Literature DB >> 20308453

Improved detection of active multiple sclerosis lesions: 3D subtraction imaging.

Bastiaan Moraal1, Mike P Wattjes, Jeroen J G Geurts, Dirk L Knol, Ronald A van Schijndel, Petra J W Pouwels, Hugo Vrenken, Frederik Barkhof.   

Abstract

PURPOSE: To examine the benefits of using near-isotropic single-slab three-dimensional (3D) magnetic resonance (MR) imaging for the creation of subtraction images and to evaluate their performance in the detection of active multiple sclerosis (MS) brain lesions in comparison with two-dimensional (2D) subtraction images.
MATERIALS AND METHODS: The study protocol was approved by the local ethics review board and all subjects gave written informed consent before investigation. Three-dimensional MR sequences, including double inversion-recovery, fluid-attenuated inversion recovery, T2-weighted, and T1-weighted magnetization-prepared rapid acquisition gradient-echo (MP-RAGE), and corresponding 2D sequences were performed twice in 14 patients (eight women, six men; mean age, 37.6 years) with MS and nine age-matched healthy control subjects (three women, six men; mean age, 31.7 years). Active lesions were scored by two independent raters, followed by a consensus reading. Lesion counts were evaluated by using negative binomial regression; interrater agreement was evaluated by using intraclass correlation coefficient.
RESULTS: Three-dimensional subtraction images had less residual misregistration and flow artifacts and depicted higher numbers of active lesions with greater interobserver agreement compared with 2D subtraction images. Among the 3D sequences, MP-RAGE subtraction imaging enabled detection of a significantly higher mean number of positive active MS lesions compared with 2D subtraction imaging (2.8 versus 1.7, P = .012), particularly infratentorial lesions (0.6 vs 0.1, P < .05), and a substantially higher (nonsignificant) mean number of small (<3 mm) lesions (0.6 vs 0.1, P > .05).
CONCLUSION: Three-dimensional subtraction imaging, after image registration, produced better image quality, leading to increased detection of active MS lesions with greater interobserver agreement in comparison with 2D subtraction imaging; 3D MP-RAGE subtraction imaging represents a promising technique to increase sensitivity in ascertaining lesion dissemination in time and increase the power of MR imaging metrics for the evaluation of treatment effects in clinical trials. RSNA, 2010

Entities:  

Mesh:

Year:  2010        PMID: 20308453     DOI: 10.1148/radiol.09090814

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


  27 in total

Review 1.  MRI monitoring of immunomodulation in relapse-onset multiple sclerosis trials.

Authors:  Frederik Barkhof; Jack H Simon; Franz Fazekas; Marco Rovaris; Ludwig Kappos; Nicola de Stefano; Chris H Polman; John Petkau; Ernst W Radue; Maria P Sormani; David K Li; Paul O'Connor; Xavier Montalban; David H Miller; Massimo Filippi
Journal:  Nat Rev Neurol       Date:  2011-12-06       Impact factor: 42.937

Review 2.  Evidence-based guidelines: MAGNIMS consensus guidelines on the use of MRI in multiple sclerosis--establishing disease prognosis and monitoring patients.

Authors:  Mike P Wattjes; Àlex Rovira; David Miller; Tarek A Yousry; Maria P Sormani; Maria P de Stefano; Mar Tintoré; Cristina Auger; Carmen Tur; Massimo Filippi; Maria A Rocca; Franz Fazekas; Ludwig Kappos; Chris Polman
Journal:  Nat Rev Neurol       Date:  2015-09-15       Impact factor: 42.937

3.  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

4.  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

Review 5.  Evidence-based guidelines: MAGNIMS consensus guidelines on the use of MRI in multiple sclerosis-clinical implementation in the diagnostic process.

Authors:  Àlex Rovira; Mike P Wattjes; Mar Tintoré; Carmen Tur; Tarek A Yousry; Maria P Sormani; Nicola De Stefano; Massimo Filippi; Cristina Auger; Maria A Rocca; Frederik Barkhof; Franz Fazekas; Ludwig Kappos; Chris Polman; David Miller; Xavier Montalban
Journal:  Nat Rev Neurol       Date:  2015-07-07       Impact factor: 42.937

6.  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

Review 7.  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

8.  Predicting breakdown of the blood-brain barrier in multiple sclerosis without contrast agents.

Authors:  R T Shinohara; J Goldsmith; F J Mateen; C Crainiceanu; D S Reich
Journal:  AJNR Am J Neuroradiol       Date:  2012-03-22       Impact factor: 3.825

9.  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

10.  Optimizing 3D FLAIR to detect MS lesions: pushing past factory settings for precise results.

Authors:  Augustin Lecler; C Bouzad; R Deschamps; F Maizeroi; J C Sadik; A Gueguen; O Gout; H Picard; J Savatovsky
Journal:  J Neurol       Date:  2019-08-01       Impact factor: 4.849

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