Standardization of Lung CT Number Using COPD Gene2 Phantom Under Various Scanning Protocols

Lung computed tomography (CT) images are widely used to diagnose chronic obstructive pulmonary disease (COPD) by evaluating signs of lung tissue destruction. Accurate diagnosis requires standardizing the CT numbers in lung CT images to distinguish between normal and damaged tissue. The CT number standardization method proposed by Chen-Mayer et al., which uses the linearity of Martinez's formula, showed promising results in phantom studies. However, our findings reveal that the CT number of water varies significantly, depending on scanning conditions and the characteristics of its container, making it an unreliable reference for lung CT number standardization. To enhance the standardization method, we modified the approach to exclude water and used only solid foams from the COPD gene2 phantom as references. To evaluate the proposed method, we collected 234 CT images of the COPD gene2 phantom from 8 different CT scanners and assessed performance by analyzing CT number standard deviations and variations. The modification resulted in improved reliability and consistency in CT number standardization. Additionally, for a detailed analysis, we segmented the dataset based on CT dose index (CTDI), X-ray tube potential, and reconstruction algorithms to examine the impact of different scanning protocols on standardization performance.

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Publication Details

Journal
Sensors
Published
2025-05-04
DOI
https://doi.org/10.3390/s25092906
Citations
1
Primary Topic
Lung Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
1.52

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article

Standardization of Lung CT Number Using COPD Gene2 Phantom Under Various Scanning Protocols

Hoondong Song, Hanjoo Jang, Jongduk Baek
1 citations
Sensors
Lung Cancer Diagnosis and Treatment
1.52
article

Standardization of Lung CT Number Using COPD Gene2 Phantom Under Various Scanning Protocols

Hoondong Song, Hanjoo Jang, Jongduk Baek
article en
1 citations

Abstract

Lung computed tomography (CT) images are widely used to diagnose chronic obstructive pulmonary disease (COPD) by evaluating signs of lung tissue destruction. Accurate diagnosis requires standardizing the CT numbers in lung CT images to distinguish between normal and damaged tissue. The CT number standardization method proposed by Chen-Mayer et al., which uses the linearity of Martinez's formula, showed promising results in phantom studies. However, our findings reveal that the CT number of water varies significantly, depending on scanning conditions and the characteristics of its container, making it an unreliable reference for lung CT number standardization. To enhance the standardization method, we modified the approach to exclude water and used only solid foams from the COPD gene2 phantom as references. To evaluate the proposed method, we collected 234 CT images of the COPD gene2 phantom from 8 different CT scanners and assessed performance by analyzing CT number standard deviations and variations. The modification resulted in improved reliability and consistency in CT number standardization. Additionally, for a detailed analysis, we segmented the dataset based on CT dose index (CTDI), X-ray tube potential, and reconstruction algorithms to examine the impact of different scanning protocols on standardization performance.

SensorsVol. 25(9)
Yonsei University (KR)
National Research Foundation of Korea
Good health and well-being
Openalex Percentile: Top 19%
Lung Cancer Diagnosis and Treatment
1.52
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Standardization of Lung CT Number Using COPD Gene2 Phantom Under Various Scanning Protocols — Hoondong Song, Hanjoo Jang, et al. · Sensors (2025) | TGRS Research Map | TGRS