Airway Structure Research Articles

Studies on the role of non-coding RNAs in controlling the activity of T cells in asthma.

Bronchial asthma, commonly known as asthma, is a chronic inflammatory disease characterized by airway inflammation, increased responsiveness and changes in airway structure. T cells, particularly T helper cells, play a crucial role in the disease. Non-coding RNAs, which are RNAs that do not code for proteins, mainly include microRNAs, long non-coding RNAs, and circular RNAs, play a role in regulating various biological processes. Studies have shown that non-coding RNAs have an important role in the activation and transformation of T cells and other biological processes in asthma. The specific mechanisms and clinical applications are worth further examination. This article reviews the recent research on the role of microRNAs, long non-coding RNAs and circular RNAs in T cells in asthma.

The role of video-fluoroscopy in the assessment of obstructive sleep apnea patients: comparative study

BackgroundPre-operative imaging tools play a crucial role in the anatomic assessment of the upper airway and adjacent structures in obstructive sleep apnea patients. The current study was aimed at comparing and correlating the results of videofluoroscopy in evaluating upper airway obstruction in surgically fit obstructive sleep apnea “OSA” patients with fiberoptic nasoendoscopic examination during the awake “Muller’s maneuver” and during sleep induced with propofol for better selection of the suitable surgical maneuver. The present study was an observational cross-sectional study of 69 surgically fit OSA patients (36 males and 33 females); their ages ranged between 29 and 65 years with mean age of 45.87 ± 9.68 years. The patients were selected from otorhinolaryngology, phoniatric, and pulmonology outpatient clinics during the period from February 2019 to January 2020.ResultsThe present study demonstrated that no statistically significant difference was found between the three techniques (video-fluoroscopy, awake fiber-optic nasoendoscopy, and drug-induced sleep nasoendoscopy “DISE”) as regards the shape of upper airway collapse at retropalatal, retroglossal, and hypopharyngeal levels in OSA patient (P: 0.621, 0.669, and 1.0 respectively). Statistically, a significant difference was observed between video-fluoroscopy, awake fiber-optic nasoendoscopy on one hand, and DISE on the other one regarding the grade of upper airway collapse at all levels (P: 0.006, 0.037, and 0.003). It was a mild significant difference in favor of DISE.ConclusionVideo-fluoroscopy is a good, reliable complementary preoperative assessment tool to identify obstruction patterns of the upper airway in OSA patients with quantitative measurements.

CT airway remodelling and chronic cough

RationaleStructural airway changes related to chronic cough (CC) are described in the literature, but so far reported data are rare and non-conclusive. Furthermore, they derive mainly from cohorts with small...

Pulmonary sleeve resection complications and management.

In tumors involving the central airway or vascular structures, achieving local control and preserving pulmonary function can be possible with a pulmonary sleeve resection. In this section, complications and management of pulmonary sleeve resections are discussed.

Development and Application of a Virtual Imaging Trial framework for Airway Quantifications via CT.

Chronic obstructive pulmonary disease (COPD) is one of the top three causes of death worldwide, characterized by emphysema and bronchitis. Airway measurements reflect the severity of bronchitis and other airway-related diseases. Airway structures can be objectively evaluated with quantitative computed tomography (CT). The accuracy of such quantifications is limited by the spatial resolution and image noise characteristics of the imaging system and can be potentially improved with the emerging photon-counting CT (PCCT) technology. This study evaluated the quantitative performance of PCCT against energy-integrating CT (EICT) systems for airway measurements, and further identified optimum CT imaging parameters for such quantifications. The study was performed using a novel virtual imaging framework by developing the first library of virtual patients with bronchitis. These virtual patients were developed based on CT images of confirmed COPD patients with varied bronchitis severity. The human models were virtually imaged at 6.3 and 12.6 mGy dose levels using a scanner-specific simulator (DukeSim), synthesizing clinical PCCT and EICT scanners (NAEOTOM Alpha, FLASH, Siemens). The projections were reconstructed with two algorithms and kernels at different matrix sizes and slice thicknesses. The CT images were used to quantify clinically relevant airway measurements ("Pi10" and "WA%") and compared against their ground truth values. Compared to EICT, PCCT provided more accurate Pi10 and WA% measurements by 63.1% and 68.2%, respectively. For both technologies, sharper kernels and larger matrix sizes led to more reliable bronchitis quantifications. This study highlights the potential advantages of PCCT against EICT in characterizing bronchitis utilizing a virtual imaging platform.

