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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
Computed tomography values calculation and volume histogram analysis for various computed tomographic patterns of
Hiromitsu Sumikawa1, Takeshi Johkoh, Shuji Yamamoto
1Department of Radiology, Osaka University Graduate School of Medical, 2-2 Yamadaoka, Suita, Osaka 565-0825, Japan. h-sumikawa@radiol.med.osaka-u.ac.jp
Journal of Computer Assisted Tomography
|October 13, 2009
Summary
Histogram analysis of computed tomography (CT) scans quantitatively distinguishes various pulmonary abnormalities. CT values and histogram shapes offer unique signatures for conditions like ground-glass opacity and emphysema.
Area of Science:
- Radiology
- Medical Imaging Analysis
- Pulmonary Medicine
Background:
- Computed tomography (CT) is crucial for diagnosing lung diseases.
- Quantitative analysis of CT images can improve diagnostic accuracy.
- Histogram analysis provides a quantitative method to characterize image textures.
Purpose of the Study:
- To determine computed tomography (CT) values for various pulmonary abnormalities using cubic and square regions of interest (ROIs).
- To evaluate CT findings through histogram analysis within ROIs.
- To assess the utility of histogram parameters in differentiating lung pathologies.
Main Methods:
- Inclusion of 89 patients with 8 distinct pulmonary CT patterns: normal lung, ground-glass attenuation, fine reticular opacity, coarse reticular opacity, honeycombing, airspace consolidation, nodular opacity, and emphysema.
- Selection of cubic and square regions of interest (ROIs) within each identified CT pattern.
- Calculation of 5 histogram values: contrast, variance, entropy, skewness, and kurtosis for each ROI.
Main Results:
- Histograms for ground-glass attenuation, fine reticular opacity, and coarse reticular opacity showed a shift to the right compared to normal lung tissue.
- Emphysema exhibited significantly higher contrast and lower entropy than the normal lung (P < 0.001).
- Other lung abnormalities demonstrated lower contrast and higher entropy relative to normal lung.
Conclusions:
- The distinct shapes of histograms are characteristic of various pulmonary abnormalities.
- Quantitative histogram values effectively reflect and characterize these abnormalities.
- Histogram analysis offers a valuable tool for the quantitative assessment of lung pathologies on CT.
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