Magnetic resonance imaging correlates of clinical outcomes in early multiple sclerosis

Amir-Hadi Maghzi1, Nisha Revirajan1, Laura J Julian2

  • 1Departments of Neurology, University of California San Francisco, San Francisco, CA, United States.

Abstract

Insights

In early multiple sclerosis (MS), lesion volume impacts auditory processing, while brain atrophy predicts physical and composite functional outcomes over time.

Area of Science:

  • Neuroimaging
  • Neurology
  • Clinical Research

Background:

  • Early multiple sclerosis (MS) is characterized by inflammatory lesions and progressive brain atrophy.
  • Understanding the relationship between these imaging markers and clinical outcomes is crucial for predicting disease progression.

Purpose of the Study:

  • To investigate the association between changes in brain magnetic resonance imaging (MRI) metrics and clinical outcomes in patients with early MS.
  • To determine if lesion volume and brain atrophy predict different aspects of long-term clinical decline.

Main Methods:

  • Early MS patients (within 12 months of onset) were followed for up to 3 years.
  • Clinical assessments included Symbol Digit Modalities Test (SDMT), MS Functional Composite (MSFC), and low contrast letter acuity (LCLA).
  • Brain volume changes (brain parenchymal volume, normal-appearing white and gray matter volume, T2 lesion volume) were quantified using SIENA and SIENAX; associations were analyzed using mixed-effects models.

Main Results:

  • Baseline T2 lesion volume predicted changes in Paced Auditory Serial Addition Test (PASAT) scores.
  • Baseline brain atrophy measures (BPV, GMV, NAWMV) predicted changes in MSFC and Timed-25 Foot Walk.
  • A 1% decrease in brain volume (SIENA) correlated with a 1.14-point decrease in SDMT and a 1.5-letter decrease in LCLA.

Conclusions:

  • Lesion volume and overall brain volume changes are associated with distinct clinical outcomes in early MS.
  • MRI-derived measures of lesion load and atrophy provide valuable prognostic information for different functional domains.

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