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

Malo Gicquel1, Anne Kerbrat1,2, Benoit Combès1

  • 1EMPENN Research Team, IRISA, CNRS-INSERM-INRIA, Rennes University, Rennes, France.

Insights

Slowly expanding lesions (SELs) are a new MRI biomarker for chronic inflammation in people with multiple sclerosis (pwMS). Detected in most pwMS, SELs show potential for predicting disease progression.

Area of Science:

  • Neurology
  • Radiology
  • Biomarker Discovery

Background:

  • Slowly expanding lesions (SELs) are a novel imaging finding in people with multiple sclerosis (pwMS).
  • SELs represent a potential biomarker for chronic inflammation, detectable via conventional MRI.
  • Understanding SELs is crucial for advancing multiple sclerosis diagnostics and treatment monitoring.

Purpose of the Study:

  • To conduct a scoping review of studies detecting SELs in pwMS using MRI.
  • To summarize detection methods, frequency, association with other inflammation markers, and prognostic value of SELs.
  • To identify limitations and suggest improvements for SELs as a clinical biomarker.

Main Methods:

  • Systematic literature search for studies reporting SEL detection in pwMS via MRI.
  • Analysis of 33 identified studies using longitudinal MRI acquisitions.
  • Categorization of detection methods and examination of reported frequencies and associations.

Main Results:

  • SELs were detected in the majority of pwMS (60-99%) across various disease phenotypes.
  • Two primary detection methods for SELs were identified, with variations in parameter settings.
  • SELs were more frequent than paramagnetic rim lesions (PRLs), with limited co-localization.

Conclusions:

  • SELs show promise as a biomarker for predicting multiple sclerosis progression and evaluating treatment efficacy.
  • Current detection methods require standardization and improvement for clinical translation.
  • Further research is needed to establish the sensitivity and specificity of SELs for identifying chronic active lesions.