females and 13 males, mean age 36.1 years) and 26 subjects with clinically definite multiple sclerosis (18 females and eight males, mean age 35.1 years, mean delay from first symptom to scan 1.8 years, median Expanded Disability Status Scale score 1.0). All had three-dimensional fast spoiled gradient recall (3D FSPGR), T(1)-weighted pre- and post-gadolinium-enhanced and T(2)-weighted scans. The 3D FSPGR images were automatically segmented into grey and white matter and cerebrospinal fluid using SPM99. 3D FSPGR hypo-intense, T(2) hyper-intense, T(1) hypo-intense and T(1) post-gadolinium-enhancing lesion volumes were determined by semi-automatic lesion segmentation. The SPM99 output was combined with the 3D FSPGR lesion segmentations to quantify tissue volumes as fractions of total intracranial volumes, producing values for the brain parenchymal fraction (BPF), white matter fraction (WMF) and grey matter fraction (GMF). Comparing multiple sclerosis with control subjects, BPF, GMF and WMF were significantly reduced (P < 0.001 for all tissue fractions). Using Pearson correlations, T(2) hyper-intense and T(1) hypo-intense lesion volumes were inversely related to BPF (T(2) r = -0.78, P < 0.001; T(1) r = -0.59, P = 0.002) and GMF (T(2) r = -0.73, P < 0.001; T(1) r = -0.53, P = 0.006), but not WMF (T(2) r = -0.30, P = 0.134; T(1) r = -0.26, P = 0.199). T(1) post-gadolinium-enhancing lesion volumes were not correlated with any fractional volumes. These results indicate that significant brain atrophy, affecting both grey and white matter, occurs early in the clinical course of multiple sclerosis. The lack of correlation between lesion load measures and WMF suggests that pathological changes in white matter may occur by mechanisms which are at least partly independent from overt lesion genesis in early multiple sclerosis.

Entities:  

Mesh:

Year:  2002        PMID: 11844733     DOI: 10.1093/brain/awf025

Source DB:  PubMed          Journal:  Brain        ISSN: 0006-8950            Impact factor:   13.501


  120 in total

1.  Standardized calculation of brain parenchymal fraction: an approach to objective assessment of cerebral atrophy.

Authors:  Freimut D Juengling; Jan Kassubek
Journal:  AJNR Am J Neuroradiol       Date:  2003-08       Impact factor: 3.825

2.  Whole-brain atrophy in multiple sclerosis measured by automated versus semiautomated MR imaging segmentation.

Authors:  Jitendra Sharma; Michael P Sanfilipo; Ralph H B Benedict; Bianca Weinstock-Guttman; Frederick E Munschauer; Rohit Bakshi
Journal:  AJNR Am J Neuroradiol       Date:  2004 Jun-Jul       Impact factor: 3.825

3.  Brain volume and diffusion markers as predictors of disability and short-term disease evolution in multiple sclerosis.

Authors:  P G Sämann; M Knop; E Golgor; S Messler; M Czisch; F Weber
Journal:  AJNR Am J Neuroradiol       Date:  2012-03-01       Impact factor: 3.825

4.  Progression of non-age-related callosal brain atrophy in multiple sclerosis: a 9-year longitudinal MRI study representing four decades of disease development.

Authors:  Juha Martola; Leszek Stawiarz; Sten Fredrikson; Jan Hillert; Jakob Bergström; Olof Flodmark; Maria Kristoffersen Wiberg
Journal:  J Neurol Neurosurg Psychiatry       Date:  2006-11-21       Impact factor: 10.154

5.  Prediction of longitudinal brain atrophy in multiple sclerosis by gray matter magnetic resonance imaging T2 hypointensity.

Authors:  Robert A Bermel; Srinivas R Puli; Richard A Rudick; Bianca Weinstock-Guttman; Elizabeth Fisher; Frederick E Munschauer; Rohit Bakshi
Journal:  Arch Neurol       Date:  2005-09

6.  Sensitivity and reproducibility of a new fast 3D segmentation technique for clinical MR-based brain volumetry in multiple sclerosis.

Authors:  Carsten Lukas; Horst K Hahn; Barbara Bellenberg; Jan Rexilius; Gebhard Schmid; Sebastian K Schimrigk; Horst Przuntek; Odo Köster; Heinz-Otto Peitgen
Journal:  Neuroradiology       Date:  2004-11-05       Impact factor: 2.804

7.  Corpus callosum atrophy correlates with gray matter atrophy in patients with multiple sclerosis.

Authors:  Eric C Klawiter; Antonia Ceccarelli; Ashish Arora; Jonathan Jackson; Sonya Bakshi; Gloria Kim; Jennifer Miller; Shahamat Tauhid; Christian von Gizycki; Rohit Bakshi; Mohit Neema
Journal:  J Neuroimaging       Date:  2014-05-09       Impact factor: 2.486

8.  Multiple sclerosis shrinks intralesional, and enlarges extralesional, brain parenchymal veins.

Authors:  María I Gaitán; Manori P de Alwis; Pascal Sati; Govind Nair; Daniel S Reich
Journal:  Neurology       Date:  2012-12-19       Impact factor: 9.910

9.  The effect of daclizumab on brain atrophy in relapsing-remitting multiple sclerosis.

Authors:  Isabela T Borges; Colin D Shea; Joan Ohayon; Blake C Jones; Roger D Stone; John Ostuni; Navid Shiee; Henry McFarland; Bibiana Bielekova; Daniel S Reich
Journal:  Mult Scler Relat Disord       Date:  2013-04-01       Impact factor: 4.339

10.  A longitudinal observational study of brain atrophy rate reflecting four decades of multiple sclerosis: a comparison of serial 1D, 2D, and volumetric measurements from MRI images.

Authors:  Juha Martola; Jakob Bergström; Sten Fredrikson; Leszek Stawiarz; Jan Hillert; Yi Zhang; Olof Flodmark; Anders Lilja; Anders Ekbom; Peter Aspelin; Maria Kristoffersen Wiberg
Journal:  Neuroradiology       Date:  2009-09-23       Impact factor: 2.804

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.