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Related Experiment Video

Updated: Jan 29, 2026

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Quantifying White Matter Hyperintensities: Automated Volumetry Compared with Visual Grading Scales.

Arturs Titovs1, Artūrs Šilovs1,2, Kalvis Kaļva1,2,3

  • 1Department of Radiology, Riga Stradins University, LV-1007 Riga, Latvia.

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|January 28, 2026
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Summary

Automated brain MRI analysis of white matter hyperintensities (WMHs) offers a more accurate measure of cognitive decline than visual grading. This automated method provides objective, sensitive, and scalable insights into WMH burden.

Keywords:
Fazekas scaleMontreal Cognitive Assessmentautomated volumetric quantificationcognitive impairmentmagnetic resonance imagingneuroradiologyquantitative neuroimaging biomarkersregional white matter hyperintensitiestotal white matter hyperintensitieswhite matter hyperintensitieswhite matter hyperintensity volume

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Area of Science:

  • Neuroimaging
  • Neurology
  • Medical Imaging Analysis

Background:

  • White matter hyperintensities (WMHs) on MRI are associated with cognitive decline.
  • Current visual grading (Fazekas scale) is subjective and lacks precision.
  • Objective quantification of WMHs is needed for better cognitive assessment.

Purpose of the Study:

  • To compare automated volumetric WMH analysis with visual grading for cognitive impairment assessment.
  • To evaluate the association between WMH volume, distribution, and cognitive status.
  • To determine if automated quantification is superior to visual grading in correlating with cognitive performance.

Main Methods:

  • Retrospective analysis of 41 adult MRIs with cognitive concerns.
  • Automated segmentation of WMHs using Icometrix software for total and regional volumes.
  • Cognitive performance assessed using the Montreal Cognitive Assessment (MoCA) and grouped into high, moderate, and low.
  • Comparison of automated volumes and Fazekas scale grades against MoCA scores.

Main Results:

  • Higher total WMH volume significantly correlated with lower MoCA scores.
  • Automated WMH volume showed significant differences across cognitive groups.
  • The Fazekas scale demonstrated a weaker correlation with MoCA scores compared to automated volume.
  • Stepwise increase in volumetric WMH burden across Fazekas categories confirmed method validity.

Conclusions:

  • Automated volumetric quantification of WMHs is more objective, sensitive, and scalable than visual grading.
  • Automated analysis provides a more accurate measure of WMH burden and its association with cognitive status.
  • This method is better suited for longitudinal monitoring and research in cognitive decline.