A Deep Attention-based U-Net for Airways Segmentation in Computed Tomography Images.

Airway segmentation is a way to quantify the diagnosis of pulmonary diseases, including chronic obstructive problems and bronchiectasis. Manual analysis by radiologists is a challenging task due to the complex airway structure. Additionally, tree-like patterns, varied shapes, sizes, and intensity make the manual airway segmentation task more complex. Deeper airways are even more difficult to segment as their intensity starts matching the lung parenchyma as the diameter of the airway cross-section gets reduced. Many earlier works have proposed different deep learning networks for airway segmentation but were unable to achieve the desired performance; hence the task of airway segmentation still possesses challenges in this field. This work proposes a convolutional neural network based on deep U-Net architecture and employs an attention block technique for airway segmentation. The attention mechanism aids in the extraction of the complicated and multi-sized airways found in the lung region, hence increasing the efficiency of the U-Net architecture. The model has been validated using VESSEL12 and EXACT09 datasets, individually and combined, with and without trachea images. The best DSC scores on EXACT09 and VESSEL12 datasets are 95.21% and 95.80%, respectively. The performance on both datasets combined gave a DSC score of 94.1%, showing that the overall performance of the proposed methodology is quite satisfactory. The generalizability of the model is also confirmed using k-fold cross-validation. The comparison of the proposed model to existing research on airway segmentation found competitive results. The use of an attention unit in the proposed model highlights the relevant information and reduces the irrelevant features, which helps to improve the performance and saves time.

A single-tube-braided stent for various airway structures.

Background: Airway stent has been widely used in airway procedures. However, the metallic and silicone tubular stents are not customized designed for individual patients and cannot adapt to complicated obstruction structures. Other customized stents could not adapt to complex airway structures with easy and standardized manufacturing methods. Object: This study aimed to design a series of novel stents with different shapes which can adapt to various airway structures, such as the "Y" shape structure at the tracheal carina, and to propose a standardized fabrication method to manufacture these customized stents in the same way. Methods: We proposed a design strategy for the stents with different shapes and introduced a braiding method to prototype six types of single-tube-braided stents. Theoretical model was established to investigate the radial stiffness of the stents and deformation upon compression. We also characterized their mechanical properties by conducting compression tests and water tank tests. Finally, a series of benchtop experiments and ex vivo experiments were conducted to evaluate the functions of the stents. Results: The theoretical model predicted similar results to the experimental results, and the proposed stents could bear a compression force of 5.79N. The results of water tank tests showed the stent was still functioning even if suffering from continuous water pressure at body temperature for a period of 30days. The phantoms and ex-vivo experiments demonstrated that the proposed stents adapt well to different airway structures. Conclusion: Our study offers a new perspective on the design of customized, adaptive, and easy-to-fabricate stents for airway stents which could meet the requirements of various airway illnesses.

A novel 3D-printed laryngoscope with integrated working channels for laryngeal surgery.

For the surgical treatment of early-stage laryngeal cancer, the use of transoral laser microsurgery (TLM) has emerged as the gold standard. However, this procedure requires a straight line of sight to the operating field. Therefore, the patient's neck needs to be brought into a hyperextended position. In a considerable number of patients, this is not possible due to anomalies in the cervical spine anatomy or soft tissue scarring, e.g., after radiation. In these cases, adequate visualization of relevant laryngeal structures cannot be ensured using a conventional rigid operating laryngoscope, which may negatively affect the outcome of these patients. We present a system based on a 3D-printed prototype of a curved laryngoscope with three integrated working channels (sMAC). The curved profile of the sMAC-laryngoscope is specifically adapted to the nonlinear anatomy of the upper airway structures. The central working channel provides access for flexible video endoscope imaging of the operating field while the two remaining channels provide access for flexible instrumentation. In a user study (n = 11), visualization and reachability of relevant laryngeal landmarks as well as the feasibility of basic surgical procedures with the proposed system were examined in a patient simulator. In a second setup, the system was evaluated for its applicability in a human body donor. All participants of the user study were able to visualize, reach and manipulate the relevant laryngeal landmarks. Reaching those took significantly less time in the second attempt compared to the first one (27.5 s ± 5.2 s vs. 39.7 s ± 16.5 s, p = 0.008) indicating a significant learning curve for handling the system. Instrument changes were performed quickly and reliably by all participants (10.9 s ± 1.7 s). All participants were able to bring the bimanual instruments into position for a vocal fold incision. Relevant laryngeal landmarks could be visualized and reached in the human body donor setup. Possibly, the proposed system may develop into an alternative treatment option for patients with early-stage laryngeal cancer and restricted mobility of the cervical spine in the future. Further improvements of the system could include finer end effectors and a flexible instrument with a laser cutting tool.

