Using imaging as a biomarker for asthma

Clinical reviews in allergy and immunology

Using imaging as a biomarker for asthma Abhaya Trivedi, MD,a Chase Hall, MD,a Eric A. Hoffman, PhD,b Jason C. Woods, PhD,c David S. Gierada, MD,a and Mario Castro, MD, MPHa St Louis, Mo, Iowa City, Iowa, and Cincinnati, Ohio INFORMATION FOR CATEGORY 1 CME CREDIT Credit can now be obtained, free for a limited time, by reading the review articles in this issue. Please note the following instructions. Method of Physician Participation in Learning Process: The core material for these activities can be read in this issue of the Journal or online at the JACI Web site: www.jacionline.org. The accompanying tests may only be submitted online at www.jacionline.org. Fax or other copies will not be accepted. Date of Original Release: January 2017. Credit may be obtained for these courses until December 31, 2017. Copyright Statement: Copyright Ó 2016-2017. All rights reserved. Overall Purpose/Goal: To provide excellent reviews on key aspects of allergic disease to those who research, treat, or manage allergic disease. Target Audience: Physicians and researchers within the field of allergic disease. Accreditation/Provider Statements and Credit Designation: The American Academy of Allergy, Asthma & Immunology (AAAAI) is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. The AAAAI designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 Creditä. Physicians should claim only the credit commensurate with the extent of their participation in the activity. List of Design Committee Members: Abhaya Trivedi, MD, Chase Hall, MD, Eric A. Hoffman, PhD, Jason C. Woods, PhD, David S. Gierada, MD, and Mario Castro, MD, MPH Disclosure of Significant Relationships with Relevant Commercial Companies/Organizations: E. A. Hoffman has received a grant from the National Institutes of Health and is founder and shareholder of VIDA

Diagnostic, Inc. M. Castro has received personal fees from Boston Scientific, Holaira, Genentech, Teva, GlaxoSmithKline, Boehringer-Ingelheim, Elsevier, and Neostem; has received grants from Amgen, Teva, Novartis, GlaxoSmithKline, Sanofi-Aventis, Vectura, Boehringer-Ingelheim, Medimmune, and Invion; and has received stock from Sparo, Inc. The rest of the authors declare that they have no relevant conflicts of interest. Activity Objectives: 1. To identify the various imaging modalities that are available in evaluating patients with asthma. 2. To describe the advantages and disadvantages of various asthma imaging techniques. 3. To determine the appropriate use of fluorine-18-fluorodeoxyglucose (18FDG) uptake with positron emission tomography (PET), hyperpolarized gas magnetic resonance imaging (MRI), and the cluster method as biomarkers in the evaluation of patients with asthma. 4. To describe the importance and implications of the as-low-asreasonably-achievable (ALARA) principle in imaging modalities used to evaluate patients with asthma. Recognition of Commercial Support: This CME activity has not received external commercial support. List of CME Exam Authors: Yasmin Hamzavi Abedi, MD, Roxanne C. Oriel, MD, Punita Ponda, MD, FAAAAI, and Vincent R. Bonagura, MD, FAAAAI. Disclosure of Significant Relationships with Relevant Commercial Companies/Organizations: The exam authors disclosed no relevant financial relationships.

There have been significant advancements in the various imaging techniques being used for the evaluation of asthmatic patients, both from a clinical and research perspective. Imaging characteristics can be used to identify specific asthmatic phenotypes and provide a more detailed understanding of endotypes contributing to the pathophysiology of the disease. Computed tomography, magnetic resonance imaging, and positron emission tomography can be used to assess pulmonary structure and function. It has been shown that specific airway and lung density measurements using computed tomography correlate with clinical parameters, including severity of disease and pathology, but also provide unique phenotypes.

