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Gross Anatomy of the Lungs

Gross Anatomy of the Lungs

The lungs are a pair of vital organs connected to the trachea via the left and right bronchi. The base of these organs meets the dome-shaped muscle known as the diaphragm. Encased by the pleurae, the lungs contact the mediastinum. The right lung is shorter yet wider, and has a larger volume than the left lung. The left lung has an indentation known as the cardiac notch. The superior region of the lungs is referred to as the apex, whereas the base is the lower region near the diaphragm. The...

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Updated: May 2, 2026

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

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

Published on: June 20, 2025

AlveolEye: rapid and precise lung morphometry guided by computer vision.

Joseph Hirsh¹, Samuel Hirsh¹, Shawyon P Shirazi^1,2

¹Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.

American Journal of Physiology. Lung Cellular and Molecular Physiology

|May 1, 2026

Summary

This summary is machine-generated.

AlveolEye, a new tool, enhances lung tissue analysis by automating measurements like mean linear intercept (MLI) and airspace volume density (ASVD). This improves accuracy and reduces variability in lung morphometry research.

Keywords:

lung morphometry machine learning

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Area of Science:

Pulmonary Pathology
Computational Biology
Histomorphometry

Background:

Accurate lung tissue evaluation is crucial for understanding development, injury, and drug effects.
Manual histological measurements (MLI, ASVD) are time-consuming and prone to inter-observer variability.

Purpose of the Study:

To develop an open-source, semi-automated tool, AlveolEye, for rapid and reproducible lung morphometry.
To improve the precision and throughput of MLI and ASVD calculations from H&E stained lung sections.

Main Methods:

Developed AlveolEye, a computer vision-assisted software for semi-automated analysis.
Validated AlveolEye against manual measurements using standard H&E stained lung tissue.
Assessed generalizability across species and impact on inter-observer variability.

Main Results:

AlveolEye-assisted MLI calculations closely matched manual measurements.
The tool preserved trends observed in injury models and human tissues.
Significantly reduced variation among analyzers, especially those with less experience.

Conclusions:

AlveolEye offers a reproducible and efficient method for lung morphometry.
The semi-automated design allows for investigator control and adaptability.
Facilitates larger sample sizes and improves statistical power in preclinical lung research.