Literature DB >> 14607319

Whole-brain atrophy in multiple sclerosis measured by two segmentation processes from various MRI sequences.

M A Horsfield1, M Rovaris, M A Rocca, P Rossi, R H B Benedict, M Filippi, R Bakshi.   

Abstract

Recent MRI and pathologic studies have drawn attention to the destructive nature of the multiple sclerosis (MS) disease process, including the early occurrence of axonal and neuronal loss, leading to macroscopic brain and spinal cord atrophy. Measurement of brain atrophy from MRI has emerged as a potential outcome measure and marker of disease severity in MS and neurodegenerative diseases such as Alzheimer's. However, the optimal method for quantifying atrophy has not been established, including the choice of pulse sequence and segmentation algorithm employed. Using two different MRI scanners to ensure generalizability of results, we compared the reproducibility of four pulse sequences and two analysis methods (fully automated [FA] and semi-automated [SA]) when obtaining brain parenchymal fraction (BPF), a normalized measure of whole-brain atrophy, in patients with MS (n=13) and normal controls (n=2). In order to ensure the validity of our fully automated analysis technique, we also used it to evaluate the atrophy rate over nine months in 57 MS patients from the placebo arm of a clinical trial. All pulse sequences were capable of yielding reproducibility of around 1% coefficient of variation (CoV) or better. The best reproducibility was obtained using 2D multi-slice sequences (conventional spin echo [SE] and fluid-attenuated inversion recovery [FLAIR]), with fully automated analysis. Fully automated analysis of the longitudinal data (conventional spin echo) showed an atrophy rate of -0.5% change in BPF per year, in line with previous findings from a similar cohort of patients. In conclusion, BPF measurement is affected by both pulse sequence and segmentation method. Automated measurement has high reproducibility especially when 2D sequences are used. Semi-automated measurement may have increased accuracy, but with a decreased efficiency and reliability.

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Year:  2003        PMID: 14607319     DOI: 10.1016/j.jns.2003.07.003

Source DB:  PubMed          Journal:  J Neurol Sci        ISSN: 0022-510X            Impact factor:   3.181


  10 in total

1.  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

2.  Reliability of longitudinal brain volume loss measurements between 2 sites in patients with multiple sclerosis: comparison of 7 quantification techniques.

Authors:  F Durand-Dubief; B Belaroussi; J P Armspach; M Dufour; S Roggerone; S Vukusic; S Hannoun; D Sappey-Marinier; C Confavreux; F Cotton
Journal:  AJNR Am J Neuroradiol       Date:  2012-07-12       Impact factor: 3.825

3.  The relationships among MRI-defined spinal cord involvement, brain involvement, and disability in multiple sclerosis.

Authors:  Adam B Cohen; Mohit Neema; Ashish Arora; Elisa Dell'oglio; Ralph H B Benedict; Shahamat Tauhid; Daniel Goldberg-Zimring; Christian Chavarro-Nieto; Antonella Ceccarelli; Joshua P Klein; James M Stankiewicz; Maria K Houtchens; Guy J Buckle; David C Alsop; Charles R G Guttmann; Rohit Bakshi
Journal:  J Neuroimaging       Date:  2011-03-29       Impact factor: 2.486

4.  Automated determination of brain parenchymal fraction in multiple sclerosis.

Authors:  M Vågberg; T Lindqvist; K Ambarki; J B M Warntjes; P Sundström; R Birgander; A Svenningsson
Journal:  AJNR Am J Neuroradiol       Date:  2012-09-13       Impact factor: 3.825

Review 5.  Segmentation of multiple sclerosis lesions in MR images: a review.

Authors:  Daryoush Mortazavi; Abbas Z Kouzani; Hamid Soltanian-Zadeh
Journal:  Neuroradiology       Date:  2011-05-17       Impact factor: 2.804

6.  Evaluating the effects of white matter multiple sclerosis lesions on the volume estimation of 6 brain tissue segmentation methods.

Authors:  S Valverde; A Oliver; Y Díez; M Cabezas; J C Vilanova; L Ramió-Torrentà; À Rovira; X Lladó
Journal:  AJNR Am J Neuroradiol       Date:  2015-02-12       Impact factor: 3.825

7.  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

Review 8.  Quantification and clinical relevance of brain atrophy in multiple sclerosis: a review.

Authors:  Blandine Grassiot; Béatrice Desgranges; Francis Eustache; Gilles Defer
Journal:  J Neurol       Date:  2009-04-08       Impact factor: 4.849

Review 9.  Brain Parenchymal Fraction in Healthy Adults-A Systematic Review of the Literature.

Authors:  Mattias Vågberg; Gabriel Granåsen; Anders Svenningsson
Journal:  PLoS One       Date:  2017-01-17       Impact factor: 3.240

10.  Brief International Cognitive Assessment for MS (BICAMS): international standards for validation.

Authors:  Ralph H B Benedict; Maria Pia Amato; Jan Boringa; Bruno Brochet; Fred Foley; Stan Fredrikson; Paivi Hamalainen; Hans Hartung; Lauren Krupp; Iris Penner; Anthony T Reder; Dawn Langdon
Journal:  BMC Neurol       Date:  2012-07-16       Impact factor: 2.474

  10 in total

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