Transport and deposition of beclomethasone dipropionate drug aerosols with varying ethanol concentration in severe asthmatic subjects

This study aims to assess the effects of varying an ethanol co-solvent on the deposition of drug particles in severe asthmatic subjects with distinct airway structures and lung functions using computational fluid dynamics. The subjects were selected from two quantitative computed tomography imaging-based severe asthmatic clusters, differentiated by airway constriction in the left lower lobe. Drug aerosols were assumed to be generated from a pressurized metered-dose inhaler (MDI). The aerosolized droplet sizes were varied by increasing the ethanol co-solvent concentration in the MDI solution. The MDI formulation consists of 1,1,2,2-tetrafluoroethane (HFA-134a), ethanol, and beclomethasone dipropionate (BDP) as the active pharmaceutical ingredient. Since HFA-134a and ethanol are volatile, both substances evaporate rapidly under ambient conditions and trigger condensation of water vapor, increasing the size of aerosols that are predominantly composed of water and BDP. The average deposition fraction in intra-thoracic airways for severe asthmatic subjects with (or without) airway constriction increased from 37%±12 to 53.2%±9.4 (or from 20.7%± 4.6 to 34.7%±6.6) when the ethanol concentration was increased from 1 to 10%wt/wt. However, when the ethanol concentration was further increased from 10 to 20%wt/wt, the deposition fraction decreased. This indicates the importance of selecting appropriate co-solvent amounts during drug formulation development for the treatment of patients with narrowed airway disease. For severe asthmatic subjects with airway narrowing, the inhaled aerosol may benefit from a low hygroscopic effect by reducing ethanol concentration to penetrate the peripheral region effectively. These results could potentially inform the selection of co-solvent amounts for inhalation therapies in a cluster-specific manner.

Pathophysiology, Therapeutic Targets, and Future Therapeutic Alternatives in COPD: Focus on the Importance of the Cholinergic System

Chronic obstructive pulmonary disease (COPD) is a progressive disease characterized by airway limitation and changes in airway structure. It has a high global burden of mortality and morbidity. The etiology of COPD is complex, but exposure to tobacco smoke and other inhaled lung oxidants are major risk factors. Both pharmacological and non-pharmacological approaches are used to manage COPD, but there remains an urgent unmet need for drugs that can modify the course of the disease. This review focuses on the role of acetylcholine and other components of the pulmonary cholinergic system in the pathogenesis of COPD, and the inhaled pharmacological agents that target it. In addition to its role as a neurotransmitter, acetylcholine regulates diverse aspects of COPD pathogenesis including bronchoconstriction, airway remodeling, mucus secretion and inflammation. Inhaled antimuscarinic drugs are a key component of therapy for COPD, as monotherapy or in combination with inhaled β2 agonists or corticosteroids. We review the evidence supporting the use of current anticholinergic agents in COPD and preview novel drugs targeting the cholinergic system and agents from other classes in clinical development, such as phosphodiesterase-4 inhibitors and monoclonal antibodies targeting inflammatory mediators.

Comparison of Rigid and Articulating Video Stylets During Simulated Endotracheal Intubation With Hyperangulated Video Laryngoscopy

BackgroundEndotracheal tube delivery through the vocal cords can be challenging with hyperangulated video laryngoscopy due to the acute angle around the tongue and surrounding airway structures. Articulating video stylets may mitigate this issue by equipping an endotracheal tube stylet with an operator-controlled articulating end that has an additional camera at the tip. ObjectivesWe compared operator-reported ease of intubation between the traditional rigid stylet (GlideRiteⓇ Rigid Stylet, Verathon Inc., Bothell, WA) and the articulating video stylet (ProVu™ Video Stylet, Flexicare Inc., Irvine, CA) with a hyperangulated video laryngoscope (GlideScopeⓇ, Verathon Inc., Bothell, WA). MethodsParticipants performed simulated intubation using a hyperangulated video laryngoscope with both stylets in random order. We compared operator-reported ease of intubation on a 0–100 visual analogue scale (VAS), best percentage of glottic opening (POGO), and time to intubation. We compared outcomes using a paired t-test or the asymptotic Wilcoxon-Pratt signed-rank test dependent on normality. ResultsWe enrolled a convenience sample of 16 emergency department attendings, residents, and physician assistant postgraduate trainees. The median operator-reported ease of intubation on VAS was 20 (interquartile range 9, 30) for the rigid stylet and 20 (10, 30) for the articulating video stylet (p = 0.832). However, the rigid stylet had a slightly shorter mean time to intubation compared with the articulating video stylet, 6.9 (standard deviation 2.5) vs. 10.3 (4.1) s, respectively (p = 0.017). POGO was similar between groups. ConclusionsDuring simulated endotracheal intubation, the rigid and articulating video stylets had similar operator-reported ease of intubation.

