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Related Concept Videos

Computed Tomography01:10

Computed Tomography

Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...

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Related Experiment Video

Updated: Jun 7, 2026

A Standardized Method for Measuring Internal Lung Surface Area via Mouse Pneumonectomy and Prosthesis Implantation
08:46

A Standardized Method for Measuring Internal Lung Surface Area via Mouse Pneumonectomy and Prosthesis Implantation

Published on: July 26, 2017

Quantification of lung surface area using computed tomography.

Ren Yuan1, Taishi Nagao, Peter D Paré

  • 1University of British Columbia James Hogg Research Centre and the Heart and Lung Institute, St. Paul’s Hospital, Burrard Street, Vancouver, Canada.

Respiratory Research
|November 3, 2010
PubMed
Summary
This summary is machine-generated.

Combining computed tomography (CT) lung density and emphysematous lesion size improves emphysema prediction. This approach offers a more accurate estimation of lung surface area per unit volume compared to using either measure alone.

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Unilateral Lung Volume Analysis Using Micro-CT for Enhanced Assessment of Pulmonary Fibrosis in Preclinical Models
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Unilateral Lung Volume Analysis Using Micro-CT for Enhanced Assessment of Pulmonary Fibrosis in Preclinical Models

Published on: June 20, 2025

Area of Science:

  • Pulmonary Medicine
  • Radiology
  • Pathology

Background:

  • Emphysema assessment often relies on computed tomography (CT) imaging.
  • Accurate prediction of emphysema severity is crucial for patient management and treatment.
  • Histological measurement of surface area per unit lung volume is a key indicator of emphysema.

Purpose of the Study:

  • To enhance CT-based prediction of emphysema by integrating regional lung density and low attenuation cluster analysis.
  • To compare CT-derived measures with histological assessments of surface area per unit lung volume.
  • To determine if combining CT parameters improves emphysema prediction accuracy.

Main Methods:

  • Histological surface area per unit lung volume was measured in 140 lung samples from 14 subjects.
  • Corresponding lung regions were identified on pre-operative CT scans.
  • Regional CT lung density and emphysematous lesion size (using low attenuation cluster analysis) were calculated and analyzed using linear mixed models.

Main Results:

  • Both median CT lung density and low attenuation cluster analysis significantly predicted histological surface area per unit lung volume (p < 0.0001).
  • A model incorporating both CT parameters provided the most accurate prediction of emphysema, as indicated by Akaike's information criterion.
  • The combined CT measures were superior to individual measures in predicting emphysema.

Conclusions:

  • Combining CT measures of lung density and emphysematous lesion size offers a more precise estimation of lung surface area per unit volume.
  • This integrated CT approach enhances the prediction of emphysema compared to using single CT parameters.
  • The findings support the use of combined CT metrics for improved emphysema assessment.