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Updated: Aug 30, 2025

Automated Measurement of Pulmonary Emphysema and Small Airway Remodeling in Cigarette Smoke-exposed Mice

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An Entropy-Based Measure of Complexity: An Application in Lung-Damage.

Pilar Ortiz-Vilchis¹, Aldo Ramirez-Arellano¹

¹Escuela Superior de Medicina, Instituto Politécnico Nacional, Mexico City C.P. 11340, Mexico.

Entropy (Basel, Switzerland)

|August 26, 2022

Summary

A new Lung Damage Measure (LDM) derived from Entropy-based Measure of Complexity (EMC) effectively differentiates COVID-19 and pneumonia severity using chest CT scans. This quantitative approach aids in assessing lung damage and clinical outcomes.

Keywords:

COVID-19 complexity measure d-summable information dimension entropy lung-damage

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Published on: March 21, 2021

Area of Science:

Medical Imaging
Computational Biology
Radiology

Background:

Computed tomography (CT) chest imaging is crucial for evaluating lung infections like pneumonia and COVID-19.
Computer-aided diagnostic systems utilizing entropy, fractality, and deep learning analyze lung CT images.
Existing methods require robust quantitative measures for lung damage assessment.

Purpose of the Study:

Introduce an Entropy-based Measure of Complexity (EMC).
Develop and validate a Lung Damage Measure (LDM) derived from EMC for medical applications.
Assess the efficacy of LDM in quantifying lung damage in COVID-19 and pneumonia patients.

Main Methods:

Analyzed CT scans from 486 healthy subjects, 263 with COVID-19, and 329 with pneumonia using the developed LDM.
Employed statistical analysis to compare LDM values across different subject groups.
Correlated LDM with clinical classification and CO-RADS scores.

Main Results:

Significant differences in LDM were observed between healthy individuals and patients with COVID-19 or pneumonia.
LDM was highest in common pneumonia, followed by COVID-19, and lowest in healthy subjects.
LDM demonstrated a positive correlation with clinical severity scores and CO-RADS.

Conclusions:

The developed Lung Damage Measure (LDM) shows potential as a quantitative tool for assessing and confirming the severity of lung damage in COVID-19 and pneumonia.
LDM offers a valuable addition to chest CT analysis for disease evaluation.
The d-summable information model may serve as a basis for a fractional LDM.