Propagation of Interactions among Aircraft Trajectories: A Complex Network Approach

Interactions between aircraft, as, e.g., those caused by minimum separation infringements, can trigger non-local cascades of interactions that can propagate over large temporal and spatial scales. Assessing those downstream effects is a computationally complex problem, which has only been tackled over rather limited time horizons. We here propose a methodology to map these interactions into networks, thus representing their potential propagation and the structure induced by them. The result is a conceptually simple and computationally tractable representation, which can be further analyzed using metrics provided by a complex networks theory. We firstly test this methodology using a synthetic airspace, then move on to the analysis of planned and executed trajectories for a large European airspace in the year 2018. We show how these propagation networks reflect the structure of airways, the intervention of air traffic controllers, and how they have evolved through time. We finally discuss potential real-world applications, and some key aspects that need to be further studied to make this a viable instrument in an operational context.

Advances in animal models of obstructive sleep apnea.

Animal experiments play an important role in the study of the pathogenesis of human diseases and new methods of diagnosis and treatment. Due to the great differences in the anatomical structure and physiology of the upper airway between animals and humans, there is currently no animal model that can fully simulate the pathological anatomy and pathophysiological characteristics of human obstructive sleep apnea (OSA) patients. Herein, we summarizes the construction methods of several OSA animal models that have been widely used in the studies published in the last 5 years, the advantages and limitations of each model as well as related evaluation techniques are described. This information has potential to provide further guide for the development of OSA related animal experiments.

Predicting severe chronic obstructive pulmonary disease exacerbations using quantitative CT: a retrospective model development and external validation study

Quantitative CT is becoming increasingly common for the characterisation of lung disease; however, its added potential as a clinical tool for predicting severe exacerbations remains understudied. We aimed to develop and validate quantitative CT-based models for predicting severe chronic obstructive pulmonary disease (COPD) exacerbations. We analysed the Subpopulations and Intermediate Outcome Measures In COPD Study (SPIROMICS) cohort, a multicentre study done at 12 clinical sites across the USA, of individuals aged 40-80 years from four strata: individuals who never smoked, individuals who smoked but had normal spirometry, individuals who smoked and had mild to moderate COPD, and individuals who smoked and had severe COPD. We used 3-year follow-up data to develop logistic regression classifiers for predicting severe exacerbations. Predictors included age, sex, race, BMI, pulmonary function, exacerbation history, smoking status, respiratory quality of life, and CT-based measures of density gradient texture and airway structure. We externally validated our models in a subset from the Genetic Epidemiology of COPD (COPDGene) cohort. Discriminative model performance was assessed using the area under the receiver operating characteristic curve (AUC), which was also compared with other predictors, including exacerbation history and the BMI, airflow obstruction, dyspnoea, and exercise capacity (BODE) index. We evaluated model calibration using calibration plots and Brier scores. Participants in SPIROMICS were enrolled between Nov 12, 2010, and July 31, 2015. Participants in COPDGene were enrolled between Jan 10, 2008, and April 15, 2011. We included 1956 participants from the SPIROMICS cohort who had complete 3-year follow-up data: the mean age of the cohort was 63·1 years (SD 9·2) and 1017 (52%) were men and 939 (48%) were women. Among the 1956 participants, 434 (22%) had a history of at least one severe exacerbation. For the CT-based models, the AUC was 0·854 (95% CI 0·852-0·855) for at least one severe exacerbation within 3 years and 0·931 (0·930-0·933) for consistent exacerbations (defined as ≥1 acute episode in each of the 3 years). Models were well calibrated with low Brier scores (0·121 for at least one severe exacerbation; 0·039 for consistent exacerbations). For the prediction of at least one severe event during 3-year follow-up, AUCs were significantly higher with CT biomarkers (0·854 [0·852-0·855]) than exacerbation history (0·823 [0·822-0·825]) and BODE index 0·812 [0·811-0·814]). 6965 participants were included in the external validation cohort, with a mean age of 60·5 years (SD 8·9). In this cohort, AUC for at least one severe exacerbation was 0·768 (0·767-0·769; Brier score 0·088). CT-based prediction models can be used for identification of patients with COPD who are at high risk of severe exacerbations. The newly identified CT biomarkers could potentially enable investigation into underlying disease mechanisms responsible for exacerbations. National Institutes of Health and the National Heart, Lung, and Blood Institute.