Hyperpolarized 129Xe and 3He are gases used as contrast media for magnetic resonance imaging that provide measurement of distal lung ventilation reflecting small-airway disease. Positron emission tomography can be useful to identify and target lung inflammation in asthmatic patients. Furthermore, imaging techniques can serve as a potential biomarker and be used to assess response to therapies, including newer biological treatments and bronchial thermoplasty. (J Allergy Clin Immunol 2017;139:1-10.)

From athe Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Washington University School of Medicine, St Louis; bthe Department of Biomedical Engineering, Department of Radiology, University of Iowa College of Medicine, Iowa City; and cthe Center for Pulmonary Imaging Research, Cincinnati Children’s Hospital Medical Center, Cincinnati. Received for publication October 19, 2016; revised November 16, 2016; accepted for publication November 17, 2016. Corresponding author: Mario Castro, MD, MPH, Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Washington University School of

Medicine, 660 S. Euclid Ave, Campus Box 8052, St Louis, MO 63110. E-mail: [email protected]. The CrossMark symbol notifies online readers when updates have been made to the article such as errata or minor corrections 0091-6749/$36.00 Ó 2016 American Academy of Allergy, Asthma & Immunology http://dx.doi.org/10.1016/j.jaci.2016.11.009

Key words: Imaging, chest CT, MRI, PET, biomarker

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Abbreviations used ADC: Apparent diffusion coefficient CFD: Computational fluid dynamics CT: Computed tomography EBUS: Endobronchial ultrasonography FDG: Fluorodeoxyglucose HU: Hounsfield units MRI: Magnetic resonance imaging OCT: Optical coherence tomography PET: Positron emission tomography WA: Wall area WT: Wall thickness

Although chest radiography and computed tomography (CT) remain the primary imaging methods used in the clinical and research evaluation of asthmatic patients, there have been parallel advancements in a growing range of imaging techniques that are now available in both the research and clinical arenas (Table I).1 Modalities such as magnetic resonance imaging (MRI), endobronchial ultrasonography (EBUS), optical coherence tomography (OCT), and positron emission tomography (PET) are among the techniques that can be used in pulmonary imaging of asthmatic patients to assess both structure and function, so that these parameters can be related back to more traditional clinical parameters for a broadened and personalized understanding of the individual patient.2 Imaging characteristics are now providing an understanding of endotypes and further defining asthmatic phenotypes3-5 and can potentially serve as predictive and response biomarkers.6 Lung imaging can be used to assess response to standard treatment, such as inhaled corticosteroids, newer pharmacologic therapies (including biologic agents), and nonpharmacologic therapies (eg, bronchial thermoplasty).7,8 This review will discuss the imaging modalities that are being used currently or have the potential for use to evaluate patients with asthma and assist the clinician in understanding the clinical benefits of their use. We will discuss the implications of imaging techniques as biomarkers and the utility of imaging in assessing and predicting treatment response.

USE OF IMAGING IN THE CLINICAL EVALUATION OF ASTHMA Imaging of the lungs in asthmatic patients has evolved dramatically over the last decade; however, the clinical diagnosis of asthma is still based on a compatible history, examination findings, and evidence of variable airflow obstruction. Chest imaging is most helpful in evaluating complications from asthma and ruling out alternative diagnoses. The chest radiographic findings are nonspecific and often can be normal. The most common abnormal finding is bronchial wall thickening, which is present on 48% to 71% of radiographs,9,10 followed by hyperinflation, which was found in 24% of cases in one series.9 Marked hyperinflation is most often seen in the setting of emphysema. Previous studies evaluating the need for chest radiographs in patients with acute asthma exacerbations revealed that patients presenting to the emergency department with uncomplicated asthma have abnormal chest radiographs only 1% to 2.2% of the time.11,12 However, this number increases to

