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Related Experiment Videos

Quantitative diffusion weighted imaging measures in patients with multiple sclerosis.

Eleonora Tavazzi1, Michael G Dwyer, Bianca Weinstock-Guttman

  • 1Buffalo Neuroimaging Analysis Center, Department of Neurology, University at Buffalo, State University of New York, Buffalo, NY, USA.

Neuroimage
|May 15, 2007
PubMed
Summary
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Diffusion-weighted imaging (DWI) effectively detects multiple sclerosis (MS) brain changes. Entropy (ENT) and gray matter fraction (GMF) show strong correlations with disease severity, particularly in SP MS.

Area of Science:

  • Neuroimaging
  • Radiology
  • Neurology

Background:

  • Diffusion-weighted imaging (DWI) shows promise for assessing multiple sclerosis (MS) severity by detecting subtle brain changes.
  • Limited studies have explored DWI's application across different MS clinical subtypes.
  • A novel, automated method for quantitative DWI analysis is proposed.

Purpose of the Study:

  • To validate a novel, fully automated method for calculating quantitative DWI measures.
  • To assess the correlation between whole brain (WB)-DWI variables and clinical/MRI measures of disease severity in a large MS cohort.
  • To differentiate between normal controls (NC), clinically isolated syndrome (CIS), and various MS subtypes using DWI.

Main Methods:

  • 432 MS patients, 16 CIS patients, and 38 NC underwent 1.5 T brain MRI.

Related Experiment Videos

  • Automated calculation of brain parenchymal fraction (BPF), gray matter fraction (GMF), and white matter fraction (WMF).
  • Quantitative DWI indices including mean parenchymal diffusivity (MPD) and entropy (ENT) were derived and correlated with clinical (EDSS, AI, 9-HPT) and lesion volume (T1, T2) data.

    • Main Results:

    • MS patients exhibited significantly lower BPF and GMF, and higher ENT, MPD, and peak height (PH) compared to NC.
    • Significant differences in BPF, GMF, ENT, PH, peak position (PP), T1-LV, T2-LV, WMF, and MPD were observed across MS clinical subtypes (RR, SP, PP).
    • ENT demonstrated a robust correlation with MRI and clinical variables in RR and SP MS, outperforming MPD. GMF and BPF showed stronger relationships with clinical variables than lesion or DWI measures. ENT and GMF were most strongly associated with the SP disease course.

    Conclusions:

    • DWI, particularly using automated methods, is valid for differentiating between NC and MS patients, and among MS subtypes.
    • Entropy (ENT) serves as a sensitive marker for overall brain damage in MS.
    • ENT and GMF are strongly related to clinical impairment, especially in secondary-progressive (SP) MS, highlighting their potential as biomarkers.