Mast cell localization within the airway smooth muscle (ASM)-bundle plays an important role in the development of airway hyper-responsiveness (AHR). Genomewide association studies implicate the ‘alarmin’ IL-33 in asthma, but its role in mast cell–ASM interactions is unknown.
We examined the expression and functional role of IL-33 in bronchial biopsies of patients with and without asthma, ex vivo ASM, mast cells, cocultured cells and in a mouse model system.
Recently, dynamic MRI of hyperpolarized 3He during inhalation revealed an alternation of the image intensity between left and right lungs with a cardiac origin (Sun Y, Butler JP, Ferrigno M, Albert MS, Loring SH. Respir Physiol Neurobiol 185: 468–471, 2013). This effect is investigated further using dynamic and phase-contrast flow MRI with inhaled 3He during slow inhalations (flow rate ∼100 ml/s) to elucidate airflow dynamics in the main lobes in six healthy subjects. The ventilation MR signal and gas inflow in the left lower lobe (LLL) of the lungs were found to oscillate clearly at the cardiac frequency in all subjects, whereas the MR signals in the other parts of the lungs had a similar oscillatory behavior but were smaller in magnitude and in anti-phase to the signal in the left lower lung. The airflow in the main bronchi showed periodic oscillations at the frequency of the cardiac cycle. In four of the subjects, backflows were observed for a short period of time of the cardiac cycle, demonstrating a pendelluft effect at the carina bifurcation between the left and right lungs. Additional 1H structural MR images of the lung volume and synchronised ECG recording revealed that maximum inspiratory flow rates in the LLL of the lungs occurred during systole when the corresponding left lung volume increased, whereas the opposite effect was observed during diastole, with gas flow redirected to the other parts of the lung. In conclusion, cardiogenic flow oscillations have a significant effect on regional gas flow and distribution within the lungs.
Lung clearance index (LCI) is a measure of abnormal ventilation distribution derived from the multiple breath inert gas washout (MBW) technique. We aimed to determine the clinical utility of LCI in non-CF bronchiectasis, and to assess two novel MBW parameters that distinguish between increases in LCI due to specific ventilation inequality (LCIvent) and increased respiratory dead space (LCIds).
Purpose - To compare quantitative fractional ventilation measurements from multiple breath washout imaging (MBW-I) using hyperpolarized 3 He with both spoiled gradient echo (SPGR) and balanced steady-state free precession (bSSFP) three-dimensional (3D) pulse sequences and to evaluate the feasibility of MBW-I with hyperpolarized 129 Xe.
Bronchial epithelial ciliary dysfunction is an important feature of asthma. We sought to determine the role in asthma of neutrophilic inflammation and nicotinamide adenine dinucleotide phosphate (NADPH) oxidases in ciliary dysfunction.
There is evidence supporting a role for the nociceptin/orphanin FQ (N/OFQ; NOP) receptor and its endogenous ligand N/OFQ in the modulation of neurogenic inflammation, airway tone and calibre. We hypothesized that NOP receptor activation has beneficial effects upon asthma immunopathology and airway hyperresponsiveness. Therefore, the expression and function of N/OFQ and the NOP receptor were examined in healthy and asthmatic human airway tissues. The concept was further addressed in an animal model of allergic asthma.
Currently, imaging in asthma is confined to chest radiography and CT. The emergence of new imaging techniques and tremendous improvement of existing imaging methods, primarily due to technological advancement, has completely changed its research and clinical prospects. In research, imaging in asthma is now being employed to provide quantitative assessment of morphology, function and pathogenic processes at the molecular level. The unique ability of imaging for non-invasive, repeated, quantitative, and in vivo assessment of structure and function in asthma could lead to identification of ‘imaging biomarkers’ with potential as outcome measures in future clinical trials. Emerging imaging techniques and their utility in the research and clinical setting is discussed in this review.
Knowledge of airflow patterns in the large airways is of interest for the understanding of obstructive airways diseases and for the development and delivery of inhaled respiratory therapies. For this purpose, computational fluids dynamics (CFD) simulations are often used to model and predict airflow in compliant lung models (1–3). However, CFD needs experimental validation. In vitro measurement of flow patterns has been performed in anatomical lung models with particle image velocimetry (4–6), laser Doppler velocimetry (7) or phase contrast velocimetry (PCV) MRI with hyperpolarized (HP) 3He (8,9).
To quantify lung ventilation response to bronchodilator in patients with asthma on a global and regional basis
Asthma is a heterogeneous condition and approximately 5-10% of asthmatic subjects have severe disease associated with structure changes of the airways (airway remodeling) that may develop over time or shortly after onset of disease. Quantitative computed tomography (QCT) imaging of the tracheobronchial tree and lung parenchyma has improved during the last 10 years, and has enabled investigators to study the large airway architecture in detail and assess indirectly the small airway structure. In severe asthmatics, morphologic changes in large airways, quantitatively assessed using 2D-3D airway registration and recent algorithms, are characterized by airway wall thickening, luminal narrowing and bronchial stenoses. Extent of expiratory gas trapping, quantitatively assessed using lung densitometry, may be used to assess indirectly small airway remodeling. Investigators have used these quantitative imaging techniques in order to attempt severity grading of asthma, and to identify clusters of asthmatic patients that differ in morphologic and functional characteristics. Although standardization of image analysis procedures needs to be improved, the identification of remodeling pattern in various phenotypes of severe asthma and the ability to relate airway structures to important clinical outcomes should help target treatment more effectively.
Modern medicine therapies tend to generate and rely on an immense amount of data that are usually produced by CT, MRI and other imaging techniques as well as genetic data coming from NGS sequencing. In order to plan a patientspecific therapy these data need to be efficiently analyzed and interpreted per individual subject. The EU-founded AirPROM project (Airway Disease Predicting Outcomes through Patient Specific Computational Modeling) is a prime example of joint cooperation that aims to develop tools to predict the progression of selected diseases and response to treatment in the area of respiratory medicine. This would not be possible without support of computer science methods. In particular, a lot of effort has been spent to integrate different software tools and present them to specialists in a form of one unified system that may be used without in depth ICT knowledge. This paper presents selected tools and techniques used to achieve this goal.
The multiple-breath inert gas washout parameter acinar ventilation heterogeneity (Sacin) is thought to be a marker of acinar airway involvement but has not been validated by using quantitative imaging techniques in asthmatic patients. We aimed to use hyperpolarized 3He diffusion magnetic resonance at multiple diffusion timescales and quantitative computed tomographic (CT) densitometry to determine the nature of acinar airway involvement in asthmatic patients.
The objective of this work is to provide a robust segmentation approach of the pulmonary field, with individualized labeling of the lungs, able to overcome the mentioned limitations. The proposed approach relies on 3-D mathematical morphology and exploits the concept of controlled relief flooding (to identify contrasted lung areas) together with patient-specific shape properties for peripheral dense tissue detection. Tested on a database of 40 MSCT of pathological lungs, the proposed approach showed correct identification of lung areas with high sensitivity and specificity in locating peripheral dense opacities.
