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Brain Imaging

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...

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Related Experiment Video

Updated: Sep 11, 2025

Whole-Brain Single-Cell Imaging and Analysis of Intact Neonatal Mouse Brains Using MRI, Tissue Clearing, and Light-Sheet Microscopy

Whole-Brain Single-Cell Imaging and Analysis of Intact Neonatal Mouse Brains Using MRI, Tissue Clearing, and Light-Sheet Microscopy

Published on: August 1, 2022

Microstructure-informed brain tissue classification using clustering of quantitative MRI measures.

Sharada Balaji¹, Marek Obajtek¹, Irene M Vavasour^2,3

¹Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.

Imaging Neuroscience (Cambridge, Mass.)

|August 13, 2025

Summary

This summary is machine-generated.

The Clustering for Anatomical Quantification and Evaluation (CAQE) framework uses quantitative MRI measures to classify brain tissue based on microstructure. This approach identified demyelination and axonal injury in multiple sclerosis (MS) patients, correlating with cognitive decline.

Keywords:

clustering myelin water imaging tensor-valued diffusion tissue classification tissue microstructure

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Area of Science:

Neuroimaging
Biomedical Engineering
Quantitative MRI

Background:

Conventional MRI segmentation relies on voxel intensities, lacking microstructural detail.
Quantitative MRI offers insights into tissue microstructure beyond conventional imaging.
The Clustering for Anatomical Quantification and Evaluation (CAQE) framework enables microstructural tissue classification.

Purpose of the Study:

To classify brain tissue using microstructural features with the CAQE framework.
To evaluate pathological changes in multiple sclerosis (MS) using CAQE.
To correlate tissue damage severity with cognitive ability in MS patients.

Main Methods:

Utilized myelin water fraction, microscopic fractional anisotropy, and tissue heterogeneity maps.
Applied the CAQE framework to classify brain tissue in healthy controls (n=25).
Applied CAQE to MS patients (n=25) to identify white matter abnormalities.

Main Results:

CAQE successfully classified brain tissue based on microstructural properties.
MS patients showed increased demyelination and axonal injury in white matter compared to controls.
Derived severity scores for white matter damage significantly correlated with cognitive function in MS.

Conclusions:

The CAQE framework provides a novel method for tissue classification using quantitative MRI.
CAQE can detect and quantify microstructural damage in MS, linking it to cognitive impairment.
The CAQE framework is adaptable for various quantitative MRI measures and applications.