Evidence map›Paper›PMID 42292345›Full record

ArticleImaging neuroscience (Cambridge, Mass.)

Detection of slowly expanding lesions in people with multiple sclerosis using MRI: A scoping review.

Malo Gicquel, Anne Kerbrat, Benoit Combès

Abstract read
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Malo GicquelEMPENN Research Team, IRISA, CNRS-INSERM-INRIA, Rennes University, Rennes, France.ORCID https://orcid.org/0009-0008-4986-0761
Anne KerbratEMPENN Research Team, IRISA, CNRS-INSERM-INRIA, Rennes University, Rennes, France.ORCID https://orcid.org/0000-0002-4530-3553
Benoit CombèsEMPENN Research Team, IRISA, CNRS-INSERM-INRIA, Rennes University, Rennes, France.ORCID https://orcid.org/0000-0003-4161-7093

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Slowly expanding lesions (SELs) have recently been described in people with multiple sclerosis (pwMS). This pattern of slow lesion expansion, often too subtle to be identified visually, can be detected on conventional brain MRI scans and represents a candidate imaging biomarker of chronic inflammation. The present study undertakes a scoping review of articles reporting the detection of SELs in pwMS using MRI. Our main objectives were to summarize the different methods used to detect SELs, describe their frequency, examine their relationship with other markers of chronic inflammation, and assess their potential prognostic role. We also discuss the limitations of this biomarker and potential methodological improvements that should be explored before considering its translation into clinical routine. We identified 33 studies that detected SELs using longitudinal MRI acquisitions. Two distinct methods for detecting SELs were identified, each implemented with various parameter settings. SELs were detected in most pwMS (60-99%) across all disease phenotypes. SELs were more frequent than paramagnetic rim lesions (PRLs), and these two markers showed only modest co-localization. Several studies suggest that SELs may be a relevant marker for predicting disease progression and evaluating the effects of treatments on chronic inflammation. While SELs appear to be a promising biomarker in pwMS, current methods require further improvement and standardization, which limits inter-study comparability and hinders translation into clinical practice. Moreover, evidence regarding the sensitivity and specificity of SELs in identifying chronic active lesions in vivo remains limited.

Indexed as

chronic active lesionschronic inflammationchronic lesion expansionmultiple sclerosisslowly expanding lesions

Identifiers

PMID42292345
PMCPMC13261561

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.