2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:1287-1297.

Summary Ventilation defect percent (VDP) measured in asthmatics with hyperpolarized helium-3 MRI was more strongly associated with ED visits and hospitalizations due to asthma exacerbation than were conventional biomarkers of lung function and inflammation.

Rationale: Hyperpolarized 129 Xe 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 to be reached regarding which of these methods to deploy for multi-center 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).Methods: 29 subjects (age: 38.4±19.0 years) were retrospectively identified for inter-method comparison. For each 129 Xe ventilation image, 7 reduced SNR image sets 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, Low-, Medium-and High-ventilation-percentage (LVP, MVP and HVP). For each cluster, the percentage of the lung it comprised was compared between the two methods, as well as how these values persisted as SNR was degraded.

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To compare the performance of three-dimensional radial ultrashort echo time (UTE) oxygen-enhanced (OE) MRI with that of hyperpolarized helium 3 (3 He) MRI with respect to quantitative ventilation measurements in patients with cystic fibrosis (CF). Materials and Methods: In this prospective study conducted from June 2013 to May 2015, 25 participants with CF aged 10-55 years (14 male; age range, 13-55 years; 11 female; age range, 10-37 years) successfully underwent pulmonary function tests, hyperpolarized 3 He MRI, and OE MRI. OE MRI used two sequential 3.5-minute normoxic and hyperoxic steady-state free-breathing UTE acquisitions. Seven participants underwent imaging at two separate examinations 1-2 weeks apart to assess repeatability. Regional ventilation was quantified as ventilation defect percentage (VDP) individually from OE MRI and hyperpolarized 3 He MRI by using the same automated quantification tool. Bland-Altman analysis, intraclass correlation coefficient (ICC), Spearman correlation coefficient, and Wilcoxon signed-rank test were used to evaluate repeatability. Results: In all 24 participants, the global VDP measurements from either OE MRI (r = 20.66, P , .001) or hyperpolarized 3 He MRI (r = 20.75, P , .001) were significantly correlated with the percentage predicted forced expiratory volume in 1 second. VDP reported at OE MRI was 5.0% smaller than (P = .014) but highly correlated with (r = 0.78, P , .001) VDP reported at hyperpolarized 3 He MRI. Both OE MRI-based VDP and hyperpolarized 3 He MRI-based VDP demonstrated good repeatability (ICC = 0.91 and 0.95, respectively; P  .001). Conclusion: In lungs with cystic fibrosis, ultrashort echo time oxygen-enhanced MRI showed similar performance compared with hyperpolarized 3 He MRI for quantitative measures of ventilation defects and their repeatability.

Background MRI of hyperpolarized 129Xenon (HP 129Xe) is increasingly utilized for investigating pulmonary function. The solubility of HP 129Xe in lung tissue, blood plasma (Barrier), and red blood cells (RBC), with unique chemical shifts, enables spectroscopic imaging of potential imaging biomarkers of gas exchange and microstructural pulmonary physiology. Purpose To quantify global average and regional repeatability of Barrier:gas, RBC:gas, and RBC:Barrier ratios derived from dissolved‐phase 129Xe imaging and their dependence on intervisit changes in lung inflation volume. Study Type Prospective. Population Fourteen healthy volunteers. One subject was unable to complete the study resulting in 13 subjects for analysis (eight female, five male, ages 24–69, 53.8 ± 13.9). Field Strength 1.5T. Assessment Subjects were imaged using a 3D radial 1‐point Dixon method to separate Barrier and RBC component signals, at two different timepoints, with ~1 month between visits. RBC:Gas, Barrier:Gas, and RBC:Barrier measures were compared across time and with pulmonary function tests (PFTs). Statistical Tests Repeatablilty was quantified using Bland–Altman plots, coefficient of repeatability, coefficient of variation (CV), and intraclass correlation coefficients (ICCs). Dependence of imaging measures on PFTs and lung volume was evaluated using Spearman and Pearson correlation coefficients, respectively. Statistical significance was determined by F‐test for intraclass correlations, and t‐test for Spearman correlations and regression. Results Mean RBC:Gas, Barrier:Gas, and RBC:Barrier had CVs of 19.2%, 20.0%, and 11.5%, respectively, and had significant ICCs, equal to 0.78, 0.79, and 0.92, respectively. Intervisit differences in RBC:Barrier were significantly correlated with intervisit differences in DLCO (r = 0.93, P = 0.007). Significant correlations with intervisit lung volume differences and intervisit differences in mean RBC:Gas (r = –0.73, P = 0.005) and Barrier:Gas (r = –0.69, P = 0.009) were found. Data Conclusion Three commonly used 129Xe MRI‐based measures of gas‐exchange show good repeatability, particularly the Barrier:RBC ratio, which did not depend on lung inflation volume and was strongly associated with intervisit changes in DLCO. Level of Evidence: 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1182–1190.

In asthma, the RML and RUL showed greater ventilation abnormalities, and the RLL and LLL were more highly ventilated with greater local heterogeneity. These findings may facilitate guided bronchoscopic sampling and localized airway treatment in future studies.

Background Ultrashort echo time (UTE) proton MRI has gained popularity for assessing lung structure and function in pulmonary imaging; however, the development of rapid biomarker extraction and regional quantification has lagged behind due to labor‐intensive lung segmentation. Purpose To evaluate a deep learning (DL) approach for automated lung segmentation to extract image‐based biomarkers from functional lung imaging using 3D radial UTE oxygen‐enhanced (OE) MRI. Study Type Retrospective study aimed to evaluate a technical development. Population Forty‐five human subjects, including 16 healthy volunteers, 5 asthma, and 24 patients with cystic fibrosis. Field Strength/Sequence 1.5T MRI, 3D radial UTE (TE = 0.08 msec) sequence. Assessment Two 3D radial UTE volumes were acquired sequentially under normoxic (21% O2) and hyperoxic (100% O2) conditions. Automated segmentation of the lungs using 2D convolutional encoder‐decoder based DL method, and the subsequent functional quantification via adaptive K‐means were compared with the results obtained from the reference method, supervised region growing. Statistical Tests Relative to the reference method, the performance of DL on volumetric quantification was assessed using Dice coefficient with 95% confidence interval (CI) for accuracy, two‐sided Wilcoxon signed‐rank test for computation time, and Bland–Altman analysis on the functional measure derived from the OE images. Results The DL method produced strong agreement with supervised region growing for the right (Dice: 0.97; 95% CI = [0.96, 0.97]; P < 0.001) and left lungs (Dice: 0.96; 95% CI = [0.96, 0.97]; P < 0.001). The DL method averaged 46 seconds to generate the automatic segmentations in contrast to 1.93 hours using the reference method (P < 0.001). Bland–Altman analysis showed nonsignificant intermethod differences of volumetric (P ≥ 0.12) and functional measurements (P ≥ 0.34) in the left and right lungs. Data Conclusion DL provides rapid, automated, and robust lung segmentation for quantification of regional lung function using UTE proton MRI. Level of Evidence: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1169–1181.