Literature DB >> 19037018

Subtraction MR images in a multiple sclerosis multicenter clinical trial setting.

Bastiaan Moraal1, Dominik S Meier, Peter A Poppe, Jeroen J G Geurts, Hugo Vrenken, William M A Jonker, Dirk L Knol, Ronald A van Schijndel, Petra J W Pouwels, Christoph Pohl, Lars Bauer, Rupert Sandbrink, Charles R G Guttmann, Frederik Barkhof.   

Abstract

PURPOSE: To explore the applicability of subtraction magnetic resonance (MR) images to (a) detect active multiple sclerosis (MS) lesions, (b) directly quantify lesion load change, and (c) detect treatment effects (distinguish treatment arms) in a placebo-controlled multicenter clinical trial by comparing the subtraction scheme with a conventional pair-wise comparison of nonregistered MR images.
MATERIALS AND METHODS: Forty-six pairs of MR studies in 40 patients (31 women; mean age, 31.9 years) from a multicenter clinical trial were used. The clinical trial was approved by local ethics review boards, and all subjects gave written informed consent. Active MS lesions were scored by two independent raters, and lesion load measurements were conducted by using semiautomated software. Lesion counts were evaluated by using the Wilcoxon signed rank test, interrater agreement was evaluated by using the intraclass correlation coefficient (ICC), and treatment (interferon beta-1b) effect was evaluated by using the Mann-Whitney U test.
RESULTS: When subtraction images were used, there was a 1.7-fold increase in the detection of positive active lesions, as compared with native image pairs, and significantly greater interobserver agreement (ICC = 0.98 vs 0.91, P < .001). Subtraction images also allowed direct quantification of positive disease activity, a measure that provided sufficient power to distinguish treatment arms (P = .012) compared with the standard measurement of total lesion load change on native images (P = .455).
CONCLUSION: MR image subtraction enabled detection of higher numbers of active MS lesions with greater interobserver agreement and exhibited increased power to distinguish treatment arms, as compared with a conventional pair-wise comparison of nonregistered MR images.

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Year:  2008        PMID: 19037018      PMCID: PMC2657481          DOI: 10.1148/radiol.2501080480

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  28 in total

1.  Comparative evaluation of multiresolution optimization strategies for multimodality image registration by maximization of mutual information.

Authors:  F Maes; D Vandermeulen; P Suetens
Journal:  Med Image Anal       Date:  1999-12       Impact factor: 8.545

2.  Optimized single-slab three-dimensional spin-echo MR imaging of the brain.

Authors:  J P Mugler; S Bao; R V Mulkern; C R Guttmann; R L Robertson; F A Jolesz; J R Brookeman
Journal:  Radiology       Date:  2000-09       Impact factor: 11.105

3.  Human gray matter: feasibility of single-slab 3D double inversion-recovery high-spatial-resolution MR imaging.

Authors:  Petra J W Pouwels; Joost P A Kuijer; John P Mugler; Charles R G Guttmann; Frederik Barkhof
Journal:  Radiology       Date:  2006-10-19       Impact factor: 11.105

4.  Intracortical lesions in multiple sclerosis: improved detection with 3D double inversion-recovery MR imaging.

Authors:  Jeroen J G Geurts; Petra J W Pouwels; Bernard M J Uitdehaag; Chris H Polman; Frederik Barkhof; Jonas A Castelijns
Journal:  Radiology       Date:  2005-07       Impact factor: 11.105

5.  Defining multiple sclerosis disease activity using MRI T2-weighted difference imaging.

Authors:  M A Lee; S Smith; J Palace; P M Matthews
Journal:  Brain       Date:  1998-11       Impact factor: 13.501

6.  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

7.  Multi-contrast, isotropic, single-slab 3D MR imaging in multiple sclerosis.

Authors:  Bastiaan Moraal; Stefan D Roosendaal; Petra J W Pouwels; Hugo Vrenken; Ronald A van Schijndel; Dominik S Meier; Charles R G Guttmann; Jeroen J G Geurts; Frederik Barkhof
Journal:  Eur Radiol       Date:  2008-05-29       Impact factor: 5.315

8.  Visual analysis of serial T2-weighted MRI in multiple sclerosis: intra- and interobserver reproducibility.

Authors:  P D Molyneux; D H Miller; M Filippi; T A Yousry; E W Radü; H J Adèr; F Barkhof
Journal:  Neuroradiology       Date:  1999-12       Impact factor: 2.804

9.  Treatment with interferon beta-1b delays conversion to clinically definite and McDonald MS in patients with clinically isolated syndromes.

