ISSN 1004-4140
CN 11-3017/P
WANG K, JI H Y, HUANG X Q, et al. Diagnostic Efficacy of Quantitative Computed Tomography in CTD-ILA/ILD[J]. CT Theory and Applications, 2025, 34(4): 611-620. DOI: 10.15953/j.ctta.2025.034. (in Chinese).
Citation: WANG K, JI H Y, HUANG X Q, et al. Diagnostic Efficacy of Quantitative Computed Tomography in CTD-ILA/ILD[J]. CT Theory and Applications, 2025, 34(4): 611-620. DOI: 10.15953/j.ctta.2025.034. (in Chinese).

Diagnostic Efficacy of Quantitative Computed Tomography in CTD-ILA/ILD

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  • Received Date: January 30, 2025
  • Revised Date: March 20, 2025
  • Accepted Date: March 23, 2025
  • Available Online: April 05, 2025
  • Objective: The aim of this study is to evaluate the diagnostic efficacy of quantitative computed tomography (CT) in differentiating between connective tissue disease-associated interstitial lung abnormalities (CTD-ILA) and connective tissue disease-associated interstitial lung disease (CTD-ILD), as well as to establish a screening protocol for connective tissue disease (CTD) patients based on quantitative CT. Methods: A total of 140 patients with CTD-ILD, 33 patients with CTD-ILA, and 109 healthy controls were enrolled. Quantitative indices were obtained using the 3D-Slicer software. Results: Significant differences in quantitative CT indices are observed among the groups. ROC analysis shows that the F%, GGO%, SD, and kurtosis are sensitive indicators for differentiating the control group from those with CTD-ILA/ILD. Notably, the best SD is demonstrated in the early diagnosis of both the CTD-ILA (AUC=0.862) and CTD-ILD (AUC=0.923) groups. Further distinguishing between CTD-ILA and CTD-ILD shows the strong discriminatory ability of the SD (AUC=0.649) and F% (AUC=0.617). Multivariable stepwise logistic regression analysis shows that F%, GGO%, SD, and kurtosis are statistically significant in differentiating the control group from the CTD-ILA/ILD groups. Conclusion: Quantitative CT is promising for the early diagnosis of CTD-ILA/ILD. Establishing a CTD screening protocol based on quantitative CT can facilitate precise patient management.

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