Rachel L. Eddy

Regional Heterogeneity of Chronic Obstructive Pulmonary Disease Phenotypes: Pulmonary (3)He Magnetic Resonance Imaging and Computed Tomography.

Abstract Pulmonary ventilation may be visualized and measured using hyperpolarized 3He magnetic resonance imaging (MRI) while emphysema and its distribution can be quantified using thoracic computed tomography (CT). Our objective was to phenotype ex-smokers with COPD based on the apical-to-basal distribution of ventilation abnormalities and emphysema to better understand how these phenotypes change regionally as COPD progresses. We evaluated 100 COPD ex-smokers who provided written informed consent and underwent spirometry, CT and 3He MRI. 3He MRI ventilation imaging was used to quantify the ventilation defect percent (VDP) for whole-lung and individual lung lobes. Regional VDP was used to generate the apical-lung (AL)-to-basal-lung (BL) difference (ΔVDP); a positive ΔVDP indicated AL-predominant and negative ΔVDP indicated BL-predominant ventilation defects. Emphysema was quantified using the relative-area-of-the-lung ≤−950HU (RA950) of the CT density histogram for whole-lung and individual lung lobes. The AL-to-BL RA950 difference (ΔRA950) was generated with a positive ΔRA950 indicating AL-predominant emphysema and a negative ΔRA950 indicating BL-predominant emphysema. Seventy-two ex-smokers reported BL-predominant MRI ventilation defects and 71 reported AL-predominant CT emphysema. BL-predominant ventilation defects (AL/BL: GOLD I = 18%/82%, GOLD II = 24%/76%) and AL-predominant emphysema (AL/BL: GOLD I = 84%/16%, GOLD II = 72%/28%) were the major phenotypes in mild-moderate COPD. In severe COPD there was a more uniform distribution for ventilation defects (AL/BL: GOLD III = 40%/60%, GOLD IV = 43%/57%) and emphysema (AL/BL: GOLD III = 64%/36%, GOLD IV = 43%/57%). Basal-lung ventilation defects predominated in mild-moderate GOLD grades, and a more homogeneous distribution of ventilation defects was observed in more advanced grade COPD; these differences suggest that over time, regional ventilation abnormalities become more homogenously distributed during disease progression.

Anatomical pulmonary magnetic resonance imaging segmentation for regional structure-function measurements of asthma

PURPOSE Pulmonary magnetic-resonance-imaging (MRI) and x-ray computed-tomography have provided strong evidence of spatially and temporally persistent lung structure-function abnormalities in asthmatics. This has generated a shift in their understanding of lung disease and supports the use of imaging biomarkers as intermediate endpoints of asthma severity and control. In particular, pulmonary (1)H MRI can be used to provide quantitative lung structure-function measurements longitudinally and in response to treatment. However, to translate such biomarkers of asthma, robust methods are required to segment the lung from pulmonary (1)H MRI. Therefore, their objective was to develop a pulmonary (1)H MRI segmentation algorithm to provide regional measurements with the precision and speed required to support clinical studies. METHODS The authors developed a method to segment the left and right lung from (1)H MRI acquired in 20 asthmatics including five well-controlled and 15 severe poorly controlled participants who provided written informed consent to a study protocol approved by Health Canada. Same-day spirometry and plethysmography measurements of lung function and volume were acquired as well as (1)H MRI using a whole-body radiofrequency coil and fast spoiled gradient-recalled echo sequence at a fixed lung volume (functional residual capacity + 1 l). We incorporated the left-to-right lung volume proportion prior based on the Potts model and derived a volume-proportion preserved Potts model, which was approximated through convex relaxation and further represented by a dual volume-proportion preserved max-flow model. The max-flow model led to a linear problem with convex and linear equality constraints that implicitly encoded the proportion prior. To implement the algorithm, (1)H MRI was resampled into ∼3 × 3 × 3 mm(3) isotropic voxel space. Two observers placed seeds on each lung and on the background of 20 pulmonary (1)H MR images in a randomized dataset, on five occasions, five consecutive days in a row. Segmentation accuracy was evaluated using the Dice-similarity-coefficient (DSC) of the segmented thoracic cavity with comparison to five-rounds of manual segmentation by an expert observer. The authors also evaluated the root-mean-squared-error (RMSE) of the Euclidean distance between lung surfaces, the absolute, and percent volume error. Reproducibility was measured using the coefficient of variation (CoV) and intraclass correlation coefficient (ICC) for two observers who repeated segmentation measurements five-times. RESULTS For five well-controlled asthmatics, forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) was 83% ± 7% and FEV1 was 86 ± 9%pred. For 15 severe, poorly controlled asthmatics, FEV1/FV C = 66% ± 17% and FEV1 = 72 ± 27%pred. The DSC for algorithm and manual segmentation was 91% ± 3%, 92% ± 2% and 91% ± 2% for the left, right, and whole lung, respectively. RMSE was 4.0 ± 1.0 mm for each of the left, right, and whole lung. The absolute (percent) volume errors were 0.1 l (∼6%) for each of right and left lung and ∼0.2 l (∼6%) for whole lung. Intra- and inter-CoV (ICC) were <0.5% (>0.91%) for DSC and <4.5% (>0.93%) for RMSE. While segmentation required 10 s including ∼6 s for user interaction, the smallest detectable difference was 0.24 l for algorithm measurements which was similar to manual measurements. CONCLUSIONS This lung segmentation approach provided the necessary and sufficient precision and accuracy required for research and clinical studies.

