Rationale and Objectives
3 He magnetic resonance imaging (MRI) can be used to quantify functional responses to asthma therapy and provocation. Ventilation imaging offers quantitative information beyond ventilation defects that have not yet been exploited. Therefore, our objective was to evaluate hyperpolarized 3 He MRI ventilation defect percent (VDP) and compare this and pulmonary function measurements to ventilation image texture features and their changes post-bronchodilator administration in patients with asthma.
Materials and Methods
Volunteers with a diagnosis of asthma provided written informed consent to an ethics board-approved protocol and underwent pulmonary function tests and MRI before and after salbutamol inhalation. MR images were analyzed using VDP, and their texture was evaluated via gray-level run-length matrices. These texture classifiers were compared to VDP in responders to bronchodilation based on VDP (VDP responders) and forced expiratory volume in 1 s (FEV 1 ) (FEV 1 responders).
Results
In total, 47 patients with asthma (18 males 39 ± 13 years, FEV 1 = 79 ± 21%) reported significantly improved FEV 1 , FEV 1 /forced vital capacity (FVC), residual volume (RV)/total lung capacity (TLC) (all P = .0001) and VDP ( P = .01) post-salbutamol. Post-salbutamol, VDP responders and nonresponders to salbutamol were significantly different for coarse-texture features including long-run emphasis (LRE) and long-run, low gray-level emphasis (LRLGE, both P < .05) and for FEV 1 responders to salbutamol, there was significantly different long-run, high gray-level emphasis (LRHGE, P = .04). There were significant relationships for VDP with LRE (R = .50, P = .0003), LRLGE (R = .34, P = .02), and LRHGE (R = .56, P = .0001). Receiver operating characteristic curves showed VDP with the strongest performance (AUC = .92), followed by coarse-texture classifier LRHGE (AUC = .83), FEV 1 (AUC = .80), LRE (AUC = .66), FVC (AUC = .58), and LRLGE (AUC = .42).
Conclusions
In patients with asthma, differences in ventilation patchiness post-salbutamol can be quantified using coarse-texture classifiers that are significantly different in bronchodilator responders.
Introduction
Asthma is a chronic inflammatory disease of the small and medium airways caused by smooth muscle hyper-responsiveness and inflammation, leading to intermittent symptoms of dyspnea, coughing, chest tightness, and wheezing . Global estimates indicate that approximately 300 million adults and children report an asthma diagnosis, and this is expected to increase in the future . Short- and long-acting bronchodilators are commonly administered to ease dyspnea and other symptoms , and importantly, the joint American Thoracic Society (ATS)-European Respiratory Society guidelines define a significant bronchodilator response of forced expiratory volume in 1 s (FEV 1 ) or forced vital capacity (FVC) improvement of 200 mL and 12% or greater respectively, as considered definitive for asthma . Bronchodilator response thresholds are controversial, however, because spirometry measurements do not always reflect bronchodilator response in terms of symptomatic relief .
Magnetic resonance imaging (MRI) using hyperpolarized noble gases such as 3 He and 129 Xe provides a way to visualize and quantify ventilation abnormalities in patients with asthma. Hallmark MRI findings in these patients include characteristic focal ventilation defects that appear to respond to therapy and are related to asthma severity . In addition, significant changes in ventilation defects are also observed after bronchodilator administration even in the absence of FEV 1 changes, in asthma and chronic obstructive pulmonary disease (COPD) .
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Methods
Study Subjects and Pulmonary Function Tests
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Asthma Criteria
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Image Acquisition
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Image Analysis and Texture Classifier Generation
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Statistics
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Results
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TABLE 1
Subject Demographics and Pulmonary Measurements
Parameter Mean (SD) Paired Significance (Two Tailed) Pre-Salbutamol ( n = 47) Post-Salbutamol ( n = 47) Age (years) 39 (13) – – Male 18 – – BMI 30 (11) – – FEV 1 % pred 79 (21) 84 (21) .0001 FVC % pred 90 (16) 91 (14) .70 FEV 1 /FVC % 71 (13) 74 (13) .0001 FEF 25–75% 48 (26) \* 77 (9) 2 .005 † TLC % pred 100 (14) 97 (12) .08 \* RV % pred 129 (35) 110 (36) .004 \* RV/TLC % pred 128 (26) 114 (25) .0001 \*
% pred , percent of predicted value; BMI, body mass index; FEV 1 , forced expiratory volume in 1 s; FVC, forced vital capacity; RV, residual volume; SD, standard deviation; TLC, total lung capacity.
