Hyperpolarized 129Xe MRI Features Associated with Interstitial Lung Disease Identified Using an Interpretable Diagnostic Algorithm.

RATIONALE AND OBJECTIVES: Hyperpolarized 129Xe magnetic resonance imaging and spectroscopy (MRI/MRS) have been used to identify numerous imaging and spectroscopic features that distinguish interstitial lung disease (ILD) from chronic obstructive pulmonary disease (COPD) and healthy controls. However, it remains unclear which specific 129Xe MRI/MRS features, and at what thresholds, are most strongly associated with ILD, relative to COPD and health. MATERIALS AND METHODS: 129Xe MRI/MRS from 155 participants (age 56.6 ± 17.8 years; 80 females), including 84 with ILD, 21 with COPD, and 50 healthy controls, were analyzed to derive eight quantitative metrics. The most informative of these metrics were selected using L1-regularized logistic regression with SHapley Additive exPlanations (SHAP) analysis. These selected metrics then informed a threshold-based decision tree that was evaluated for comprehensive diagnostic performance. Its stability was assessed with bootstrap resampling. RESULTS: The decision tree utilized the following 129Xe metrics: high membrane uptake (Memhigh), ventilation defect percentage (VDP), red blood cell (RBC) transfer defect gradient (ΔRDPBA), and RBC chemical shift, achieving an overall classification accuracy of 93.5%. Class-specific sensitivity/specificity for healthy, COPD and ILD were 90.0%/95.2%, 100%/ 100% and 94.1%/92.9% respectively, with the stability of features and thresholds confirmed by bootstrapping. CONCLUSION: This interpretable approach highlights four physiologically meaningful 129Xe MRI/MRS metrics strongly associated with ILD, supporting their further development for early detection and individualized physiological assessment.

Duke Scholars

Author Aparna Swaminathan Medicine, Pulmonary, Allergy, and Critical Care Medicine

Author Bryan O'Sullivan-Murphy Radiology, Cardiothoracic Imaging

Author Bastiaan Driehuys Radiology

Author David Mummy Radiology