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nearly 34% in patients who are unresponsive to initial bronchodilator therapy and require admission to the hospital.13 Abnormalities that can change management include pneumothorax, pulmonary vascular congestion, focal parenchymal opacities, and enlarged cardiac silhouette. As with chest radiography, CT of the chest is not indicated in the routine management of asthma. However, it is helpful if the clinician suspects an alternative diagnosis or complication based on an unusual history (eg, large amounts of expectorated sputum suggestive of bronchiectasis) or physical examination findings (eg, inspiratory crackles suggestive of interstitial lung disease). Common CT findings include bronchial wall thickening, air trapping, and bronchiectasis.14 Automated techniques are now being used to evaluate the extent of airway wall thickening in a highly objective and reproducible manner. Multiple studies have demonstrated that disease severity correlates with the degree of bronchial thickening and air trapping.15-17 Importantly, CT imaging might be necessary to rule out diseases that masquerade as asthma, such as intrathoracic or extrathoracic airway obstruction, obliterative bronchiolitis, chronic obstructive pulmonary disease, congestive heart failure, hypersensitivity pneumonitis, hypereosinophilic syndromes, allergic bronchopulmonary aspergillosis, and eosinophilic granulomatosis with polyangiitis (Churg-Strauss syndrome). In the evaluation of asthma, MRI is an appealing complementary or, in some cases, alternative modality to CT imaging because of the lack of ionizing radiation. However, at this time, MRI is limited to asthma research because of the paucity of anatomic detail with conventional proton MRI. Hyperpolarized helium and xenon gases have emerged as methods for evaluating the functional changes of the distal small airways.18 By using this technique, ventilation defects can be quantified by evaluating the percentage of voxels with a signal intensity of less than a threshold of 60% of the total lung mean signal intensity. Studies have demonstrated that patients with severe asthma have larger ventilation defects than those without severe asthma.19 The comparative contributions of CT and MRI to an improved understanding of the lungs has been recently reviewed.20 Typically, imaging is performed at full inspiration (total lung capacity [TLC]; Fig 1, A) and end expiration, either at residual volume or functional residual capacity (Fig 1, B). Protocols for specific scanners21 and automated image analysis software are used to identify the lungs, lobes (Fig 1, A), airway tree (Fig 2), and vascular tree. Empirically derived thresholds have been established whereby the percentage of the imaged voxels within the lung field at total lung capacity of less than 2950 Hounsfield units (HU) is considered emphysema-like or hyperinflated. Voxels of less than 2856 HU on the expiratory image are considered air trapped (Fig 3). Image-matching methods have been used (parametric response mapping22 and disease probability mapping23,24; Fig 4, A and B), whereby inspiratory and expiratory scans are warped together such that voxels can be assigned to categories of air-trapped, normal, and hyperinflated lungs. Airway metrics include luminal area, minimum and maximum diameters, hydraulic diameter, tapering, wall area (WA) and wall thickness (WT), WA percentage (WA%), and branch angles. Previous applications of these various metrics to asthma have been reviewed by Castro et al.2 CT examinations have increased from approximately 3 million in 1980 to 80 million in 2011.25,26 The expansion of CT use in medicine and in the novel phenotyping of the lung in both

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TABLE I. Asthma imaging summary Modality

CT

MRI

Structural assessment

Detailed assessment d Airway tree d Vascular tree d Lung parenchyma d d

EBUS

OCT

PET

d

d

d

Lung microstructure using ADC Combined with CT for detailed structural evaluation Access airways as small as 4 mm with visualization of multiple layers of airway wall Two-dimensional images of airway wall with spatial resolution of 1-15 mm and penetration of 2-4 mm Combine with CT for detailed structural evaluation

