Literature DB >> 34704024

Cortical and phase rim lesions on 7 T MRI as markers of multiple sclerosis disease progression.

Constantina A Treaba1,2, Allegra Conti3, Eric C Klawiter4, Valeria T Barletta1,2, Elena Herranz1,2, Ambica Mehndiratta1, Andrew W Russo4, Jacob A Sloane5, Revere P Kinkel6, Nicola Toschi1,3, Caterina Mainero1,2.   

Abstract

In multiple sclerosis, individual lesion-type patterns on magnetic resonance imaging might be valuable for predicting clinical outcome and monitoring treatment effects. Neuropathological and imaging studies consistently show that cortical lesions contribute to disease progression. The presence of chronic active white matter lesions harbouring a paramagnetic rim on susceptibility-weighted magnetic resonance imaging has also been associated with an aggressive form of multiple sclerosis. It is, however, still uncertain how these two types of lesions relate to each other, or which one plays a greater role in disability progression. In this prospective, longitudinal study in 100 multiple sclerosis patients (74 relapsing-remitting, 26 secondary progressive), we used ultra-high field 7-T susceptibility imaging to characterize cortical and rim lesion presence and evolution. Clinical evaluations were obtained over a mean period of 3.2 years in 71 patients, 46 of which had a follow-up magnetic resonance imaging. At baseline, cortical and rim lesions were identified in 96% and 63% of patients, respectively. Rim lesion prevalence was similar across disease stages. Patients with rim lesions had higher cortical and overall white matter lesion load than subjects without rim lesions (P = 0.018-0.05). Altogether, cortical lesions increased by both count and volume (P = 0.004) over time, while rim lesions expanded their volume (P = 0.023) whilst lacking new rim lesions; rimless white matter lesions increased their count but decreased their volume (P = 0.016). We used a modern machine learning algorithm based on extreme gradient boosting techniques to assess the cumulative power as well as the individual importance of cortical and rim lesion types in predicting disease stage and disability progression, alongside with more traditional imaging markers. The most influential imaging features that discriminated between multiple sclerosis stages (area under the curve±standard deviation = 0.82 ± 0.08) included, as expected, the normalized white matter and thalamic volume, white matter lesion volume, but also leukocortical lesion volume. Subarachnoid cerebrospinal fluid and leukocortical lesion volumes, along with rim lesion volume were the most important predictors of Expanded Disability Status Scale progression (area under the curve±standard deviation = 0.69 ± 0.12). Taken together, these results indicate that while cortical lesions are extremely frequent in multiple sclerosis, rim lesion development occurs only in a subset of patients. Both, however, persist over time and relate to disease progression. Their combined assessment is needed to improve the ability of identifying multiple sclerosis patients at risk of progressing disease.
© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  MRI; cortical lesions; machine learning; multiple sclerosis; phase rim lesions

Year:  2021        PMID: 34704024      PMCID: PMC8361394          DOI: 10.1093/braincomms/fcab134

Source DB:  PubMed          Journal:  Brain Commun        ISSN: 2632-1297


  50 in total

1.  Quantitative in vivo magnetic resonance imaging of multiple sclerosis at 7 Tesla with sensitivity to iron.

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Journal:  Ann Neurol       Date:  2008-12       Impact factor: 10.422

2.  Beyond focal cortical lesions in MS: An in vivo quantitative and spatial imaging study at 7T.

Authors:  Céline Louapre; Sindhuja T Govindarajan; Costanza Giannì; Christian Langkammer; Jacob A Sloane; Revere P Kinkel; Caterina Mainero
Journal:  Neurology       Date:  2015-10-14       Impact factor: 9.910

Review 3.  Microglial immune checkpoint mechanisms.

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4.  Chronic multiple sclerosis lesions: characterization with high-field-strength MR imaging.

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Journal:  Radiology       Date:  2011-11-14       Impact factor: 11.105

5.  Widespread demyelination in the cerebellar cortex in multiple sclerosis.

Authors:  Alexandra Kutzelnigg; Jens C Faber-Rod; Jan Bauer; Claudia F Lucchinetti; Per S Sorensen; Henning Laursen; Christine Stadelmann; Wolfgang Brück; Helmut Rauschka; Manfred Schmidbauer; Hans Lassmann
Journal:  Brain Pathol       Date:  2007-01       Impact factor: 6.508

6.  Seven-tesla phase imaging of acute multiple sclerosis lesions: a new window into the inflammatory process.

Authors:  Martina Absinta; Pascal Sati; María I Gaitán; Pietro Maggi; Irene C M Cortese; Massimo Filippi; Daniel S Reich
Journal:  Ann Neurol       Date:  2013-09-16       Impact factor: 10.422

7.  In vivo characterization of cortical and white matter neuroaxonal pathology in early multiple sclerosis.

Authors:  Tobias Granberg; Qiuyun Fan; Constantina Andrada Treaba; Russell Ouellette; Elena Herranz; Gabriel Mangeat; Céline Louapre; Julien Cohen-Adad; Eric C Klawiter; Jacob A Sloane; Caterina Mainero
Journal:  Brain       Date:  2017-11-01       Impact factor: 13.501

Review 8.  Deep learning for computational biology.

Authors:  Christof Angermueller; Tanel Pärnamaa; Leopold Parts; Oliver Stegle
Journal:  Mol Syst Biol       Date:  2016-07-29       Impact factor: 11.429

9.  Increased PK11195 PET binding in the cortex of patients with MS correlates with disability.

Authors:  Marios Politis; Paolo Giannetti; Paul Su; Federico Turkheimer; Shiva Keihaninejad; Kit Wu; Adam Waldman; Omar Malik; Paul M Matthews; Richard Reynolds; Richard Nicholas; Paola Piccini
Journal:  Neurology       Date:  2012-07-03       Impact factor: 9.910

10.  Iron is a sensitive biomarker for inflammation in multiple sclerosis lesions.

Authors:  Veela Mehta; Wei Pei; Grant Yang; Suyang Li; Eashwar Swamy; Aaron Boster; Petra Schmalbrock; David Pitt
Journal:  PLoS One       Date:  2013-03-14       Impact factor: 3.240

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  2 in total

1.  Multiple sclerosis cortical lesion detection with deep learning at ultra-high-field MRI.

Authors:  Francesco La Rosa; Erin S Beck; Josefina Maranzano; Ramona-Alexandra Todea; Peter van Gelderen; Jacco A de Zwart; Nicholas J Luciano; Jeff H Duyn; Jean-Philippe Thiran; Cristina Granziera; Daniel S Reich; Pascal Sati; Meritxell Bach Cuadra
Journal:  NMR Biomed       Date:  2022-03-31       Impact factor: 4.478

2.  Slowly Expanding Lesions Predict 9-Year Multiple Sclerosis Disease Progression.

Authors:  Paolo Preziosa; Elisabetta Pagani; Alessandro Meani; Lucia Moiola; Mariaemma Rodegher; Massimo Filippi; Maria A Rocca
Journal:  Neurol Neuroimmunol Neuroinflamm       Date:  2022-02-01
  2 in total

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