Hyperpolarized 3He Magnetic Resonance Functional Imaging Semiautomated Segmentation

Rationale and Objectives: To improve intra- and interobserver variability and enable the use of functional magnetic resonance imaging (MRI) for multicenter, multiobserver studies, we generated a semiautomated segmentation method for hyperpolarized helium-3 (He-3) MRI. Therefore the objective of this study was to compare the reproducibility and spatial agreement of manual and semiautomated segmentation of He-3 MRI ventilation defect volume (VDV) and ventilation volume (VV) in subjects with asthma, chronic obstructive pulmonary disease (COPD), and cystic fibrosis (CF). Materials and Methods: The multistep semiautomated segmentation method we developed employed hierarchical K-means clustering to classify He-3 MRI pixel intensity values into five user-determined clusters ranging from signal void to hyperintense. A seeded region-growing algorithm was also used to segment the H-1 MRI thoracic cavity for coregistration to the 3He cluster-map, generating VDV and VV. Results: We compared manual segmentation performed by an expert observer and semiautomated measurements of He-3 MRI VDV and observed strong significant correlations between the volumes generated using each method (asthma, n = 5, r = 0.89, P < .0001; COPD, n = 5, r = 0.84, P < .0001; CF, n = 5, r = 0.89, P < .0001). Semiautomated VDV had high interobserver reproducibility (coefficient of variation [CV] = 7%, intraclass correlation coefficient [ICC] = 0.96); intraobserver reproducibility was significantly higher for semiautomated (CV = 5%, ICC = 1.00) compared to manual VDV (CV = 12%, ICC = 0.98). Spatial agreement for W determined using the Dice coefficient (D) was also high for all disease states (asthma, D = 0.95; COPD, D = 0.88; CF, D = 0.90). Conclusions: Semiautomated segmentation 3He MRI provides excellent inter-and intraobserver precision with high spatial and quantitative agreement with manual measurements enabling its use in longitudinal studies.