Functional assessment d d

Clinical utility

Regional ventilation Parenchymal perfusion

d d

d

d

High spatial resolution evaluation of regional ventilation Gas exchange

d

None

d

d

d

Disadvantages

Noninvasive measure of airway remodeling Biomarker to assess response to therapy

d

Radiation exposure prohibits serial examinations

Biomarker to assess response to therapy Assessment of ventilation/ perfusion ratio

d

Less structural detail than CT Limited to specialized MRI centers

Monitor serial airways changes

d

d

d d d

None

d d

Microscopic view of WT and subepithelial matrix Monitor serial airway changes

d d d

d d

Pulmonary inflammation Ventilation/perfusion

d d

Response to anti-inflammatory therapies Evaluate inhaled drug delivery

d d

Requires bronchoscopy No functional assessment Standards not yet established Requires bronchoscopy Subject to respiratory cycle movement Standards not yet established Limited spatial resolution Radiation exposure

FIG 1. Chest CT for lung density. A, Three-dimensional volume rendition of the lung, lobes, and bronchial tree detected from a CT image of the fully inflated (total lung capacity) lung of a healthy subject. B, CT scan of the chest showing a similar volume rendition using the expiratory image (in this case functional residual capacity) of a patient with severe asthma. Note the areas of air trapping and pruning of the airways. Image processing was derived by using Apollo software (VIDA Diagnostics, Coralville, Iowa).

asthmatic patients and those with chronic obstructive pulmonary disease has led to growing public concern about the potential risk of excess cancers. Because radiation risks are greatest in women and younger patients, the dose delivered should remain a special concern in these populations.27,28 In this context physicians and researchers must consider the risk/benefit ratio when seeking to use this imaging modality. There have been considerable improvements in the sensitivity and spatial resolution of detector technologies; improvements in iterative reconstruction methodologies for image noise reduction associated with low-dose imaging29; use of more powerful x-ray tubes with smaller focal spots, allowing for beam shaping with tin filters30; and use of variable doses31 as the scanner spirals about the thorax based on local path lengths and densities. Thus, with the appropriate technologies, CT imaging can be carried out at 1% to 3% of previous doses.32,33 Therefore CT chest examinations

should be programmed with techniques that conform to the as-low-as-reasonably-achievable principal yet provide adequate image quality.

ASSESSING LUNG STRUCTURE AND FUNCTION WITH CT, OCT, EBUS, PET, AND MRI With the drive to more broadly use CT for its newfound roles in clinical assessment of the lung, screening, phenotyping, and drug and device discovery and outcomes assessment, there have been rapid advances, bringing highly evolved CT technologies into the clinical environment. CT imaging can provide comprehensive evaluation of the lung by allowing for detailed descriptions of not only the airway tree and lung parenchyma but also regional ventilation.2 Multidetector row CT allows for faster acquisition of

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FIG 3. Chest CT scan showing air-trapping distribution. The figure demonstrates the concentration of regions determined to represent air trapping (voxels < 2856) on the expiratory CT image of the same patient with severe asthma shown in Fig 1, B. Trapped air, which was defined as voxels within the lung field of less than 2856 HU, are demonstrated by spheres proportional to the area of air trapping (volume-rendered view). Each lobe is color coded. Image processing was derived by using Apollo software (VIDA Diagnostics, Coralville, Iowa). FIG 2. Three-dimensional chest CT scan of the bronchial tree. The figure demonstrates labeling of the bronchial tree out to the segmental bronchi of a patient with severe asthma, enabling each segmental bronchial WT to be measured quantitatively. Image processing was derived by using Apollo software (VIDA Diagnostics, Coralville, Iowa). BronInt, Bronchus intermedius; LLB, left lower lobe bronchus; LMB, left mainstem bronchus; LUL, left upper lobe; RMB, right mainstem bronchus; RUL, right upper lobe.

