Unlabelled: The development of the high-resolution computed tomography (HRCT) has improved the ability to detect and quantify emphysema in various groups of patients with chronic airflow obstruction (COPD). Significant correlations have previously been found between indices of air flow obstruction, hyperinflation, reduced diffusing capacity for carbon monoxide (DLCO), and the extent of emphysema (emph.%) assessed by HRCT. However, the relationship between emph.% and ventilation-perfusion (V(A)/Q) inequality in COPD is unknown. Twenty COPD patients with a mean forced expiratory volume in 1 s (FEV1) of 38.2 (+/- 15.5)% in percent of predicted value (%P), a mean PaO2 value of 9.6 (+/- 1.3) kPa, and a mean diffusing capacity of 43.6 (+/- 23.0)%P, were subjected to measurements by the multiple elimination inert gas technique (MIGET). The extent of emphysema was determined by HRCT at both full inspiration, emph.I(%) and at full expiration, emph.E(%), with a cut-off limit of -910 Hounsfield Units (HU) using the "Density Mask" method. The ventilation directed towards high V(A)/Q areas was 73 (+/- 10.2)% and the mean ventilation (V-mean) was elevated about three times compared to normal. The mean emph.(I)% and emph.(E) was 45.6 (+/- 16.9) and 32.7 (+/- 190)%, respectively. Significant correlations were shown between the emphysema extent and several lung function parameters, but no correlation was found between the emphysema extent and the V(A)/Q relationships or the blood gas values. Reduced DLCO%P correlated with less high V(A)/Q ventilation (r=0.73, P < 0.05) for the subgroup of COPD patients with DLCO(%P) less than 50% (n=12).
Conclusions: In COPD patients, suffering from moderate to severe emphysema without severe blood gas impairment, no correlation was shown between the extent of emphysema, as assessed by HRCT, and the severity of ventilation-perfusion inequality. A substantial collateral ventilation in severe emphysema may be a mechanism that prevents a deterioration in V(A)/Q relationships and in blood gas levels.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1053/rmed.2002.1371 | DOI Listing |
Clin Radiol
December 2024
São Paulo State University (UNESP), Medical School, Botucatu, Brazil. Electronic address:
Aim: To enhance the understanding of COVID-19 regional lung damage pattern by analyzing the organ in subregions, beyond the typical lobe segmentation.
Materials And Methods: This study used semiautomatic computed tomography (CT) imaging segmentation and quantification to investigate regional lung impairments in patients with COVID-19. Each lung was divided into 12 regions, and the anatomical impairments obtained from the CT image (emphysema, ground glass opacity, and collapsed tissue) were quantified.
Am J Med Sci
January 2025
Department of Critical Care Medicine, Dongying People's Hospital, Dongying, Shandong, China. Electronic address:
Background: Patients with combined pulmonary fibrosis and emphysema (CPFE) may experience emphysema or fibrosis progression on chest computed tomography (CT). This study aimed to investigate the relationship and prognosis in CPFE patients with emphysema or fibrosis progression.
Methods: A total of 188 CPFE patients were included in our retrospective cohort study.
Thorax
January 2025
Department of Pulmonology and Home Mechanical Ventilation, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Purpose: In patients with chronic obstructive pulmonary disease (COPD) treated with chronic non-invasive ventilation (NIV), the relation between improvements in nocturnal transcutaneous partial pressure of CO (PtcCO) and daytime arterial partial pressure of CO (PaCO) remains uncertain. Also, to what extent improvements in nocturnal PtcCO result in better health-related quality of life (HRQL), exercise capacity, lung function and survival has not been investigated.
Patients And Methods: Patients with COPD who were initiated on chronic NIV were prospectively followed for 6 months.
Invest Radiol
October 2024
From the Institute for Diagnostic and Interventional Radiology, University Hospital Zurich, University Zurich, Zurich, Switzerland (B.K., F.E., J.K., T.F., L.J.); Advanced Radiology Center, Department of Diagnostic Imaging and Oncological Radiotherapy, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy (C.S., A.R.L.); and Section of Radiology, Department of Radiological and Hematological Sciences, Università Cattolica del Sacro Cuore, Rome, Italy (A.R.L.).
Objectives: The aim of this study was to evaluate the feasibility and efficacy of visual scoring, low-attenuation volume (LAV), and deep learning methods for estimating emphysema extent in x-ray dose photon-counting detector computed tomography (PCD-CT), aiming to explore future dose reduction potentials.
Methods: One hundred one prospectively enrolled patients underwent noncontrast low- and chest x-ray dose CT scans in the same study using PCD-CT. Overall image quality, sharpness, and noise, as well as visual emphysema pattern (no, trace, mild, moderate, confluent, and advanced destructive emphysema; as defined by the Fleischner Society), were independently assessed by 2 experienced radiologists for low- and x-ray dose images, followed by an expert consensus read.
Eur Radiol
December 2024
Thoracic Surgery Unit, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy.
Objectives: To assess the consistency of automated measurements of coronary artery calcification (CAC) burden and emphysema extent on computed tomography (CT) images acquired with different radiation dose protocols in a lung cancer screening (LCS) population.
Materials And Methods: The patient cohort comprised 361 consecutive screenees who underwent a low-dose CT (LDCT) scan and an ultra-low-dose CT (ULDCT) scan at an incident screening round. Exclusion criteria for CAC measurements were software failure and previous history of CVD, including coronary stenting, whereas for emphysema assessment, software failure only.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!