Deep Learning-Based Segmentation of Airway Morphology from Endobronchial Optical Coherence Tomography

Background: Manual measurement of endobronchial optical coherence tomography (EB-OCT) images means a heavy workload in the clinical practice, which can also introduce bias if the subjective opinions of doctors are involved. Objective: We aim to develop a convolutional neural network (CNN)-based EB-OCT image analysis algorithm to automatically identify and measure EB-OCT parameters of airway morphology. Methods: The ResUNet, MultiResUNet, and Siamese network were used for analyzing airway inner area (Ai), airway wall area (Aw), airway wall area percentage (Aw%), and airway bifurcate segmentation obtained from EB-OCT imaging, respectively. The accuracy of the automatic segmentations was verified by comparing with manual measurements. Results: Thirty-three patients who were diagnosed with asthma (n = 13), chronic obstructive pulmonary disease (COPD, n = 13), and normal airway (n = 7) were enrolled. EB-OCT was performed in RB9 segment (lateral basal segment of the right lower lobe), and a total of 17,820 OCT images were collected for CNN training, validation, and testing. After training, the Ai, Aw, and airway bifurcate were readily identified in both normal airway and airways of asthma and COPD. The ResUNet and the MultiResUNet resulted in a mean dice similarity coefficient of 0.97 and 0.95 for Ai and Aw segmentation. The accuracy Siamese network in identifying airway bifurcate was 96.6%. Bland-Altman analysis indicated there was a negligible bias between manual and CNN measurements for Ai (bias = −0.02 to 0.01, 95% CI = −0.12 to 0.14) and Aw% (bias = −0.06 to 0.12, 95% CI = −1.98 to 2.14). Conclusion: EB-OCT imaging in conjunction with ResUNet, MultiResUNet, and Siamese network could automatically measure normal and diseased airway structure with an accurate performance.

Advances and Highlights of miRNAs in Asthma: Biomarkers for Diagnosis and Treatment.

Asthma is a heterogeneous inflammatory disease of the airways that causes breathing difficulties, episodes of cough and wheezing, and in more severe cases can greatly diminish quality of life. Epigenetic regulation, including post-transcriptional mediation of microRNAs (miRNAs), is one of the mechanisms behind the development of the range of asthma phenotypes and endotypes. As in every other immune-mediated disease, miRNAs regulate the behavior of cells that shape the airway structure as well as those in charge of the defense mechanisms in the bronchi and lungs, controlling cell survival, growth, proliferation, and the ability of cells to synthesize and secrete chemokines and immune mediators. More importantly, miRNAs are molecules with chemical and biological properties that make them appropriate biomarkers for disease, enabling stratification of patients for optimal drug selection and thereby simplifying clinical management and reducing both the economic burden and need for critical care associated with the disease. In this review, we summarize the roles of miRNAs in asthma and describe how they regulate the mechanisms of the disease. We further describe the current state of miRNAs as biomarkers for asthma phenotyping, endotyping, and treatment selection.

Con: Limitations of POCUS Examination: Be Aware of Overdiagnosis and Undertreatment