multiple cross-sectional slices of images with a high spatial resolution. OCT is a tool that produces a 2-dimensional image of the airway wall by using near-infrared light through a fiberoptic catheter.34 Distinct imaging patterns are produced as a result of the varying optical refractive properties of the different tissue layers (Fig 5).35 A previous study of patients with chronic obstructive pulmonary disease showed a strong correlation between OCT and CT measurements of average WA and lumen area.36 Asthmatic patients, when evaluated by using OCT, had greater distension of the airways at a given pressure and had decreased lumen area compared with control subjects.37 Therefore OCT can be used to monitor serial airway changes after a therapeutic intervention, such as bronchial thermoplasty, while avoiding cumulative radiation exposure (Fig 5). Another method for assessing airway structure is through the use of EBUS. It is performed with an ultrasonographic probe through the working channel of a fiberoptic bronchoscope. Radial EBUS can access airways as small as 4 mm in internal diameter, and it can visualize multiple layers of the airway wall (Fig 6).38 Studies with EBUS demonstrated an increase in airway WT in asthmatic patients compared with that in healthy control subjects comparable with that measured by using CT.39,40 Like OCT, EBUS offers the ability to monitor serial changes without exposure to ionizing radiation. Although OCT and EBUS can be used to identify structural changes, CT in combination with MRI and PET imaging can provide an objective quantitative assessment of the interactions between structure and function. Several imaging modalities, including CT, MRI, PET, or any combination of the 3, have been used to assess regional lung function. Hyperpolarized 3He and 129Xe gases are used as MRI contrast media for measuring

pulmonary function biomarkers, which include lung ventilation, quantification of airway microstructures, and gas exchange (Fig 7, A).7,18,41-46 Ventilation defects observed in hyperpolarized gas magnetic resonance images of asthmatic patients (Fig 7, B) have been shown to correspond spatially to regions of air trapping, as identified on CT.47 One study determined that the number of ventilation defects per image slice correlated to asthma severity and degree of airflow limitation.19 Furthermore, the ventilation defect percentage, as measured by using hyperpolarized 3He MRI, has been shown to correlate with the clinical features of asthmatic patients, including medication requirement, airway pathology, severity, symptom score, and atopic markers.48 It was also shown that many areas of regional obstruction persisted over time, with 67% of ventilation defects persisting over an interval of 31 days and 38% persisting over 85 days.44 It has also been shown that 3He MRI can be used to measure treatment effects after bronchial thermoplasty.7 The apparent diffusion coefficient (ADC), a method that takes advantage of the diffusive nature of gases in diffusion-weighted MRI, can be used to infer the structure of alveoli and terminal bronchioles.49 Regions in which the diffusive motion of gas atoms are restricted by normal alveolar walls have lower ADC values, whereas areas of increased alveolar size or alveolar destruction allow for increased diffusion and are characterized by higher ADC values (Fig 8). Higher ADC values have been shown to correlate with areas of emphysema-like lung by using CT and lower diffusion capacity on pulmonary function testing.50 Asthmatic patients have been found to have small focal areas of increased ADC values that might represent air trapping.51 Although hyperpolarized gas MRI provides a direct measure of lung ventilation, the high cost and shortage of 3He and the need for polarizers and specialized hardware, limit this technique to certain research institutions.52 Multivolume CT and 1H MRI are also used as another means for evaluating lung function by extracting the per-voxel signal/ density change between inspiration and expiration.53-56 Previous multivolume CT studies have demonstrated the ability of this

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FIG 4. MDCT chest image matching. Parametric response mapping22 and disease probability mapping23,24 methods are demonstrated whereby inspiratory and expiratory scans are warped together, such that voxels can be assigned to categories of air trapped, normal, and emphysema/hyperinflated. A, Voxels from total lung capacity (y-axis) and functional residual capacity (x-axis) in terms of their probability of being hyperinflated versus ventilated in a plot from a patient with severe asthma, A healthy subject is shown in the insert (upper left). Green represents the normal end of the scale, yellow represents the probability of being air trapped (poorly ventilated), and red represents hyperinflation. Because the image is a probability map, the colors are shown blended. B, Quantitation of clusters of air-trapped versus normal lung tissue as a function of lung location. LLL, Left lower lobe; LUL, left upper lobe; RLL, right lower lobe; RML, right middle lobe; RUL, right upper lobe.