Authors:  L Kappos; C H Polman; M S Freedman; G Edan; H P Hartung; D H Miller; X Montalban; F Barkhof; L Bauer; P Jakobs; C Pohl; R Sandbrink
Journal:  Neurology       Date:  2006-08-16       Impact factor: 9.910

10.  Magnetic resonance imaging effects of interferon beta-1b in the BENEFIT study: integrated 2-year results.

Authors:  Frederik Barkhof; Chris H Polman; Ernst-Wilhelm Radue; Ludwig Kappos; Mark S Freedman; Gilles Edan; Hans-Peter Hartung; David H Miller; Xavier Montalbán; Peter Poppe; Marlieke de Vos; Fatiha Lasri; Lars Bauer; Susanne Dahms; Klaus Wagner; Christoph Pohl; Rupert Sandbrink
Journal:  Arch Neurol       Date:  2007-09
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  20 in total

1.  Intensity based methods for brain MRI longitudinal registration. A study on multiple sclerosis patients.

Authors:  Yago Diez; Arnau Oliver; Mariano Cabezas; Sergi Valverde; Robert Martí; Joan Carles Vilanova; Lluís Ramió-Torrentà; Alex Rovira; Xavier Lladó
Journal:  Neuroinformatics       Date:  2014-07

2.  Improved Detection of New MS Lesions during Follow-Up Using an Automated MR Coregistration-Fusion Method.

Authors:  A Galletto Pregliasco; A Collin; A Guéguen; M A Metten; J Aboab; R Deschamps; O Gout; L Duron; J C Sadik; J Savatovsky; A Lecler
Journal:  AJNR Am J Neuroradiol       Date:  2018-06-07       Impact factor: 3.825

3.  A novel imaging technique for better detecting new lesions in multiple sclerosis.

Authors:  Paul Eichinger; Hanni Wiestler; Haike Zhang; Viola Biberacher; Jan S Kirschke; Claus Zimmer; Mark Mühlau; Benedikt Wiestler
Journal:  J Neurol       Date:  2017-07-29       Impact factor: 4.849

4.  FLAIRfusion Processing with Contrast Inversion : Improving Detection and Reading Time of New Cerebral MS Lesions.

Authors:  M A Schmidt; R A Linker; S Lang; H Lücking; T Engelhorn; S Kloska; M Uder; A Cavallaro; A Dörfler; P Dankerl
Journal:  Clin Neuroradiol       Date:  2017-03-06       Impact factor: 3.649

Review 5.  Current and Emerging Therapies in Multiple Sclerosis: Implications for the Radiologist, Part 2-Surveillance for Treatment Complications and Disease Progression.

Authors:  C McNamara; G Sugrue; B Murray; P J MacMahon
Journal:  AJNR Am J Neuroradiol       Date:  2017-04-20       Impact factor: 3.825

6.  A subtraction pipeline for automatic detection of new appearing multiple sclerosis lesions in longitudinal studies.

Authors:  Onur Ganiler; Arnau Oliver; Yago Diez; Jordi Freixenet; Joan C Vilanova; Brigitte Beltran; Lluís Ramió-Torrentà; Alex Rovira; Xavier Lladó
Journal:  Neuroradiology       Date:  2014-03-04       Impact factor: 2.804

7.  Multiple sclerosis: identification of temporal changes in brain lesions with computer-assisted detection software.

Authors:  M Bilello; M Arkuszewski; P Nucifora; I Nasrallah; E R Melhem; L Cirillo; J Krejza
Journal:  Neuroradiol J       Date:  2013-05-10

8.  Automatic lesion incidence estimation and detection in multiple sclerosis using multisequence longitudinal MRI.

Authors:  E M Sweeney; R T Shinohara; C D Shea; D S Reich; C M Crainiceanu
Journal:  AJNR Am J Neuroradiol       Date:  2012-07-05       Impact factor: 3.825

9.  Improving Multiple Sclerosis Plaque Detection Using a Semiautomated Assistive Approach.

Authors:  J van Heerden; D Rawlinson; A M Zhang; R Chakravorty; M A Tacey; P M Desmond; F Gaillard
Journal:  AJNR Am J Neuroradiol       Date:  2015-06-18       Impact factor: 3.825

10.  Validation of White-Matter Lesion Change Detection Methods on a Novel Publicly Available MRI Image Database.

Authors:  Žiga Lesjak; Franjo Pernuš; Boštjan Likar; Žiga Špiclin
Journal:  Neuroinformatics       Date:  2016-10
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