Interstitial lung disease in systemic sclerosis quantification of disease classification and progression with high-resolution computed tomography: An observational study.

Introduction: Systemic sclerosis-associated interstitial lung disease accounts for up to 20% of mortality in these patients and has a highly variable prognosis. Functional respiratory imaging, a quantitative computed tomography imaging technique which allows mapping of regional information, can provide a detailed view of lung structures. It thereby shows potential to better characterize this disease.

SARS-CoV-2 seroprevalence survey among health care providers in a Belgian public multiple-site hospital.

Although the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is lasting for more than 1 year, the exposition risks of health-care providers are still unclear. Available evidence is conflicting. We investigated the prevalence of antibodies against SARS-CoV-2 in the staff of a large public hospital with multiple sites in the Antwerp region of Belgium.

Comparison between the ATS/ERS/JRS/ALAT criteria of 2011 and 2018 for Usual Interstitial Pneumonia on HRCT: a cross-sectional study.

Objectives: To determine whether the revised 2018 ATS/ERS/JRS/ALAT radiological criteria for usual interstitial pneumonia (UIP) provide better diagnostic agreement compared to the 2011 guidelines.

Methods: Cohort for this cross-sectional study (single center, nonacademic) was recruited from a multidisciplinary team discussion (MDD) from July 2010 until November 2018, with clinical suspicion of fibrosing interstitial lung disease (= 325). Exclusion criteria were technical HRCT issues, known connective tissue disease (rheumatoid arthritis, systemic sclerosis, poly-or dermatomyositis), exposure to pulmonary toxins or lack of working diagnosis after MDD.

Machine Learning Algorithms Utilizing Functional Respiratory Imaging May Predict COPD Exacerbations.

Rationale And Objectives: Acute chronic obstructive pulmonary disease exacerbations (AECOPD) have a significant negative impact on the quality of life and accelerate progression of the disease. Functional respiratory imaging (FRI) has the potential to better characterize this disease. The purpose of this study was to identify FRI parameters specific to AECOPD and assess their ability to predict future AECOPD, by use of machine learning algorithms, enabling a better understanding and quantification of disease manifestation and progression.

A randomized study using functional respiratory imaging to characterize bronchodilator effects of glycopyrrolate/formoterol fumarate delivered by a metered dose inhaler using co-suspension delivery technology in patients with COPD.

Background: Functional respiratory imaging (FRI) uses high-resolution computed tomography (HRCT) scans to assess changes in airway volume and resistance.

Patients And Methods: In this randomized, double-blind, 2-week, crossover, Phase IIIB study, patients with moderate-to-severe COPD received twice-daily glycopyrrolate/formoterol fumarate delivered by a metered dose inhaler (GFF MDI, 18/9.6 μg) and placebo MDI, formulated using innovative co-suspension delivery technology.

Functional respiratory imaging (FRI) for optimizing therapy development and patient care.

Functional imaging techniques offer the possibility of improved visualization of anatomical structures such as; airways, lobe volumes and blood vessels. Computer-based flow simulations with a three-dimensional element add functionality to the images. By providing valuable detailed information about airway geometry, internal airflow distribution and inhalation profile, functional respiratory imaging can be of use routinely in the clinic.