Automated CT-based measurements of radial and longitudinal expansion of airways due to breathing-related lung volume change.

Background: Respiratory function is impaired in chronic obstructive pulmonary disease (COPD). Automation of multi-volume CT-based measurements of different components of breathing-related airway deformations will help understand multi-pathway impairments in respiratory mechanics in COPD.

Purpose: To develop and evaluate multi-volume chest CT-based automated measurements of breathing-related radial and longitudinal expansion of individual airways between inspiratory and expiratory lung volumes.

Phenotypes and Trajectories of Tobacco-exposed Persons with Preserved Spirometry: Insights from Lung Volumes.

Among tobacco-exposed persons with preserved spirometry (TEPS), we previously demonstrated that different lung volume indices, specifically elevated total lung capacity (TLC) versus elevated ratio of functional residual capacity-to-TLC (FRC/TLC), identify different lung disease characteristics in the COPDGene cohort. Determine differential disease characteristics and trajectories associated with the lung volume indices among TEPS in the SPIROMICS cohort. We categorized TEPS (n=814) by tertiles (low, intermediate, high) of TLC or residual volume-to-TLC (RV/TLC) derived from baseline CT images, and then examined clinical and spirometric disease trajectories in mutually exclusive categories of participants with high TLC without high RV/TLC ([TLC]) versus high RV/TLC without high TLC ([RV/TLC]).

Residential fungal β-(1,3)-D-glucan exposure is associated with decreased pulmonary function in fibrotic pulmonary sarcoidosis.

Background: Sarcoidosis is a multi-system disease frequently affecting the lungs. It is thought to be mediated by gene-environment interaction; for example, epidemiological data show organic aerosol exposure increases risk of pulmonary sarcoidosis.

Research Question: Does exposure to bioaerosol associate with worse lung disease in patients with pulmonary sarcoidosis?

Research Question: Using an observational, cohort study design, we measured residential exposure to fungal and bacterial cell wall material, β-(1,3)-D-glucan (BDG) and endotoxin, respectively, in healthy control subjects and those with pulmonary sarcoidosis.

Automated CT-based decoupling of the effects of airway narrowing and wall thinning on airway counts in chronic obstructive pulmonary disease.

Objective: We examine pathways of airway alteration due to wall thinning, narrowing, and obliteration in chronic obstructive pulmonary disease (COPD) using CT-derived airway metrics.

Methods: Ex-smokers (N = 649; age mean ± std: 69 ± 6 years; 52% male) from the COPDGene Iowa cohort (September 2013-July 2017) were studied. Total airway count (TAC), peripheral TAC beyond 7th generation (TACp), and airway wall thickness (WT) were computed from chest CT scans using previously validated automated methods.

Dynamic and prognostic proteomic associations with FEV decline in chronic obstructive pulmonary disease.

Rationale: Identification and validation of circulating biomarkers for lung function decline in COPD remains an unmet need.

Objective: Identify prognostic and dynamic plasma protein biomarkers of COPD progression.

Methods: We measured plasma proteins using SomaScan from two COPD-enriched cohorts, the Subpopulations and Intermediate Outcomes Measures in COPD Study (SPIROMICS) and Genetic Epidemiology of COPD (COPDGene), and one population-based cohort, Multi-Ethnic Study of Atherosclerosis (MESA) Lung.

Ultra-low dose hip CT-based automated measurement of volumetric bone mineral density at proximal femoral subregions.

Background: Forty to fifty percent of women and 13%-22% of men experience an osteoporosis-related fragility fracture in their lifetimes. After the age of 50 years, the risk of hip fracture doubles in every 10 years. x-Ray based DXA is currently clinically used to diagnose osteoporosis and predict fracture risk.

Real-World Effectiveness of Nirmatrelvir in Protecting Long COVID for Outpatient Adult Patients - A Large-Scale Observational Cohort Study from the RECOVER Initiative.

Paxlovid has been approved for use in patients who are at high risk for severe acute COVID-19 illness. Evidence regarding whether Paxlovid protects against Post-Acute Sequelae of SARS-CoV-2 infection (PASC), or Long COVID, is mixed in high-risk patients and lacking in low-risk patients. With a target trial emulation framework, we evaluated the association of Paxlovid treatment within 5 days of SARS-CoV-2 infection with incident Long COVID and hospitalization or death from any cause in the post-acute period (30-180 days after infection) using electronic health records from the Patient-Centered Clinical Research Networks (PCORnet) RECOVER repository.