technique to assess regional changes in lung density (interpreted as ventilation) and regional variations in ventilation in both healthy subjects and diseased patients.53,55,56 Although this technique using CT has been shown to be exquisitely sensitive to regional variation, concern over exposure to ionizing radiation makes serial imaging with CT impractical, particularly for vulnerable populations.57,58 Multivolume MRI has recently been developed as a potential surrogate for assessing ventilation inhomogeneity caused by gravitational dependence and regional abnormalities caused by lung disease.54 One advantage of gated MRI is that patients can freely breathe during a scan; through a technique of either prospective or retrospective gating, images at inspiration and expiration can be used for ventilation mapping.59 PET is able to measure pulmonary perfusion and ventilation when used in combination with a positron emitter isotope of nitrogen, 13NN. These PET ventilation studies have been undertaken to assess asthma pathophysiology and have allowed for the development of models that help explain the heterogeneity of peripheral airway involvement.60,61 Although 13NN-PET imaging can provide a direct measure of lung ventilation, it is limited by low resolution, low signal-to-noise ratios, nontrivial radiation doses, and time-averaged acquisitions that might not reflect tidal breathing.62 In addition to measuring lung ventilation, PET imaging, most often with fluorine-18-fluorodeoxyglucose (18F-FDG), a commonly used radiolabeled molecule, is able to visualize metabolically active cells. FDG-PET shows promise as an imaging biomarker of lung inflammation in asthmatic patients because previous studies suggest that neutrophils are the primary source of increased FDG uptake in the lungs.63 Furthermore, in studies involving human subjects, increased regional FDG uptake was shown to correlate with conditions characterized by inflammation, sarcoidosis, cystic fibrosis, and chronic obstructive pulmonary disease.64-67 The ability of FDG-PET to assess an

inflammatory response points to its potential as a tool to better understand asthma pathogenesis, phenotype differences, and responses to anti-inflammatory therapies.2 Conventional lung function measurement techniques, such as pulmonary function tests and exercise tests, which measure aerobic capacity and dynamic hyperinflation, lack the ability to assess regional distribution of changes in local airway resistances and airway volume growth.68 Computational fluid dynamics (CFD) is a technique whereby airflow patterns of the respiratory system are simulated in 3-dimensional computer models, and this provides a quantitative basis for predicting airflow and transport of inhaled material.69 CFD combined with highresolution CT was used to study the asthmatic response to bronchodilation.70 This study determined that changes in CFD airway model parameters after administration of a bronchodilator correlated to the observed changes in clinical outcomes discovered through spirometric measurements.70 A separate study used hyperpolarized 3He phase-contrast MRI in conjunction with CFD to compare measured and predicted airflow patterns in rat pulmonary airways. Their findings demonstrated that integration of these 2 techniques can be used to develop and assess predicted airflow in vivo and test mass-transfer models, which are fundamental to gas mixing in respiratory physiology.71 Additionally, CFD models have been used in an attempt to assess the bronchiolar airway deposition of inhaled aerosolized medication to better understand delivery of anti-inflammatory drugs in asthmatic patients.72 CT and proton MRI tend to overlap somewhat in the implementation of visualizing lung structure and function; however, each imaging modality has its own set of drawbacks and advantages. Specifically, CT is typically the gold standard in pulmonary imaging and offers greater image resolution and easily interpretable x-ray attenuation in HU, but it exposes patients to ionizing radiation. Although the resolution of MRI is often slightly lower, it can serve as a longitudinal imaging surrogate

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FIG 5. OCT images (A) and mean 6 SD airway measurements (B) before bronchial thermoplasty (BT), 6 months after bronchial thermoplasty, and 2 years after bronchial thermoplasty, with the corresponding bronchial biopsy specimen at 6 months after bronchial thermoplasty (C). BM, Basement membrane; Epi, epithelium; SM, smooth muscle; WA, airway wall. Scale bars 5 1 mm. Reproduced with permission of the European Respiratory Society from Kirby et al.35

for CT to limit a patient’s exposure to ionizing radiation, with signal that is less readily quantifiable as macroscopic density.