Sputum Eosinophilia and Magnetic Resonance Imaging Ventilation Heterogeneity in Severe Asthma

Rationale: Inflammation and smooth muscle dysfunction are integral components of severe asthma that contribute to luminal obstruction causing airflow limitation, ventilation heterogeneity, and symptoms. This is important for guiding treatment decisions directed at the inflammatory (e.g., anti‐T‐helper cell type 2 monoclonal antibodies) and noninflammatory, smooth muscle‐mediated (e.g., bronchial thermoplasty) components of severe asthma. Objectives: To investigate the contribution of eosinophilic bronchitis and smooth muscle dysfunction to magnetic resonance imaging (MRI) ventilation heterogeneity in patients with severe asthma. Methods: We measured the inhaled hyperpolarized gas MRI response to salbutamol as a marker of smooth muscle dysfunction, and sputum eosinophils as a marker of airway inflammation, and their contributions to ventilation heterogeneity (quantified as the ventilation defect percent [VDP]) in 27 patients with severe asthma. Spirometry and forced oscillation airway resistance measurements were also acquired pre‐ and postsalbutamol. Patients were dichotomized on the basis of sputum eosinophilia, and pre‐ and postsalbutamol VDP and physiological measurements were evaluated. Measurements and Main Results: MRI VDP improved with salbutamol inhalation in patients in whom sputum eosinophilia was uncontrolled (≥3%, n = 16) (P = 0.002) and in those in whom it was controlled (<3%, n = 11) (P = 0.02), independent of improvements in FEV1, indicating smooth muscle response. In those patients in whom sputum eosinophilia was uncontrolled, greater VDP persisted postsalbutamol (P = 0.004). Postsalbutamol VDP correlated with sputum eosinophils (r = 0.63; P = 0.005). Conclusions: In patients with severe asthma, MRI regionally identifies the inflammatory and noninflammatory components of airway disease. Ventilation heterogeneity persists postsalbutamol in patients with uncontrolled eosinophilic bronchitis, which may be the functional consequence of airway inflammation.

Ultrashort echo time MRI biomarkers of asthma.

To develop and assess ultrashort echo‐time (UTE) magnetic resonance imaging (MRI) biomarkers of lung function in asthma patients.

