Literature DB >> 35397094

Evolution of acute "black hole" lesions in patients with relapsing-remitting multiple sclerosis.

Dejan Kostic1,2, Evica Dincic2,3, Aleksandar Jovanovski1, Smiljana Kostic2,3, Nemanja Rancic4,5, Biljana Georgievski-Brkic6, Miroslav Misovic1,2, Katarina Koprivsek7.   

Abstract

OBJECTIVE: Gadolinium-enhanced T1-weighted lesions are a well-established marker of areas with acute inflammatory activity. A majority of these gadolinium-enhanced T1 lesions are isointense relative to the surrounding white matter, but 20-40% of such active lesions will evolve during one year into areas of low signal ("black hole"). This study sought to characterize evolution of "black hole" lesions in patients with relapsing-remitting multiple sclerosis (MS) using the magnetic resonance imaging (MRI), which measures active lesions via the count of new or enlarged T2 and gadolinium-enhanced T1-weighted lesions.
MATERIALS AND METHODS: This was a prospective, observational case-series study which utilized pre- and post-gadolinium contrast T1-weighted and Proton density MRI scans. Twenty-nine patients (8 males and 21 females) with average age of 38.86 ± 6.58 years and disease duration of 5.75 ± 7.00 years were used to analyze 196 acute demyelinating plaques detected on MRI images during the 24-month follow-up of post-gadolinium signal intensity enhancement of MS plaques.
RESULTS: Significant difference in black hole development was found between the shapes of acute and chronic "black holes". Ring-shaped and patchy plaques were 4.09 (1.87-8.91) times more likely and 1.49 (0.71-3.12) times less likely to develop an acute "black holes" than homogeneous plaques, respectively. Acute plaques with higher lesion-to-CSF SI ratio and larger surface area showed a greater tendency to develop into acute and chronic "black holes".
CONCLUSIONS: The value of lesion-to-CSF SI ratio and surface area were found as the predictors of the "black hole" formation.
© 2022. The Author(s) under exclusive licence to Belgian Neurological Society.

Entities:  

Keywords:  3 T magnet; Acute black holes; Magnetic resonance imaging; Multiple sclerosis; Proton density; T1-weighted

Year:  2022        PMID: 35397094     DOI: 10.1007/s13760-022-01938-9

Source DB:  PubMed          Journal:  Acta Neurol Belg        ISSN: 0300-9009            Impact factor:   2.396


  30 in total

Review 1.  Black holes in multiple sclerosis: definition, evolution, and clinical correlations.

Authors:  M A Sahraian; E-W Radue; S Haller; L Kappos
Journal:  Acta Neurol Scand       Date:  2009-12-05       Impact factor: 3.209

Review 2.  MRI in multiple sclerosis: what's inside the toolbox?

Authors:  Mohit Neema; James Stankiewicz; Ashish Arora; Zachary D Guss; Rohit Bakshi
Journal:  Neurotherapeutics       Date:  2007-10       Impact factor: 7.620

3.  Use of Magnetic Resonance Imaging as Well as Clinical Disease Activity in the Clinical Classification of Multiple Sclerosis and Assessment of Its Course: A Report from an International CMSC Consensus Conference, March 5-7, 2010.

Authors:  Stuart D Cook; Suhayl Dhib-Jalbut; Peter Dowling; Luca Durelli; Corey Ford; Gavin Giovannoni; June Halper; Colleen Harris; Joseph Herbert; David Li; John A Lincoln; Robert Lisak; Fred D Lublin; Claudia F Lucchinetti; Wayne Moore; Robert T Naismith; Carlos Oehninger; Jack Simon; Maria Pia Sormani
Journal:  Int J MS Care       Date:  2012

Review 4.  Association between pathological and MRI findings in multiple sclerosis.

Authors:  Massimo Filippi; Wolfgang Brück; Declan Chard; Franz Fazekas; Jeroen J G Geurts; Christian Enzinger; Simon Hametner; Tanja Kuhlmann; Paolo Preziosa; Àlex Rovira; Klaus Schmierer; Christine Stadelmann; Maria A Rocca
Journal:  Lancet Neurol       Date:  2019-02       Impact factor: 44.182

Review 5.  Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria.

Authors:  Alan J Thompson; Brenda L Banwell; Frederik Barkhof; William M Carroll; Timothy Coetzee; Giancarlo Comi; Jorge Correale; Franz Fazekas; Massimo Filippi; Mark S Freedman; Kazuo Fujihara; Steven L Galetta; Hans Peter Hartung; Ludwig Kappos; Fred D Lublin; Ruth Ann Marrie; Aaron E Miller; David H Miller; Xavier Montalban; Ellen M Mowry; Per Soelberg Sorensen; Mar Tintoré; Anthony L Traboulsee; Maria Trojano; Bernard M J Uitdehaag; Sandra Vukusic; Emmanuelle Waubant; Brian G Weinshenker; Stephen C Reingold; Jeffrey A Cohen
Journal:  Lancet Neurol       Date:  2017-12-21       Impact factor: 44.182

6.  New MRI lesions and topography at 6 months of treatment initiation and disease activity during follow up in relapsing remitting multiple sclerosis patients.

Authors:  Facundo Silveira; Francisco Sánchez; Jimena Miguez; Laura Contartese; Alejandra Gómez; Liliana Patrucco; Edgardo Cristiano; Juan Ignacio Rojas
Journal:  Neurol Res       Date:  2020-01-20       Impact factor: 2.448

Review 7.  Epidemiology of Multiple Sclerosis.

Authors:  Jonathan Howard; Stephen Trevick; David S Younger
Journal:  Neurol Clin       Date:  2016-08-18       Impact factor: 3.806

8.  Persistent T1 hypointensity as an MRI marker for treatment efficacy in multiple sclerosis.

Authors:  I J van den Elskamp; J Lembcke; V Dattola; K Beckmann; C Pohl; W Hong; R Sandbrink; K Wagner; D L Knol; B Uitdehaag; F Barkhof
Journal:  Mult Scler       Date:  2008-07       Impact factor: 6.312

Review 9.  Imaging outcomes for neuroprotection and repair in multiple sclerosis trials.

Authors:  Frederik Barkhof; Peter A Calabresi; David H Miller; Stephen C Reingold
Journal:  Nat Rev Neurol       Date:  2009-05       Impact factor: 42.937

10.  Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria.

Authors:  Chris H Polman; Stephen C Reingold; Brenda Banwell; Michel Clanet; Jeffrey A Cohen; Massimo Filippi; Kazuo Fujihara; Eva Havrdova; Michael Hutchinson; Ludwig Kappos; Fred D Lublin; Xavier Montalban; Paul O'Connor; Magnhild Sandberg-Wollheim; Alan J Thompson; Emmanuelle Waubant; Brian Weinshenker; Jerry S Wolinsky
Journal:  Ann Neurol       Date:  2011-02       Impact factor: 10.422

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