RELATING STRUCTURE AND FUNCTION TO CLINICAL PARAMETERS Airway remodeling is a term used to describe increased airway WT in asthmatic patients. This condition encompasses a range of processes, including mucous gland hyperplasia, smooth muscle hypertrophy, inflammatory cell infiltration, and collagen deposition.73 CT has been used to evaluate the extent of airway wall thickening.74,75 WA% and WT percentage (WT%) measured by

using CT were increased in patients with severe asthma and correlated with airway epithelial thickness on endobronchial biopsy specimens. Not only did airway measurements correlate with pathology, clinical correlations were apparent as well. Patients with increased WA% and WT% had lower FEV1 and greater bronchodilator response.17 A separate study found a significant correlation between WA and asthma control scores for all bronchi and WA/BSA in the subsegmental bronchi only.76 These imaging characteristics can help characterize asthmatic phenotypes and differentiate between severe and nonsevere disease because those with severe disease exhibited increased airway remodeling.

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FIG 6. EBUS of the bronchial wall from an equine asthma model (A) and corresponding histologic (B) images. Only a portion of the second-layer (L2) area and corresponding smooth muscle area have been encircled in yellow to allow the reader to appreciate the rest of the image. D1 and D2, Perpendicular diameters (blue dotted lines); LA, lumen area (filled light green area); L1-5, ultrasound layers 1 to 5; Pi, airway perimeter (continuous green line). Modified from Bullone et al.38 Ó 2015 Bullone et al.

Further evaluation of differences in airway remodeling among severe asthma cluster subphenotypes was undertaken by Gupta et al.3 Unbiased phenotyping of patients with severe asthma was completed by using a cluster analysis, as previously described,77 and showed 4 distinct phenotypes. When compared with the healthy control group, all 4 phenotypes exhibited a decrease in lumen area and an increase in WA%. Although there was no significant difference between the subphenotypes, those patients with severe asthma and persistent airflow obstruction had a significantly increased WA% when compared with those without fixed obstruction. Another key finding was that WA% was increased in patients with persistent neutrophilic inflammation measured by using repeat sputum evaluation. Neutrophilic inflammation has also been associated with the air-trapping phenotype. Patients with air trapping were significantly more likely to have asthma-related hospitalizations, intensive care unit admissions, and greater airflow limitations compared with those without air trapping.4 This suggests that air trapping quantified by using CT might identify a unique and more severe phenotype of asthma. A novel cluster method was recently implemented to identify CT-determined phenotypes.5 Three unique clusters were described by using CT measures of air trapping and proximal airway remodeling. All clusters demonstrated air trapping, but clusters 1 and 3 had more significant air trapping and worse lung function than cluster 2. Cluster 1 patients had increased lumen and wall measurements, cluster 2 patients did not have proximal airway remodeling, and cluster 3 patients had luminal narrowing. Imaging characteristics can be incorporated in future cluster analyses to better understand specific asthma phenotypes. In a series of articles, Choi et al78,79 have demonstrated the use of a combination of metrics, including lung shape, hydraulic diameter of the airway segments, airway cross-sectional shape, airway branch angles, lung densities, and more, to improve the ability of quantitative CT to differentiate between nonasthmatic subjects,

FIG 7. Lung MRI demonstrates ventilation maps based on the distribution of hyperpolarized Xe gas assessed by using magnetic resonance images of a healthy subject (A) and an asthmatic patient (B), respectively. Note the patchy regions of poor to no ventilation in patients with severe asthma.

patients with nonsevere asthma, and patients with severe asthma. These growing sets of metrics are being used to advance the concept of identifying clusters serving to differentiate asthmatic