Free-breathing Functional Pulmonary MRI: Response to Bronchodilator and Bronchoprovocation in Severe Asthma

RATIONALE AND OBJECTIVES Ventilation heterogeneity is a hallmark feature of asthma. Our objective was to evaluate ventilation heterogeneity in patients with severe asthma, both pre- and post-salbutamol, as well as post-methacholine (MCh) challenge using the lung clearance index, free-breathing pulmonary 1H magnetic resonance imaging (FDMRI), and inhaled-gas MRI ventilation defect percent (VDP). MATERIALS AND METHODS Sixteen severe asthmatics (49 ± 10 years) provided written informed consent to an ethics board-approved protocol. Spirometry, plethysmography, and multiple breath nitrogen washout to measure the lung clearance index were performed during a single visit within 15 minutes of MRI. Inhaled-gas MRI and FDMRI were performed pre- and post-bronchodilator to generate VDP. For asthmatics with forced expiratory volume in 1 second (FEV1) >70%predicted, MRI was also performed before and after MCh challenge. Wilcoxon signed-rank tests, Spearman correlations, and a repeated-measures analysis of variance were performed. RESULTS Hyperpolarized 3He (P = .02) and FDMRI (P = .02) VDP significantly improved post-salbutamol and for four asthmatics who could perform MCh (n = 4). 3He and FDMRI VDP significantly increased at the provocative concentration of MCh, resulting in a 20% decrease in FEV1 (PC20) and decreased post-bronchodilator (P = .02), with a significant difference between methods (P = .01). FDMRI VDP was moderately correlated with 3He VDP (ρ = .61, P = .01), but underestimated VDP relative to 3He VDP (-6 ± 9%). Whereas 3He MRI VDP was significantly correlated with the lung clearance index, FDMRI was not (ρ = .49, P = .06). CONCLUSIONS FDMRI VDP generated in free-breathing asthmatic patients was correlated with static inspiratory breath-hold 3He MRI VDP but underestimated VDP relative to 3He MRI VDP. Although less sensitive to salbutamol and MCh, FDMRI VDP may be considered for asthma patient evaluations at centers without inhaled-gas MRI.

Free-breathing Pulmonary MR Imaging to Quantify Regional Ventilation

Purpose To measure regional specific ventilation with free-breathing hydrogen 1 (1H) magnetic resonance (MR) imaging without exogenous contrast material and to investigate correlations with hyperpolarized helium 3 (3He) MR imaging and pulmonary function test measurements in healthy volunteers and patients with asthma. Materials and Methods Subjects underwent free-breathing 1H and static breath-hold hyperpolarized 3He MR imaging as well as spirometry and plethysmography; participants were consecutively recruited between January and June 2017. Free-breathing 1H MR imaging was performed with an optimized balanced steady-state free-precession sequence; images were retrospectively grouped into tidal inspiration or tidal expiration volumes with exponentially weighted phase interpolation. MR imaging volumes were coregistered by using optical flow deformable registration to generate 1H MR imaging-derived specific ventilation maps. Hyperpolarized 3He MR imaging- and 1H MR imaging-derived specific ventilation maps were coregistered to quantify regional specific ventilation within hyperpolarized 3He MR imaging ventilation masks. Differences between groups were determined with the Mann-Whitney test and relationships were determined with Spearman (ρ) correlation coefficients. Statistical analyses were performed with software. Results Thirty subjects (median age: 50 years; interquartile range [IQR]: 30 years), including 23 with asthma and seven healthy volunteers, were evaluated. Both 1H MR imaging-derived specific ventilation and hyperpolarized 3He MR imaging-derived ventilation percentage were significantly greater in healthy volunteers than in patients with asthma (specific ventilation: 0.14 [IQR: 0.05] vs 0.08 [IQR: 0.06], respectively, P < .0001; ventilation percentage: 99% [IQR: 1%] vs 94% [IQR: 5%], P < .0001). For all subjects, 1H MR imaging-derived specific ventilation correlated with plethysmography-derived specific ventilation (ρ = 0.54, P = .002) and hyperpolarized 3He MR imaging-derived ventilation percentage (ρ = 0.67, P < .0001) as well as with forced expiratory volume in 1 second (FEV1) (ρ = 0.65, P = .0001), ratio of FEV1 to forced vital capacity (ρ = 0.75, P < .0001), ratio of residual volume to total lung capacity (ρ = -0.68, P < .0001), and airway resistance (ρ = -0.51, P = .004). 1H MR imaging-derived specific ventilation was significantly greater in the gravitational-dependent versus nondependent lung in healthy subjects (P = .02) but not in patients with asthma (P = .1). In patients with asthma, coregistered 1H MR imaging specific ventilation and hyperpolarized 3He MR imaging maps showed that specific ventilation was diminished in corresponding 3He MR imaging ventilation defects (0.05 ± 0.04) compared with well-ventilated regions (0.09 ± 0.05) (P < .0001). Conclusion 1H MR imaging-derived specific ventilation correlated with plethysmography-derived specific ventilation and ventilation defects seen by using hyperpolarized 3He MR imaging.

