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Related Experiment Video

Updated: Jul 5, 2025

Histological Quantification of Chronic Myocardial Infarct in Rats
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A toolkit for stroke infarct volume estimation in rodents.

Rebecca Z Weber1, Davide Bernardoni2, Nora H Rentsch1

  • 1Institute for Regenerative Medicine, University of Zurich, Schlieren 8952, Switzerland; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland.

Neuroimage
|January 14, 2024
PubMed
Summary

Accurately estimating stroke volume is crucial for stroke research. This study presents a toolkit using ex-vivo MRI and immunofluorescence to reliably quantify infarct volumes, showing high correlation between methods for assessing brain tissue damage.

Keywords:
HistologyImmunofluorescence imagingMRIPhotothrombotic strokeStroke sizeStroke volume

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Area of Science:

  • Neuroscience
  • Medical Imaging
  • Histology

Background:

  • Stroke volume is a critical indicator of infarct severity and treatment efficacy.
  • Accurate stroke volume estimation is challenging due to data limitations.
  • Post-mortem imaging and histology are vital for precise brain tissue damage assessment.

Purpose of the Study:

  • To introduce a semi-automated toolkit for reliable stroke volume estimation.
  • To compare infarct volume measurements from ex-vivo MRI and immunofluorescence histology.
  • To investigate stroke-related scarring and angiogenesis in peri-infarct regions.

Main Methods:

  • Utilized ex-vivo magnetic resonance imaging (MRI) of whole mouse brains.
  • Employed immunofluorescence staining on brain sections for histological analysis.
  • Quantified infarct areas at acute (3 days) and chronic (28 days) stages post-stroke.

Main Results:

  • MRI-derived infarct volumes showed high correlation (Pearson r > 0.9) with histological measurements, with low deviation (6.6% acute, 4.9% chronic).
  • High coherence (Dice similarity coefficient > 0.8) was observed between MRI and histology regions of interest.
  • Histology-based delineation exhibited greater inter-operator similarity than MRI.

Conclusions:

  • The developed toolkit enables accurate assessment of brain tissue damage using ex-vivo MRI and histology.
  • Both MRI and histology are effective methods for quantifying infarct volumes.
  • A negative correlation exists between GFAP+ fluorescence intensity and MRI-derived lesion size, indicating altered glial response.