What type of study is this?

This is a Quantitative Study study.

September 17, 2025

Classification of COPD and ILD Subtypes Using 129Xe MRI/MRS with Unsupervised Cluster Analysis

Key Points

Four clusters were identified that effectively distinguish healthy individuals from COPD and ILD patients.
Using k-means clustering, the analysis revealed distinct patterns in pulmonary gas exchange and hemodynamics.
Internal validation indices supported the optimal number of clusters for differentiating lung disease subtypes.
This work sets the stage for future clinical trials to validate non-invasive metrics using 129Xe MRI/MRS.

Abstract

Motivation: 129Xe MRI/MRS can assess distinct aspects of pulmonary gas exchange and hemodynamics. However, there is no gold standard against which these metrics can be validated. Goal(s): To evaluate whether unsupervised cluster analysis of 129Xe MRI/MRS metrics naturally reveal patterns known to be associated with certain disease groups. Approach: Eight 129Xe MRI/MRS features were subjected to k-means clustering with internal validation indices used to determine optimal cluster number. Results: The analysis identified four clusters that largely distinguished healthy, COPD, and ILD patient groups. Impact: This study offers a pathway for designing future prospective clinical trials that could validate non-invasive 129Xe MRI/MRS metrics of gas exchange by demonstrating that certain patterns distinguish between lung disease subtypes with high accuracy.

Mark Helpful

Bookmark

Relay