Literature DB >> 11836778

Quantitative analysis of MRI signal abnormalities of brain white matter with high reproducibility and accuracy.

Xingchang Wei1, Simon K Warfield, Kelly H Zou, Ying Wu, Xiaoming Li, Alexandre Guimond, John P Mugler, Randall R Benson, Leslie Wolfson, Howard L Weiner, Charles R G Guttmann.   

Abstract

PURPOSE: To assess the reproducibility and accuracy compared to radiologists of three automated segmentation pipelines for quantitative magnetic resonance imaging (MRI) measurement of brain white matter signal abnormalities (WMSA).
MATERIALS AND METHODS: WMSA segmentation was performed on pairs of whole brain scans from 20 patients with multiple sclerosis (MS) and 10 older subjects who were positioned and imaged twice within 30 minutes. Radiologist outlines of WMSA on 20 sections from 16 patients were compared with the corresponding results of each segmentation method.
RESULTS: The segmentation method combining expectation-maximization (EM) tissue segmentation, template-driven segmentation (TDS), and partial volume effect correction (PVEC) demonstrated the highest accuracy (the absolute value of the Z-score was 0.99 for both groups of subjects), as well as high interscan reproducibility (repeatability coefficient was 0.68 mL in MS patients and 1.49 mL in aging subjects).
CONCLUSION: The addition of TDS to the EM segmentation and PVEC algorithms significantly improved the accuracy of WMSA volume measurements, while also improving measurement reproducibility. Copyright 2002 Wiley-Liss, Inc.

Entities:  

Mesh:

Year:  2002        PMID: 11836778     DOI: 10.1002/jmri.10053

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  37 in total

1.  Human brain: reliability and reproducibility of pulsed arterial spin-labeling perfusion MR imaging.

Authors:  Geon-Ho Jahng; Enmin Song; Xiao-Ping Zhu; Gerald B Matson; Michael W Weiner; Norbert Schuff
Journal:  Radiology       Date:  2005-03       Impact factor: 11.105

2.  A rhesus monkey reference label atlas for template driven segmentation.

Authors:  Jonathan J Wisco; Douglas L Rosene; Ronald J Killiany; Mark B Moss; Simon K Warfield; Svetlana Egorova; Ying Wu; Zsusanna Liptak; Jeremy Warner; Charles R G Guttmann
Journal:  J Med Primatol       Date:  2008-05-05       Impact factor: 0.667

Review 3.  Partial volume effect modeling for segmentation and tissue classification of brain magnetic resonance images: A review.

Authors:  Jussi Tohka
Journal:  World J Radiol       Date:  2014-11-28

4.  Vascular dementia.

Authors:  Richard L Strub
Journal:  Ochsner J       Date:  2003

5.  Application of variable threshold intensity to segmentation for white matter hyperintensities in fluid attenuated inversion recovery magnetic resonance images.

Authors:  Byung Il Yoo; Jung Jae Lee; Ji Won Han; San Yeo Wool Oh; Eun Young Lee; James R MacFall; Martha E Payne; Tae Hui Kim; Jae Hyoung Kim; Ki Woong Kim
Journal:  Neuroradiology       Date:  2014-02-04       Impact factor: 2.804

6.  MR imaging intensity modeling of damage and repair in multiple sclerosis: relationship of short-term lesion recovery to progression and disability.

Authors:  D S Meier; H L Weiner; C R G Guttmann
Journal:  AJNR Am J Neuroradiol       Date:  2007 Nov-Dec       Impact factor: 3.825

7.  Computer-assisted segmentation of white matter lesions in 3D MR images using support vector machine.

Authors:  Zhiqiang Lao; Dinggang Shen; Dengfeng Liu; Abbas F Jawad; Elias R Melhem; Lenore J Launer; R Nick Bryan; Christos Davatzikos
Journal:  Acad Radiol       Date:  2008-03       Impact factor: 3.173

8.  Segmentation of subtraction images for the measurement of lesion change in multiple sclerosis.

Authors:  Y Duan; P G Hildenbrand; M P Sampat; D F Tate; I Csapo; B Moraal; R Bakshi; F Barkhof; D S Meier; C R G Guttmann
Journal:  AJNR Am J Neuroradiol       Date:  2008-02       Impact factor: 3.825

9.  Regional white matter atrophy--based classification of multiple sclerosis in cross-sectional and longitudinal data.

Authors:  M P Sampat; A M Berger; B C Healy; P Hildenbrand; J Vass; D S Meier; T Chitnis; H L Weiner; R Bakshi; C R G Guttmann
Journal:  AJNR Am J Neuroradiol       Date:  2009-08-20       Impact factor: 3.825

10.  Multiple sclerosis lesion detection using constrained GMM and curve evolution.

Authors:  Oren Freifeld; Hayit Greenspan; Jacob Goldberger
Journal:  Int J Biomed Imaging       Date:  2009-09-10
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