Objective To investigate the effect of contrast enhancement on the diagnosis of interstitial lung abnormalities (ILA) in automatic quantitative CT measurement in patients with paired pre- and post-contrast scans. Materials and methods Patients who underwent chest CT for thoracic surgery between April 2017 and December 2020 were retrospectively analyzed. ILA quantification was performed using deep learning-based automated software. Cases were categorized as ILA or non-ILA according to the Fleischner Society’s definition, based on the quantification results or radiologist assessment (reference standard). Measurement variability, agreement, and diagnostic performance between the pre- and post-contrast scans were evaluated. Results In 1134 included patients, post-contrast scans quantified a slightly larger volume of nonfibrotic ILA (mean difference: −0.2%), due to increased ground-glass opacity and reticulation volumes (−0.2% and −0.1%), whereas the fibrotic ILA volume remained unchanged (0.0%). ILA was diagnosed in 15 (1.3%), 22 (1.9%), and 40 (3.5%) patients by pre- and post-contrast scans and radiologists, respectively. The agreement between the pre- and post-contrast scans was substantial (κ = 0.75), but both pre-contrast (κ = 0.46) and post-contrast (κ = 0.54) scans demonstrated moderate agreement with the radiologist. The sensitivity for ILA (32.5% vs. 42.5%, p = 0.221) and specificity for non-ILA (99.8% vs. 99.5%, p = 0.248) were comparable between pre- and post-contrast scans. Radiologist’s reclassification for equivocal ILA due to unilateral abnormalities increased the sensitivity for ILA (67.5% and 75.0%, respectively) in both pre- and post-contrast scans. Conclusion Applying automated quantification on post-contrast scans appears to be acceptable in terms of agreement and diagnostic performance; however, radiologists may need to improve sensitivity reclassifying equivocal ILA. Key Points <Emphasis Type="BoldItalic">Question</Emphasis> The effect of contrast enhancement on the automated quantification of interstitial lung abnormality (ILA) remains unknown. <Emphasis Type="BoldItalic">Findings</Emphasis> Automated quantification measured slightly larger ground-glass opacity and reticulation volumes on post-contrast scans than on pre-contrast scans; however, contrast enhancement did not affect the sensitivity for interstitial lung abnormality. <Emphasis Type="BoldItalic">Clinical relevance</Emphasis> Applying automated quantification on post-contrast scans appears to be acceptable in terms of agreement and diagnostic performance. Graphical Abstract

Effect of contrast enhancement on diagnosis of interstitial lung abnormality in automatic quantitative CT measurement

期刊论文
发表日期：

2025年6月3日

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Jaeyeon Choi,
Yura Ahn,
Youngjae Kim,
Han Na Noh,
Kyung-Hyun Do,
Joon Beom Seo,
Sang Min Lee

摘要

Objective

To investigate the effect of contrast enhancement on the diagnosis of interstitial lung abnormalities (ILA) in automatic quantitative CT measurement in patients with paired pre- and post-contrast scans.

Materials and methods

Patients who underwent chest CT for thoracic surgery between April 2017 and December 2020 were retrospectively analyzed. ILA quantification was performed using deep learning-based automated software. Cases were categorized as ILA or non-ILA according to the Fleischner Society’s definition, based on the quantification results or radiologist assessment (reference standard). Measurement variability, agreement, and diagnostic performance between the pre- and post-contrast scans were evaluated.

Results

In 1134 included patients, post-contrast scans quantified a slightly larger volume of nonfibrotic ILA (mean difference: −0.2%), due to increased ground-glass opacity and reticulation volumes (−0.2% and −0.1%), whereas the fibrotic ILA volume remained unchanged (0.0%). ILA was diagnosed in 15 (1.3%), 22 (1.9%), and 40 (3.5%) patients by pre- and post-contrast scans and radiologists, respectively. The agreement between the pre- and post-contrast scans was substantial (κ = 0.75), but both pre-contrast (κ = 0.46) and post-contrast (κ = 0.54) scans demonstrated moderate agreement with the radiologist. The sensitivity for ILA (32.5% vs. 42.5%, p = 0.221) and specificity for non-ILA (99.8% vs. 99.5%, p = 0.248) were comparable between pre- and post-contrast scans. Radiologist’s reclassification for equivocal ILA due to unilateral abnormalities increased the sensitivity for ILA (67.5% and 75.0%, respectively) in both pre- and post-contrast scans.

Conclusion

Applying automated quantification on post-contrast scans appears to be acceptable in terms of agreement and diagnostic performance; however, radiologists may need to improve sensitivity reclassifying equivocal ILA.

Key Points

Question The effect of contrast enhancement on the automated quantification of interstitial lung abnormality (ILA) remains unknown.

Findings Automated quantification measured slightly larger ground-glass opacity and reticulation volumes on post-contrast scans than on pre-contrast scans; however, contrast enhancement did not affect the sensitivity for interstitial lung abnormality.

Clinical relevance Applying automated quantification on post-contrast scans appears to be acceptable in terms of agreement and diagnostic performance.

Graphical Abstract