Using imaging as a biomarker for asthma

Abstract

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.

Keywords: Imaging; MRI; PET; biomarker; chest CT.

Figure 1. CT chest lung density

Panel A demonstrates a 3D volume rendition of the lung, lobes and bronchial tree detected from a CT image of the fully inflated (total lung capacity) lung of a normal subject. Panel B. CT chest shows a similar volume rendition using the expiratory image (in this case, functional residual capacity) of a subject with severe asthma. Note areas of air trapping and pruning of the airways. Image processing derived from Apollo software (VIDA Diagnostics, Coralville, IA).

Figure 2. CT chest 3D bronchial tree

Figure demonstrates labeling of the bronchial tree out to the segmental bronchi of a subject with severe asthma enabling each segmental bronchial wall thickness to be measured quantitatively. Image processing derived from Apollo software (VIDA Diagnostics, Coralville, IA).

Figure 3. CT chest air trapping distribution

Figure demonstrates the concentration of regions determined to represent air trapping (voxels <−856) on the expiratory CT image of the same subject with severe asthma in Figure 1B. Trapped air, defined as voxels within the lung field falling below −856 HU, are demonstrated by sphericals proportional to area of air trapping (volume rendered view). Each lobe is color-coded.

Figure 4. MDCT chest image matching

Parametric response mapping (PRM) (76) and disease probability mapping (DPM) [77-78]) 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/hyper-inflated can be assigned. Panel A maps voxels from TLC (y axis) and FRC (x axis) in terms of their probability of a being hyper-inflated vs. ventilated in a plot from a severe asthmatic; a normal subject is shown in the insert (upper left). The green represents the normal end of the scale, yellow represents the probability of being air trapped (poorly ventilated) and red represents hyper-inflation. Because the image is a probability map, the colors are shown blended. Panel B serves to quantitate clusters of air trapped vs. normal lung tissue as a function of lung location.

Figure 5. Optical Coherence Tomography

Optical coherence tomography (OCT) images (A) and mean ± standard deviation airway measurements (B) prior to bronchial thermoplasty (BT), 6 months post-BT and 2 years post-BT, with C) the corresponding bronchial biopsy at 6 months post-BT. Epi: epithelium; BM: basement membrane; SM: smooth muscle: WA: airway wall. Scale bars=1 mm. Modified with permission from [82].

Figure 6. Endobronchial Ultrasound

Endobronchial ultrasound (EBUS) of bronchial wall from equine asthma model (A) and corresponding histological (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 appreciate the rest of the image. L1-5: ultrasound layers 1-5; D1 and D2: perpendicular diameters (blue dotted lines); LA: lumen area (filled light green area); Pi: airway perimeter (continuous green line). Modified from [83]. © 2015 Bullone et al.

Figure 7. Magnetic Resonance Imaging

MRI lung demonstrate ventilation maps based upon the distribution of hyperpolarized Xe gas assessed via MRI of a normal (A) and an asthmatic subject (B) respectively. Note the patchy regions of poor to no ventilation in subject with severe asthma.

Figure 8. Apparent Diffusion Coefficient

Apparent Diffusion Coefficient (ADC) map of healthy non-smoker (A), Chronic Obstructive Pulmonary Disease (COPD) gold stage 2 (B), and severe asthmatic (C). The color scale on the right represents diffusion coefficients in cm2/sec with blue representing low ADC values and yellow representing higher ADC values. Notice the regions of higher ADC values in the COPD patient corresponding to areas of alveoli destruction. Image courtesy of James Quirk, PhD, Washington University in St. Louis