Exploratory Study on COPD Phenotypes and their Progression: Integrating SPECT and qCT Imaging Analysis.

Background: The objective of this study is to understand chronic obstructive pulmonary disease (COPD) phenotypes and their progressions by quantifying heterogeneities of lung ventilation from the single photon emission computed tomography (SPECT) images and establishing associations with the quantitative computed tomography (qCT) imaging-based clusters and variables.

Methods: Eight COPD patients completed a longitudinal study of three visits with intervals of about a year. CT scans of these subjects at residual volume, functional residual capacity, and total lung capacity were taken for all visits.

Human-airway surface mesh smoothing based on graph convolutional neural networks.

Background And Objective: A detailed representation of the airway geometry in the respiratory system is critical for predicting precise airflow and pressure behaviors in computed tomography (CT)-image-based computational fluid dynamics (CFD). The CT-image-based geometry often contains artifacts, noise, and discontinuities due to the so-called stair step effect. Hence, an advanced surface smoothing is necessary.

Investigating distributions of inhaled aerosols in the lungs of post-COVID-19 clusters through a unified imaging and modeling approach.

Background: Recent studies, based on clinical data, have identified sex and age as significant factors associated with an increased risk of long COVID. These two factors align with the two post-COVID-19 clusters identified by a deep learning algorithm in computed tomography (CT) lung scans: Cluster 1 (C1), comprising predominantly females with small airway diseases, and Cluster 2 (C2), characterized by older individuals with fibrotic-like patterns. This study aims to assess the distributions of inhaled aerosols in these clusters.

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).

Contrastive learning and subtyping of post-COVID-19 lung computed tomography images.

Patients who recovered from the novel coronavirus disease 2019 (COVID-19) may experience a range of long-term symptoms. Since the lung is the most common site of the infection, pulmonary sequelae may present persistently in COVID-19 survivors. To better understand the symptoms associated with impaired lung function in patients with post-COVID-19, we aimed to build a deep learning model which conducts two tasks: to differentiate post-COVID-19 from healthy subjects and to identify post-COVID-19 subtypes, based on the latent representations of lung computed tomography (CT) scans.

CT-based lung motion differences in patients with usual interstitial pneumonia and nonspecific interstitial pneumonia.

We applied quantitative CT image matching to assess the degree of motion in the idiopathic ILD such as usual interstitial pneumonia (UIP) and nonspecific interstitial pneumonia (NSIP). Twenty-one normal subjects and 42 idiopathic ILD (31 UIP and 11 NSIP) patients were retrospectively included. Inspiratory and expiratory CT images, reviewed by two experienced radiologists, were used to compute displacement vectors at local lung regions matched by image registration.

Characterizing Subjects Exposed to Humidifier Disinfectants Using Computed-Tomography-Based Latent Traits: A Deep Learning Approach.

Around nine million people have been exposed to toxic humidifier disinfectants (HDs) in Korea. HD exposure may lead to HD-associated lung injuries (HDLI). However, many people who have claimed that they experienced HD exposure were not diagnosed with HDLI but still felt discomfort, possibly due to the unknown effects of HD.

A computed tomography imaging-based subject-specific whole-lung deposition model.

The respiratory tract is an important route for beneficial drug aerosol or harmful particulate matter to enter the body. To assess the therapeutic response or disease risk, whole-lung deposition models have been developed, but were limited by compartment, symmetry or stochastic approaches. In this work, we proposed an imaging-based subject-specific whole-lung deposition model.

CT-derived 3D-diaphragm motion in emphysema and IPF compared to normal subjects.

Image registration-based local displacement analysis enables evaluation of respiratory motion between two computed tomography-captured lung volumes. The objective of this study was to compare diaphragm movement among emphysema, idiopathic pulmonary fibrosis (IPF) and normal subjects. 29 normal, 50 emphysema, and 51 IPF subjects were included.

Longitudinal Imaging-Based Clusters in Former Smokers of the COPD Cohort Associate with Clinical Characteristics: The SubPopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS).

Purpose: Quantitative computed tomography (qCT) imaging-based cluster analysis identified clinically meaningful COPD former-smoker subgroups (clusters) based on cross-sectional data. We aimed to identify progression clusters for former smokers using longitudinal data.

Patients And Methods: We selected 472 former smokers from SPIROMICS with a baseline visit and a one-year follow-up visit.

Generation-based study of airway remodeling in smokers with normal-looking CT with normalization to control inter-subject variability.

Purpose: With the help of quantitative computed tomography (QCT), it is possible to identify smoking-associated airway remodeling. However, there is currently little information on whether QCT-based airway metrics are sensitive to early airway wall remodeling in subclinical phases of smoking-associated airway disease. This study aimed to evaluate a predictive model that normalized airway parameters and investigate structural airway alterations in smokers with normal-looking CT using the normalization scheme.

Latent traits of lung tissue patterns in former smokers derived by dual channel deep learning in computed tomography images.

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease and the traditional variables extracted from computed tomography (CT) images may not be sufficient to describe all the topological features of lung tissues in COPD patients. We employed an unsupervised three-dimensional (3D) convolutional autoencoder (CAE)-feature constructor (FC) deep learning network to learn from CT data and derive tissue pattern-clusters jointly. We then applied exploratory factor analysis (EFA) to discover the unobserved latent traits (factors) among pattern-clusters.

Assessment and Validation of a Hygroscopic Growth Model with Different Water Activity Estimation Methods.

Hygroscopic growth models are currently of interest as aids for targeting the deposition of inhaled drug particles in preferred areas of the lung that will maximize their pharmaceutical effect. Mathematical models derived to estimate hygroscopic growth over time have been previously developed but have not been thoroughly validated. For this study, model validation involved a comparison of modeled values to measured values when the growing droplet had reached equilibrium.

