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Hyperpolarized ¹²⁹Xe MRI enables quantitative evaluation of regional ventilation. To this end, multiple classifiers have been proposed to determine ventilation defect percentage (VDP) as well as other cluster populations. However, consensus has not yet been reached regarding which of these methods to deploy for multicenter clinical trials. Here, we compare two published classification techniques–linear-binning and adaptive K-means–to establish their limits of agreement and their robustness against reduced signal-to-noise ratio (SNR).

A total of 29 subjects (age: 38.4 ± 19.0 years) were retrospectively identified for inter-method comparison. For each ¹²⁹Xe ventilation image, 7 images with reduced SNR were generated with equal decrements relative to the native SNR. All 8 sets of images were then analyzed using both methods independently to classify all lung voxels into four clusters: VDP …