What is the minimal clinically important difference for helium-3 magnetic resonance imaging ventilation defects?

Pulmonary magnetic resonance imaging (MRI) using inhaled polarised gases provides a way to directly visualise and sensitively measure lung ventilation abnormalities or ventilation defects [1]; the burden in individual patients may be directly quantified as the percent ventilation volume [2], ventilation defect volume (VDV) [3] or ventilation defect percent (VDP) [4], which is VDV normalised to the total lung volume. In patients with asthma, MRI ventilation defects worsen during methacholine [5] and exercise challenge [5, 6], and respond to bronchodilation [5, 6]. However, it is still unknown if quantitative changes in MRI ventilation abnormalities directly reflect changes in patient-related outcomes like symptoms; this is important when considering MRI for clinical and research studies in asthma patients, which require an understanding of the minimal clinically important difference (MCID). In asthmatics, the estimated MCID for 3He MRI ventilation defect volume is 110 mL and that for ventilation defect percentage is 2%, which are similar to FEV1, suggesting that these biomarkers are suitable for use in clinical trials http://ow.ly/yQ8K30jAFnX

MRI ventilation abnormalities predict quality-of-life and lung function changes in mild-to-moderate COPD: longitudinal TINCan study

COPD biomarkers are urgently required for clinical trials of new therapies. We evaluated the longitudinal change and relationship of MRI and CT biomarkers of COPD with St. Georges Respiratory Questionnaire (SGRO) and FEV1 worsening over 30 months. Among imaging biomarkers, only the longitudinal change in MRI ventilation defect percent (VDP) was greater in ever-smoker (n=34/p<0.05) and COPD (n=48/p<0.0001) subgroups compared with never-smokers (n=42). Only the longitudinal change in VDP was correlated with change in SGRQ (r=0.26/p=0.03), and only baseline VDP predicted longitudinal change in SGRQ>minimum clinically important difference (p=0.047) in mild-to-moderate COPD. These data strongly support the use of MRI intermediate endpoints in COPD studies. Trial Registration Number NCT02723474; Status: Recruiting.

MRI and CT lung biomarkers: Towards an in vivo understanding of lung biomechanics

BACKGROUND The biomechanical properties of the lung are necessarily dependent on its structure and function, both of which are complex and change over time and space. This makes in vivo evaluation of lung biomechanics and a deep understanding of lung biomarkers, very challenging. In patients and animal models of lung disease, in vivo evaluations of lung structure and function are typically made at the mouth and include spirometry, multiple-breath gas washout tests and the forced oscillation technique. These techniques, and the biomarkers they provide, incorporate the properties of the whole organ system including the parenchyma, large and small airways, mouth, diaphragm and intercostal muscles. Unfortunately, these well-established measurements mask regional differences, limiting their ability to probe the lungs gross and micro-biomechanical properties which vary widely throughout the organ and its subcompartments. Pulmonary imaging has the advantage in providing regional, non-invasive measurements of healthy and diseased lung, in vivo. Here we summarize well-established and emerging lung imaging tools and biomarkers and how they may be used to generate lung biomechanical measurements. METHODS We review well-established and emerging lung anatomical, microstructural and functional imaging biomarkers generated using synchrotron x-ray tomographic-microscopy (SRXTM), micro-x-ray computed-tomography (micro-CT), clinical CT as well as magnetic resonance imaging (MRI). FINDINGS Pulmonary imaging provides measurements of lung structure, function and biomechanics with high spatial and temporal resolution. Imaging biomarkers that reflect the biomechanical properties of the lung are now being validated to provide a deeper understanding of the lung that cannot be achieved using measurements made at the mouth.