Associations of pulmonary microvascular blood volume with per cent emphysema and CT emphysema subtypes in the community: the MESA Lung study.

Background: Pulmonary microvasculature alterations are implicated in emphysema pathogenesis, but the association between pulmonary microvascular blood volume (PMBV) and emphysema has not been directly assessed at scale, and prior studies have used non-specific measures of emphysema.

Methods: The Multi-Ethnic Study of Atherosclerosis Lung Study invited participants recruited from the community without renal impairment to undergo contrast-enhanced dual-energy CT. Pulmonary blood volume was calculated by material decomposition; PMBV was defined as blood volume in the peripheral 2 cm of the lung.

The pleural gradient does not reflect the superimposed pressure in patients with class III obesity.

Background: The superimposed pressure is the primary determinant of the pleural pressure gradient. Obesity is associated with elevated end-expiratory esophageal pressure, regardless of lung disease severity, and the superimposed pressure might not be the only determinant of the pleural pressure gradient. The study aims to measure partitioned respiratory mechanics and superimposed pressure in a cohort of patients admitted to the ICU with and without class III obesity (BMI ≥ 40 kg/m), and to quantify the amount of thoracic adipose tissue and muscle through advanced imaging techniques.

Mechanical ventilation guided by driving pressure optimizes local pulmonary biomechanics in an ovine model.

Mechanical ventilation exposes the lung to injurious stresses and strains that can negatively affect clinical outcomes in acute respiratory distress syndrome or cause pulmonary complications after general anesthesia. Excess global lung strain, estimated as increased respiratory system driving pressure, is associated with mortality related to mechanical ventilation. The role of small-dimension biomechanical factors underlying this association and their spatial heterogeneity within the lung are currently unknown.

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).

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.

LungViT: Ensembling Cascade of Texture Sensitive Hierarchical Vision Transformers for Cross-Volume Chest CT Image-to-Image Translation.

Chest computed tomography (CT) at inspiration is often complemented by an expiratory CT to identify peripheral airways disease. Additionally, co-registered inspiratory-expiratory volumes can be used to derive various markers of lung function. Expiratory CT scans, however, may not be acquired due to dose or scan time considerations or may be inadequate due to motion or insufficient exhale; leading to a missed opportunity to evaluate underlying small airways disease.

Structural Predictors of Lung Function Decline in Young Smokers with Normal Spirometry.

Chronic obstructive pulmonary disease (COPD) due to tobacco smoking commonly presents when extensive lung damage has occurred. We hypothesized that structural change would be detected early in the natural history of COPD and would relate to loss of lung function with time. We recruited 431 current smokers (median age, 39 yr; 16 pack-years smoked) and recorded symptoms using the COPD Assessment Test (CAT), spirometry, and quantitative thoracic computed tomography (QCT) scans at study entry.

Attention U-net for automated pulmonary fissure integrity analysis in lung computed tomography images.

Computed Tomography (CT) imaging is routinely used for imaging of the lungs. Deep learning can effectively automate complex and laborious tasks in medical imaging. In this work, a deep learning technique is utilized to assess lobar fissure completeness (also known as fissure integrity) from pulmonary CT images.

Electrical Impedance Tomography Identifies Evolution of Regional Perfusion in a Porcine Model of Acute Respiratory Distress Syndrome.

Background: Bedside electrical impedance tomography could be useful to visualize evolving pulmonary perfusion distributions when acute respiratory distress syndrome worsens or in response to ventilatory and positional therapies. In experimental acute respiratory distress syndrome, this study evaluated the agreement of electrical impedance tomography and dynamic contrast-enhanced computed tomography perfusion distributions at two injury time points and in response to increased positive end-expiratory pressure (PEEP) and prone position.

Methods: Eleven mechanically ventilated (VT 8 ml · kg-1) Yorkshire pigs (five male, six female) received bronchial hydrochloric acid (3.

A specific combination of laboratory data is associated with overweight lungs in patients with COVID-19 pneumonia at hospital admission: secondary cross-sectional analysis of a randomized clinical trial.

Background: Lung weight may be measured with quantitative chest computed tomography (CT) in patients with COVID-19 to characterize the severity of pulmonary edema and assess prognosis. However, this quantitative analysis is often not accessible, which led to the hypothesis that specific laboratory data may help identify overweight lungs.

Methods: This cross-sectional study was a secondary analysis of data from SARITA2, a randomized clinical trial comparing nitazoxanide and placebo in patients with COVID-19 pneumonia.

Improving pulmonary perfusion assessment by dynamic contrast-enhanced computed tomography in an experimental lung injury model.

Pulmonary perfusion has been poorly characterized in acute respiratory distress syndrome (ARDS). Optimizing protocols to measure pulmonary blood flow (PBF) via dynamic contrast-enhanced (DCE) computed tomography (CT) could improve understanding of how ARDS alters pulmonary perfusion. In this study, comparative evaluations of injection protocols and tracer-kinetic analysis models were performed based on DCE-CT data measured in ventilated pigs with and without lung injury.

Direct estimation of regional lung volume change from paired and single CT images using residual regression neural network.

Background: Chest computed tomography (CT) enables characterization of pulmonary diseases by producing high-resolution and high-contrast images of the intricate lung structures. Deformable image registration is used to align chest CT scans at different lung volumes, yielding estimates of local tissue expansion and contraction.

Purpose: We investigated the utility of deep generative models for directly predicting local tissue volume change from lung CT images, bypassing computationally expensive iterative image registration and providing a method that can be utilized in scenarios where either one or two CT scans are available.