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TABLE 2
Ventilation Defect and Texture Measurements
Ventilation Measurements
Mean (SD) All Subjects ( n = 47) Responders ( n = 14) Nonresponders ( n = 33) Pre-Salbutamol Post-Salbutamol Significance Pre-Salbutamol Post-Salbutamol Significance Pre-Salbutamol Post-Salbutamol Significance VDP 6 (7) 4 (5) .01 10 (8) 7 (5) .07 4 (7) 3 (4) .5 SRE .10 (.01) .10 (.01) 2 .10 (.01) .10 (.01) 3 .1 (.01) .1 (.01) 3 LRE 1100 (200) 1100 (100) 2 1000 (150) 1020 (140) 3 1100 (180) 1100 (140) .6 GLNU 3500 (600) 3400 (700) .4 3700 (690) 3300 (550) 4 3500 (580) 3400 (700) 2 RLNU 220 (30) 220 (30) 1 220 (25) 220 (34) 2 220 (30) 230 (30) .8 RP .40 (.05) .41 (.05) .9 .43 (.05) .41 (.05) 2 .42 (.05) .41 (.05) 2 LGRE .70 (.05) .70 (.05) .2 .74 (.03) .72 (.04) .07 .72 (.03 .72 (.04) 2 HGRE 1400 (320) 1400 (300) 2 1300 (240) 1300 (260) 3 1400 (350) 1400 (300) 3 SRLGE .002 (.001) .002 (.001) .8 .002 (.001) .002 (.001) .9 .002 (.001) .002 (.001) 3 SRHGE 1400 (300) 1400 (300) 2 1300 (240) 1300 (260) 2 1400 (350) 1400 (300) 2 LRLGE 830 (100) 800 (100) .4 790 (90) 780 (100) 4 840 (110) 810 (80) .5 LRHGE 6000 (1600) 6300 (1800) .5 5100 (1500) 6000 (1600) .04 6400 (1500) 6500 (1800) 1
Ventilation Measurements
Mean (SD) VDP-Derived Responders ( n = 10) VDP-Derived Nonresponders ( n = 37) Pre-Salbutamol Post-Salbutamol Significance Pre-Salbutamol Post-Salbutamol Significance VDP 10 (3) 6 (0) .001 3 (3) 3 (3) .001 SRE .1 (.02) .1 (.01) 3 .1 (.01) .1 (.01) .5 LRE 870 (130) 980 (160) .01 1100 (150) 1100 (130) .02 GLNU 3700 (800) 3600 (450) 4 3500 (550) 3300 (690) .2 RLNU 220 (20) 220 (30) 4 220 (30) 220 (30) 1 RP .42 (.06) .42 (.05) .8 .43 (.05) .41 (.05) .3 LGRE .75 (.03) .71 (.02) 2 .72 (.03) .71 (.04) .3 HGRE 1400 (400) 1300 (310) 2 1300 (300) 1400 (290) 2 SRLGE .002 (.001) .002 (.001) 2 .002 (.001) .002 (.001) 2 SRHGE 1400 (400) 1300 (300) 3 1300 (300) 1400 (290) 1 LRLGE 710 (80) 770 (90) .04 860 (90) 810 (83) .01 LRHGE 4200 (1000) 5200 (1300) .1 6500 (1400) 6700 (1700) .8
GLNU, gray-level nonuniformity; HGRE, high gray-level run emphasis; LGRE, low gray-level run emphasis; LRE, long-run emphasis; LRHGE, long-run high gray-level emphasis; LRLGE, long-run low gray-level emphasis; RLNU, run-length nonuniformity; RP, run percentage; SD, standard deviation; SRE, short-run emphasis; SRHGE, short-run high-level gray emphasis; SRLGE, short-run, low gray-level emphasis; VDP, ventilation defect percent.
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Discussion
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Acknowledgments
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