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

## TL;DR

This paper introduces a new method for classifying brain tissues using MRI data that focuses on microstructural features, helping detect changes in diseases like multiple sclerosis.

## Contribution

The novel contribution is the CAQE framework, which uses quantitative MRI measures to classify brain tissue without spatial constraints.

## Key findings

- The CAQE framework successfully classified brain tissue using microstructural MRI measures in healthy participants.
- In multiple sclerosis patients, the framework identified areas of demyelination and axonal injury in white matter.
- Severity scores derived from tissue classifications correlated with cognitive ability in MS patients.

## Abstract

Traditional tissue classification approaches in vivo use voxel intensities from conventional clinical magnetic resonance (MR) images for segmentation, which does not incorporate information about specific aspects of microstructure. With the Clustering for Anatomical Quantification and Evaluation (CAQE) framework, quantitative MRI measures can be used to classify tissue based only on microstructural features with no spatial enforcement, and pathological changes in disease can be evaluated. In this study, maps of whole-brain myelin water fraction, microscopic fractional anisotropy, and tissue heterogeneity were used to classify brain tissue in 25 healthy participants. CAQE was then applied to 25 participants with multiple sclerosis (MS), where tissue classifications indicated areas of increased demyelination and axonal injury in white matter compared with a healthy average tissue classification. Severity scores were derived from tissue classifications to quantify diffuse white matter damage, and correlated significantly with cognitive ability in MS. The CAQE framework can be adapted for other applications and extended to use different quantitative MRI measures.