Association of Ground-Glass Opacities with Systemic Inflammation and Progression of Emphysema.

Ground-glass opacities (GGOs) in the absence of interstitial lung disease are understudied. To assess the association of GGOs with white blood cells (WBCs) and progression of quantified chest computed tomography emphysema. We analyzed data of participants in the SPIROMICS study (Subpopulations and Intermediate Outcome Measures in COPD Study).

MSO-GP: 3-D segmentation of large and complex conjoined tree structures.

Robust segmentation of large and complex conjoined tree structures in 3-D is a major challenge in computer vision. This is particularly true in computational biology, where we often encounter large data structures in size, but few in number, which poses a hard problem for learning algorithms. We show that merging multiscale opening with geodesic path propagation, can shed new light on this classic machine vision challenge, while circumventing the learning issue by developing an unsupervised visual geometry approach (digital topology/morphometry).

Long-COVID improves in 50% of patients after a year in a Midwestern cohort.

Background: Many of those infected with COVID-19 experience long-term disability due to persistent symptoms known as Long-COVID, which include ongoing respiratory issues, loss of taste and smell, and impaired daily functioning.

Research Question: This study aims to better understand the chronology of long-COVID symptoms.

Study Design And Methods: We prospectively enrolled 403 adults from the University of Iowa long-COVID clinic (June 2020 to February 2022).

Chest CT-based automated vertebral fracture assessment using artificial intelligence and morphologic features.

Background: Spinal degeneration and vertebral compression fractures are common among the elderly that adversely affect their mobility, quality of life, lung function, and mortality. Assessment of vertebral fractures in chronic obstructive pulmonary disease (COPD) is important due to the high prevalence of osteoporosis and associated vertebral fractures in COPD.

Purpose: We present new automated methods for (1) segmentation and labelling of individual vertebrae in chest computed tomography (CT) images using deep learning (DL), multi-parametric freeze-and-grow (FG) algorithm, and separation of apparently fused vertebrae using intensity autocorrelation and (2) vertebral deformity fracture detection using computed vertebral height features and parametric computational modelling of an established protocol outlined for trained human experts.

Chronic obstructive pulmonary disease (COPD) and COPD-like phenotypes.

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease. Historically, two COPD phenotypes have been described: chronic bronchitis and emphysema. Although these phenotypes may provide additional characterization of the pathophysiology of the disease, they are not extensive enough to reflect the heterogeneity of COPD and do not provide granular categorization that indicates specific treatment, perhaps with the exception of adding inhaled glucocorticoids (ICS) in patients with chronic bronchitis.

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.

Vessel and Airway Characteristics in One-Year Computed Tomography-defined Rapid Emphysema Progression: SPIROMICS.

Rates of emphysema progression vary in chronic obstructive pulmonary disease (COPD), and the relationships with vascular and airway pathophysiology remain unclear. We sought to determine if indices of peripheral (segmental and beyond) pulmonary arterial dilation measured on computed tomography (CT) are associated with a 1-year index of emphysema (EI; percentage of voxels <-950 Hounsfield units) progression. Five hundred ninety-nine former and never-smokers (Global Initiative for Chronic Obstructive Lung Disease stages 0-3) were evaluated from the SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study) cohort: rapid emphysema progressors (RPs;  = 188, 1-year ΔEI > 1%), nonprogressors ( = 301, 1-year ΔEI ± 0.

The rate of hypercapnic respiratory failure in a pulmonary function test laboratory database.

https://bit.ly/3H8DlfM.

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.

A Survey on Artificial Intelligence in Pulmonary Imaging.

Over the last decade, deep learning (DL) has contributed a paradigm shift in computer vision and image recognition creating widespread opportunities of using artificial intelligence in research as well as industrial applications. DL has been extensively studied in medical imaging applications, including those related to pulmonary diseases. Chronic obstructive pulmonary disease, asthma, lung cancer, pneumonia, and, more recently, COVID-19 are common lung diseases affecting nearly 7.

Anxiety and depression symptoms among patients with long COVID: a retrospective cohort study.

Patients suffering from post-acute sequelae of COVID-19 (PASC) have a higher prevalence of anxiety and depression than the general population. The long-term trajectory of these sequelae is still unfolding. To assess the burden of anxiety and depression among patients presenting to the University of Iowa Hospitals and Clinics (UIHC) post-COVID-19 clinic, we analyzed how patient factors influenced Generalized Anxiety Disorder-7 (GAD-7) and Patient Health Questionnaire-9 (PHQ-9) scores.