An integrated 1D breathing lung simulation with relative hysteresis of airway structure and regional pressure for healthy and asthmatic human lungs.

This study aims to develop a one-dimensional (1D) computational fluid dynamics (CFD) model with dynamic airway geometry that considers airway wall compliance and acinar dynamics. The proposed 1D model evaluates the pressure distribution and the hysteresis between the pressure and tidal volume () in the central and terminal airways for healthy and asthmatic subjects. Four-dimensional CT images were captured at 11-14 time points during the breathing cycle.

Association of Dysanapsis With Chronic Obstructive Pulmonary Disease Among Older Adults.

Importance: Smoking is a major risk factor for chronic obstructive pulmonary disease (COPD), yet much of COPD risk remains unexplained.

Objective: To determine whether dysanapsis, a mismatch of airway tree caliber to lung size, assessed by computed tomography (CT), is associated with incident COPD among older adults and lung function decline in COPD.

Design, Setting, And Participants: A retrospective cohort study of 2 community-based samples: the Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study, which involved 2531 participants (6 US sites, 2010-2018) and the Canadian Cohort of Obstructive Lung Disease (CanCOLD), which involved 1272 participants (9 Canadian sites, 2010-2018), and a case-control study of COPD: the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS), which involved 2726 participants (12 US sites, 2011-2016).

Quantitative CT-based structural alterations of segmental airways in cement dust-exposed subjects.

Background: Dust exposure has been reported as a risk factor of pulmonary disease, leading to alterations of segmental airways and parenchymal lungs. This study aims to investigate alterations of quantitative computed tomography (QCT)-based airway structural and functional metrics due to cement-dust exposure.

Methods: To reduce confounding factors, subjects with normal spirometry without fibrosis, asthma and pneumonia histories were only selected, and a propensity score matching was applied to match age, sex, height, smoking status, and pack-years.

Transport and deposition of hygroscopic particles in asthmatic subjects with and without airway narrowing.

This study numerically investigates the effect of hygroscopicity on transport and deposition of particles in severe asthmatic lungs with distinct airway structures. The study human subjects were selected from two imaging-based severe asthmatic clusters with one characterized by non-constricted airways and the other by constricted airways in the lower left lobe (LLL). We compared the deposition fractions of sodium chloride (NaCl) particles with a range of aerodynamic diameters (1-8 μm) in cluster archetypes under conditions with and without hygroscopic growth.

Erratum: Structural and Functional Features on Quantitative Chest Computed Tomography in the Korean Asian versus the White American Healthy Non-Smokers.

This corrects the article on p. 20 in vol. 1236, PMID: 31270987.

Imaging-based clusters in former smokers of the COPD cohort associate with clinical characteristics: the SubPopulations and intermediate outcome measures in COPD study (SPIROMICS).

Background: Quantitative computed tomographic (QCT) imaging-based metrics enable to quantify smoking induced disease alterations and to identify imaging-based clusters for current smokers. We aimed to derive clinically meaningful sub-groups of former smokers using dimensional reduction and clustering methods to develop a new way of COPD phenotyping.

Methods: An imaging-based cluster analysis was performed for 406 former smokers with a comprehensive set of imaging metrics including 75 imaging-based metrics.

Structural and Functional Features on Quantitative Chest Computed Tomography in the Korean Asian versus the White American Healthy Non-Smokers.

Objective: Considering the different prevalence rates of diseases such as asthma and chronic obstructive pulmonary disease in Asians relative to other races, Koreans may have unique airway structure and lung function. This study aimed to investigate unique features of airway structure and lung function based on quantitative computed tomography (QCT)-imaging metrics in the Korean Asian population (Koreans) as compared with the White American population (Whites).

Materials And Methods: QCT data of healthy non-smokers (223 Koreans vs.

1D network simulations for evaluating regional flow and pressure distributions in healthy and asthmatic human lungs.

This study aimed to introduce a one-dimensional (1D) computational fluid dynamics (CFD) model for airway resistance and lung compliance to examine the relationship between airway resistance, pressure, and regional flow distribution. We employed five healthy and five asthmatic subjects who had dynamic computed tomography (CT) scans (4D CT) along with two static scans at total lung capacity and functional residual capacity. Fractional air-volume change ( ) from 4D CT was used for a validation of the 1D CFD model.

Differences in Particle Deposition Between Members of Imaging-Based Asthma Clusters.

Four computed tomography (CT) imaging-based clusters have been identified in a study of the Severe Asthma Research Program (SARP) cohort and have been significantly correlated with clinical and demographic metrics ( 2017; 140:690-700.e8). We used a computational fluid dynamics (CFD) model to investigate air flow and aerosol deposition within imaging archetypes representative of the four clusters.

Imaging-based clusters in current smokers of the COPD cohort associate with clinical characteristics: the SubPopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS).

Background: Classification of COPD is usually based on the severity of airflow, which may not sensitively differentiate subpopulations. Using a multiscale imaging-based cluster analysis (MICA), we aim to identify subpopulations for current smokers with COPD.

Methods: Among the SPIROMICS subjects, we analyzed computed tomography images at total lung capacity (TLC) and residual volume (RV) of 284 current smokers.

A Feasible Computational Fluid Dynamics Study for Relationships of Structural and Functional Alterations with Particle Depositions in Severe Asthmatic Lungs.

This study aims to investigate the effect of altered structures and functions in severe asthma on particle deposition by using computational fluid dynamics (CFD) models. Airway geometrical models of two healthy subjects and two severe asthmatics were reconstructed from computed tomography (CT) images. Subject-specific flow boundary conditions were obtained by image registration to account for regional functional alterations of severe asthmatics.