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Postmortem quantitative MRI disentangles histological lesion types in multiple sclerosis.

Riccardo Galbusera1,2, Erik Bahn3, Matthias Weigel1,2,4

  • 1Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland.

Brain Pathology (Zurich, Switzerland)
|December 8, 2022
PubMed
Summary
This summary is machine-generated.

Quantitative MRI measures can differentiate multiple sclerosis (MS) lesion types, particularly remyelinated ones. This study links these MRI measures to myelin, axon, and astrocyte content in MS brain tissue.

Keywords:
histologymultiple sclerosispostmortem imagingquantitative MRIremyelination

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Area of Science:

  • Neuroimaging
  • Neuropathology
  • Biophysics

Background:

  • Quantitative MRI (qMRI) offers biophysical insights into central nervous system (CNS) microstructural properties.
  • Multiple sclerosis (MS) involves complex lesion pathology, including remyelination, which is challenging to characterize non-invasively.
  • Understanding the relationship between qMRI metrics and histological tissue components is crucial for accurate MS assessment.

Purpose of the Study:

  • To identify qMRI measures capable of distinguishing histological lesion types in postmortem MS brains, with a focus on remyelinated lesions.
  • To investigate the correlation between qMRI measures and quantitative histological markers of myelin, axons, and astrocytes within MS lesions and normal-appearing white matter (NAWM).

Main Methods:

  • Three fixed MS whole brains were analyzed using 3T qMRI, acquiring Magnetization Transfer Ratio (MTR), Myelin Water Fraction (MWF), quantitative T1 (qT1), Quantitative Susceptibility Mapping (QSM), Fractional Anisotropy (FA), and Radial Diffusivity (RD) maps.
  • Lesion types (active, inactive, chronic active, remyelinated) were identified histologically.
  • Statistical analyses included logistic regression for lesion discrimination and Spearman correlations/linear mixed-effect models for qMRI-histology associations.

Main Results:

  • MTR and MWF were the most effective qMRI measures for predicting remyelinated lesions.
  • RD and QSM distinguished active lesions, while no significant qMRI differences were found between chronic active and inactive lesions.
  • MWF and RD correlated with myelin content; FA correlated with axon content in both lesions and NAWM; MWF showed association with astrocyte immunoreactivity in lesions, alongside evidence of astrogliosis in remyelinated lesions.

Conclusions:

  • qMRI measures, particularly MTR and MWF, demonstrate significant potential in differentiating MS lesion types, especially remyelinated lesions.
  • Specific qMRI metrics correlate with myelin, axon, and astrocyte content, offering insights into the microstructural underpinnings of MS pathology.
  • The study highlights the utility of qMRI in characterizing MS lesions and provides a foundation for further in vivo investigations.