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TSPO-Detectable Chronic Active Lesions Predict Disease Progression in Multiple Sclerosis

BACKGROUND AND OBJECTIVES: In the multiple sclerosis (MS) brain, chronic active lesions can be detected using MRI- and PET-based methods. In this study, we investigated whether the frequency of TSPO-PET–detectable chronic active lesions associates with disease progression measured using the Expanded...

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Autores principales: Polvinen, Eero, Matilainen, Markus, Nylund, Marjo, Sucksdorff, Marcus, Airas, Laura M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10291892/
https://www.ncbi.nlm.nih.gov/pubmed/37349108
http://dx.doi.org/10.1212/NXI.0000000000200133
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author Polvinen, Eero
Matilainen, Markus
Nylund, Marjo
Sucksdorff, Marcus
Airas, Laura M.
author_facet Polvinen, Eero
Matilainen, Markus
Nylund, Marjo
Sucksdorff, Marcus
Airas, Laura M.
author_sort Polvinen, Eero
collection PubMed
description BACKGROUND AND OBJECTIVES: In the multiple sclerosis (MS) brain, chronic active lesions can be detected using MRI- and PET-based methods. In this study, we investigated whether the frequency of TSPO-PET–detectable chronic active lesions associates with disease progression measured using the Expanded Disability Status Scale (EDSS) at 5-year follow-up. METHODS: Chronic lesion–associated innate immune cell activation was evaluated using TSPO-PET in 82 patients with MS. Chronic lesions were categorized into rim-active, inactive, and overall active lesion subtypes based on innate immune cell activation patterns in the lesion core and at the 2-mm perilesional rim. Logistic regression was used to identify best predictors of progression. RESULTS: Twenty-one patients experienced disability progression during the follow-up. These patients had a significantly higher proportion of rim-active lesions (p < 0.001) and a significantly lower proportion of inactive lesions (p = 0.001) compared with nonprogressed patients. The results were similar in the patient group having no relapses during the follow-up (60 patients, 14 experienced progression). In logistic regression modeling, the categorized variable “patients with >10% rim-active lesions and ≤50% inactive lesions of all chronic lesions” predicted disease progression in the entire cohort (OR = 26.8, p < 0.001) and in the group free of relapses (OR = 34.8, p = 0.002). DISCUSSION: The results show that single TSPO-PET–based in vivo lesion phenotyping of chronic MS lesions provides a strong predictor for MS disease progression. This emphasizes the significance of chronic active lesions in disability accumulation in MS.
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spelling pubmed-102918922023-06-27 TSPO-Detectable Chronic Active Lesions Predict Disease Progression in Multiple Sclerosis Polvinen, Eero Matilainen, Markus Nylund, Marjo Sucksdorff, Marcus Airas, Laura M. Neurol Neuroimmunol Neuroinflamm Research Article BACKGROUND AND OBJECTIVES: In the multiple sclerosis (MS) brain, chronic active lesions can be detected using MRI- and PET-based methods. In this study, we investigated whether the frequency of TSPO-PET–detectable chronic active lesions associates with disease progression measured using the Expanded Disability Status Scale (EDSS) at 5-year follow-up. METHODS: Chronic lesion–associated innate immune cell activation was evaluated using TSPO-PET in 82 patients with MS. Chronic lesions were categorized into rim-active, inactive, and overall active lesion subtypes based on innate immune cell activation patterns in the lesion core and at the 2-mm perilesional rim. Logistic regression was used to identify best predictors of progression. RESULTS: Twenty-one patients experienced disability progression during the follow-up. These patients had a significantly higher proportion of rim-active lesions (p < 0.001) and a significantly lower proportion of inactive lesions (p = 0.001) compared with nonprogressed patients. The results were similar in the patient group having no relapses during the follow-up (60 patients, 14 experienced progression). In logistic regression modeling, the categorized variable “patients with >10% rim-active lesions and ≤50% inactive lesions of all chronic lesions” predicted disease progression in the entire cohort (OR = 26.8, p < 0.001) and in the group free of relapses (OR = 34.8, p = 0.002). DISCUSSION: The results show that single TSPO-PET–based in vivo lesion phenotyping of chronic MS lesions provides a strong predictor for MS disease progression. This emphasizes the significance of chronic active lesions in disability accumulation in MS. Lippincott Williams & Wilkins 2023-06-22 /pmc/articles/PMC10291892/ /pubmed/37349108 http://dx.doi.org/10.1212/NXI.0000000000200133 Text en Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits downloading and sharing the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.
spellingShingle Research Article
Polvinen, Eero
Matilainen, Markus
Nylund, Marjo
Sucksdorff, Marcus
Airas, Laura M.
TSPO-Detectable Chronic Active Lesions Predict Disease Progression in Multiple Sclerosis
title TSPO-Detectable Chronic Active Lesions Predict Disease Progression in Multiple Sclerosis
title_full TSPO-Detectable Chronic Active Lesions Predict Disease Progression in Multiple Sclerosis
title_fullStr TSPO-Detectable Chronic Active Lesions Predict Disease Progression in Multiple Sclerosis
title_full_unstemmed TSPO-Detectable Chronic Active Lesions Predict Disease Progression in Multiple Sclerosis
title_short TSPO-Detectable Chronic Active Lesions Predict Disease Progression in Multiple Sclerosis
title_sort tspo-detectable chronic active lesions predict disease progression in multiple sclerosis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10291892/
https://www.ncbi.nlm.nih.gov/pubmed/37349108
http://dx.doi.org/10.1212/NXI.0000000000200133
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