Hyperpolarized3 He 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 (3 He) MRI. Therefore the objective of this study was to compare the reproducibility and spatial agreement of manual and semiautomated segmentation of3 He 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 classify3 He 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 the1 H MRI thoracic cavity for coregistration to the3 He cluster-map, generating VDV and VV. Results We compared manual segmentation performed by an expert observer and semiautomated measurements of3 He 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 VV 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 segmentation3 He MRI provides excellent inter- and intraobserver precision with high spatial and quantitative agreement with manual measurements enabling its use in longitudinal studies.