A Personalized Spring Network Representation of Emphysematous Lungs From CT Images.

Emphysema is a progressive disease characterized by irreversible tissue destruction and airspace enlargement, which manifest as low attenuation area (LAA) on CT images. Previous studies have shown that inflammation, protease imbalance, extracellular matrix remodeling and mechanical forces collectively influence the progression of emphysema. Elastic spring network models incorporating force-based mechanical failure have been applied to investigate the pathogenesis and progression of emphysema.

Predicting pulmonary ventilation damage after radiation therapy for nonsmall cell lung cancer using a ResNet generative adversarial network.

Background: Functional lung avoidance radiation therapy (RT) is a technique being investigated to preferentially avoid specific regions of the lung that are predicted to be more susceptible to radiation-induced damage. Reducing the dose delivered to high functioning regions may reduce the occurrence radiation-induced lung injuries (RILIs) and toxicities. However, in order to develop effective lung function-sparing plans, accurate predictions of post-RT ventilation change are needed to determine which regions of the lung should be spared.

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

Background: 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.

Methods: 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.

Robust Measures of Image-Registration-Derived Lung Biomechanics in SPIROMICS.

Chronic obstructive pulmonary disease (COPD) is an umbrella term used to define a collection of inflammatory lung diseases that cause airflow obstruction and severe damage to the lung parenchyma. This study investigated the robustness of image-registration-based local biomechanical properties of the lung in individuals with COPD as a function of Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage. Image registration was used to estimate the pointwise correspondences between the inspiration (total lung capacity) and expiration (residual volume) computed tomography (CT) images of the lung for each subject.

CT-derived vessel segmentation for analysis of post-radiation therapy changes in vasculature and perfusion.

Vessel segmentation in the lung is an ongoing challenge. While many methods have been able to successfully identify vessels in normal, healthy, lungs, these methods struggle in the presence of abnormalities. Following radiotherapy, these methods tend to identify regions of radiographic change due to post-radiation therapytoxicities as vasculature falsely.

Pulmonary Blood Volume Among Older Adults in the Community: The MESA Lung Study.

Background: The pulmonary vasculature is essential for gas exchange and impacts both pulmonary and cardiac function. However, it is difficult to assess and its characteristics in the general population are unknown. We measured pulmonary blood volume (PBV) noninvasively using contrast enhanced, dual-energy computed tomography to evaluate its relationship to age and symptoms among older adults in the community.

Unsupervised segmentation and quantification of COVID-19 lesions on computed Tomography scans using CycleGAN.

Background: Lesion segmentation is a critical step in medical image analysis, and methods to identify pathology without time-intensive manual labeling of data are of utmost importance during a pandemic and in resource-constrained healthcare settings. Here, we describe a method for fully automated segmentation and quantification of pathological COVID-19 lung tissue on chest Computed Tomography (CT) scans without the need for manually segmented training data.

Methods: We trained a cycle-consistent generative adversarial network (CycleGAN) to convert images of COVID-19 scans into their generated healthy equivalents.

Early versus late intubation in COVID-19 patients failing helmet CPAP: A quantitative computed tomography study.

Purpose: To describe the effects of timing of intubation in COVID-19 patients that fail helmet continuous positive airway pressure (h-CPAP) on progression and severity of disease.

Methods: COVID-19 patients that failed h-CPAP, required intubation, and underwent chest computed tomography (CT) at two levels of positive end-expiratory pressure (PEEP, 8 and 16 cmHO) were included in this retrospective study. Patients were divided in two groups (early versus late) based on the duration of h-CPAP before intubation.

Effects of Lung Injury on Regional Aeration and Expiratory Time Constants: Insights From Four-Dimensional Computed Tomography Image Registration.

: Intratidal changes in regional lung aeration, as assessed with dynamic four-dimensional computed tomography (CT; 4DCT), may indicate the processes of recruitment and derecruitment, thus portending atelectrauma during mechanical ventilation. In this study, we characterized the time constants associated with deaeration during the expiratory phase of pressure-controlled ventilation in pigs before and after acute lung injury using respiratory-gated 4DCT and image registration. : Eleven pigs were mechanically ventilated in pressure-controlled mode under baseline conditions and following an oleic acid model of acute lung injury.

Case Studies in Physiology: Temporal variations of the lung parenchyma and vasculature in asymptomatic COVID-19 pneumonia: a multispectral CT assessment.

This study reports systematic longitudinal pathophysiology of lung parenchymal and vascular effects of asymptomatic COVID-19 pneumonia in a young, healthy never-smoking male. Inspiratory and expiratory noncontrast along with contrast dual-energy computed tomography (DECT) scans of the chest were performed at baseline on the day of acute COVID-19 diagnosis (), and across a 90-day period. Despite normal vital signs and pulmonary function tests on the day of diagnosis, the CT scans and corresponding quantification metrics detected abnormalities in parenchymal expansion based on image registration, ground-glass (GGO) texture (inflammation) as well as DECT-derived pulmonary blood volume (PBV).

Lung distribution of gas and blood volume in critically ill COVID-19 patients: a quantitative dual-energy computed tomography study.

Background: Critically ill COVID-19 patients have pathophysiological lung features characterized by perfusion abnormalities. However, to date no study has evaluated whether the changes in the distribution of pulmonary gas and blood volume are associated with the severity of gas-exchange impairment and the type of respiratory support (non-invasive versus invasive) in patients with severe COVID-19 pneumonia.

Methods: This was a single-center, retrospective cohort study conducted in a tertiary care hospital in Northern Italy during the first pandemic wave.