ULTRASOUND IS A REVOLUTIONARY, noninvasive imaging tool that, when used and interpreted by trained personnel in the proper clinical situation, can provide correct diagnosis and treatment. Point-of-care ultrasound (POCUS) is defined as a handheld, mobile, broadly applied ultrasound machine capable of performing limited studies at bedside to provide answers to focused, closed-ended, binary questions. 1 Baribeau Y Sharkey A Chaudhary O et al. Handheld point-of-care ultrasound probes: The New generation of POCUS. J Cardiothorac Vasc Anesth. 2020; 34: 3139-3145 Abstract Full Text Full Text PDF PubMed Scopus (41) Google Scholar , 2 Reisinger NC Koratala A. Incorporating training in POCUS in nephrology fellowship curriculum. Clin J Am Soc Nephrol. 2022; 17: 1442-1445 Crossref PubMed Scopus (0) Google Scholar Over the last 15 years, the medical literature has demonstrated the importance of this tool in medical practice, 3 Miller DL Abo A Abramowicz JS et al. Diagnostic ultrasound safety review for point-of-care ultrasound practitioners. J Ultrasound Med. 2020; 39: 1069-1084 Crossref PubMed Scopus (17) Google Scholar with applications including delineation of airway structures, lung pathology, cardiac structure and function, gastric volume and content, guided vascular procedures, and emergent focused assessment with sonography for trauma examination. 4 Kalagara H Coker B Gersterin NS et al. Point-of-care ultrasound (POCUS) for the cardiothoracic anesthesiologist. J Cardiothorac Vasc Anesth. 2022; 36: 1132-1147 Abstract Full Text Full Text PDF PubMed Scopus (4) Google Scholar However, this readily accessible tool cannot completely replace patient history, physical examination, clinical judgment, and other formal imaging modalities read by a specialist for the diagnosis, monitoring, and treatment of patient clinical status. There is a concern for overdiagnosis and undertreatment of various clinical pathologies using POCUS, and future direction is needed to optimize this diagnostic tool and prevent overdiagnosis and undertreatment.

The role of cone-beam computed tomography in the radiographic evaluation of obstructive sleep apnea: A review article.

The apnea-hypopnea index is widely regarded as a measure of the severity of obstructive sleep apnea (OSA), a condition characterized by recurrent episodes of apnea or hypopnea during sleep that induce airway collapse. OSA is a catastrophic problem due to the wide range of health issues it can cause, including cardiovascular disease and memory loss. This review was conducted to clarify the roles of various imaging modalities, particularly cone-beam computed tomography (CBCT), in the diagnosis of and preoperative planning for OSA. Unfortunately, 2-dimensional imaging techniques yield insufficient data for a comprehensive diagnosis, given the complex anatomy of the airway. Three-dimensional (3D) imaging is favored as it more accurately represents the patient's airway structure. Although computed tomography and magnetic resonance imaging can depict the actual 3D airway architecture, their use is limited by factors such as high radiation dose and noise associated with the scans. This review indicates that CBCT is a low-radiation imaging technique that can be used to incidentally identify patients with OSA, thereby facilitating early referral and ultimately enhancing the accuracy of surgical outcome predictions.

Prediction of obstructive sleep apnea using deep learning in 3D craniofacial reconstruction.

Obstructive sleep apnea (OSA) is a common sleep disorder. However, current diagnostic methods are labor-intensive and require professionally trained personnel. We aimed to develop a deep learning model using upper airway computed tomography (CT) to predict OSA and to warn the medical technician if a patient has OSA while the patient is undergoing any head and neck CT scan, even for other diseases. A total of 219 patients with OSA [apnea-hypopnea index (AHI) ≥10/h] and 81 controls (AHI <10/h) were enrolled. We reconstructed each patient's CT into 3 types (skeletal structures, external skin structures, and airway structures) and captured reconstructed models in 6 directions (front, back, top, bottom, left profile, and right profile). The 6 images from each patient were imported into the ResNet-18 network to extract features and output the probability of OSA using two fusion methods: Add and Concat. Five-fold cross-validation was used to reduce bias. Finally, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were calculated. All 18 views with Add as the feature fusion performed better than did the other reconstruction and fusion methods. This gave the best performance for this prediction method with an AUC of 0.882. We present a model for predicting OSA using upper airway CT and deep learning. The model has satisfactory performance and enables CT to accurately identify patients with moderate to severe OSA.

Development of Adaptive Immunity and Its Role in Lung Remodeling.

Asthma is characterized by airflow limitations resulting from bronchial closure, which can be either reversible or fixed due to changes in airway tissue composition and structure, also known as remodeling. Airway remodeling is defined as increased presence of mucins-producing epithelial cells, increased thickness of airway smooth muscle cells, angiogenesis, increased number and activation state of fibroblasts, and extracellular matrix (ECM) deposition. Airway inflammation is believed to be the main cause of the development of airway remodeling in asthma. In this chapter, we will review the development of the adaptive immune response and the impact of its mediators and cells on the elements defining airway remodeling in asthma.