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FIG 8. ADC map of a healthy nonsmoker (A), a patient with Global Initiative for Chronic Obstructive Lung Disease stage 2 chronic obstructive pulmonary disease (COPD; B), and a patient with severe asthma (C). The color scale on the right represents diffusion coefficients in square centimeters per second, with blue representing low ADC values and yellow representing higher ADC values. Notice the regions of higher ADC values in the patient with COPD corresponding to areas of alveolar destruction. Image courtesy of James Quirk, PhD, Washington University in St Louis.

patients into subgroups with the hopes of improving the discovery of more targeted interventions. Currently, serum total IgE and blood eosinophil measurements are examples of biomarkers being used to characterize specific asthmatic phenotypes to determine the appropriate patient for specific treatments. These markers are not used to monitor response to treatment with immunomodulatory and biological therapies. Airway imaging is an emerging biomarker, but standardization is required.6 While awaiting further validation studies, it is important to note that there is some current evidence to support the use of imaging for assessing and predicting response to specific treatments.

IMAGING AS A BIOMARKER The effect of inhaled corticosteroid use on air trapping in patients with mild-to-moderate asthma with uncontrolled symptoms has been assessed by using CT. After completing 3 months of therapy with an inhaled corticosteroid, patients exhibited a decrease in air trapping, as measured by using CT.80 Thus air trapping can serve as a potential outcome related to disease control. Recently, biologic therapy with anti–IL-5 mAb has shown promise to reverse the airway remodeling process. In 26 patients with severe refractory asthma with sputum eosinophilia, Haldar et al81 demonstrated that treatment with mepolizumab (an anti–IL-5 mAb) significantly decreased average WA over 1 year compared with placebo. Current analytic tools allow for measurement of the ventilation defect percentage from 129Xe and 3He MRI, which is the volume of lung not involved in ventilation. Texture features can also be generated from MRI ventilation images and can be used to quantify differences in lung ventilation after bronchodilator therapy.82 Further studies are needed to evaluate the optimal imaging biomarker to assess response to biologic therapy in asthmatic patients. A combination of 2 imaging modalities can be used to assess response and guide therapy. Regional lung ventilation has been quantified in patients with severe asthma by using multidetector CT and 3He MRI.7 A majority of the patients with severe asthma underwent bronchial thermoplasty and had repeat 3He MRI. Comparisons were made between the pretreatment and posttreatment images in relation to segmental defect percentages and whole-lung defect percentages. Although ventilation defects increased immediately after bronchial thermoplasty, the ventilation defects decreased after a longer period of observation. This information can be used to potentially guide bronchial

thermoplasty and can be used to target specific segments, potentially decreasing the number of treatment sessions or the number of segments needing treatment.

CONCLUSION Current use of chest CT in asthmatic patients has been used to identify alternative diagnosis or complicating conditions that might be contributing to uncontrolled disease. Recent studies have now demonstrated that quantitative CT of the chest and hyperpolarized gas MRI can be used as a biomarker of airway remodeling. Prospective longitudinal trials of targeted biologics (anti-IgE, IL-5, IL-4a, and IL-13) and nonpharmacologic (bronchial thermoplasty) treatments using these quantitative imaging biomarkers are needed to assess whether these treatments are modifying the course of this disease. If these disease-modifying effects of treatment can be demonstrated, then perhaps they can be introduced earlier in the disease process. What do we know? d Several imaging modalities are clinically available for use in evaluation of asthmatic patients. d

CT, MRI, and PET are among the modalities that can provide detailed assessment of lung structure and function.

d

Measurements from imaging, such as WT, air trapping, and ventilation defects, can serve as biomarkers and be used to assess response to new therapies.

What is still unknown? d Prospective trials of biologic agents and bronchial thermoplasty using imaging end points are necessary to determine whether these therapies are truly disease-modifying agents. d

Further studies are needed to determine the optimal biomarker to assess response to therapies.

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