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Related Experiment Video

Updated: Jun 22, 2026

Fabrication and Characterization of Optical Tissue Phantoms Containing Macrostructure

Fabrication and Characterization of Optical Tissue Phantoms Containing Macrostructure

Published on: February 12, 2018

Cystic Lung Phantom to Validate Clinical CT Protocols.

Shefra Shah¹, Farah Hussaini¹, Dumitru Mazilu¹

¹Laboratory of Imaging Physics, Biochemistry and Biophysics Center, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA.

Methods and Protocols

|June 25, 2025

Summary

A new cystic lung phantom helps calibrate CT scans for lung diseases like LAM. Small cysts are often underestimated in volume, an important finding for clinical assessment.

Keywords:

CT cystic lung phantom CT scan cystic lung disease

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Last Updated: Jun 22, 2026

Fabrication and Characterization of Optical Tissue Phantoms Containing Macrostructure

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Published on: February 12, 2018

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia

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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

Area of Science:

Radiology
Medical Imaging
Pulmonary Medicine

Background:

Accurate measurement of cystic lung volumes from CT scans is crucial for diseases like Lymphangioleiomyomatosis (LAM).
Existing methods lack a standardized phantom to calibrate CT-based volume measurements of pulmonary cysts.
Pulmonary cysts present a challenge in quantitative CT analysis.

Purpose of the Study:

To develop and validate an easily replicable cystic lung phantom for CT calibration.
To assess the accuracy of CT-based volume measurements for pulmonary cysts of varying sizes.
To investigate potential biases in CT volumetry of lung cysts.

Main Methods:

Construction of a cystic lung phantom with a trachea and lung compartments containing air cavities of varying sizes.
Utilization of NIST-recommended foam material to simulate lung parenchyma radiodensity.
Testing the phantom on a clinical CT scanner with two lung analysis software types.

Main Results:

The lung phantom's structures were accurately recognized by analysis software.
CT-based volume measurements showed underestimation of individual cyst volumes, particularly for smaller cysts.
The degree of underestimation increased as cyst size decreased.

Conclusions:

The developed cystic lung phantom is effective for CT calibration and analysis.
Clinicians should be aware of the systematic underestimation of small pulmonary cyst volumes in CT scans.
This finding is critical for accurate cyst burden assessment in patients with numerous small pulmonary cysts.