ISSN 1004-4140
CN 11-3017/P
YUE L Y, XU Y H, JIANG G L, et al. The Value of Subtraction Computed Tomography in Evaluating the Enhancement Degree of Thoracic Lesions[J]. CT Theory and Applications, 2024, 34(5): 1-6. DOI: 10.15953/j.ctta.2024.246. (in Chinese).
Citation: YUE L Y, XU Y H, JIANG G L, et al. The Value of Subtraction Computed Tomography in Evaluating the Enhancement Degree of Thoracic Lesions[J]. CT Theory and Applications, 2024, 34(5): 1-6. DOI: 10.15953/j.ctta.2024.246. (in Chinese).

The Value of Subtraction Computed Tomography in Evaluating the Enhancement Degree of Thoracic Lesions

  • Objective: This study aimed to explore the clinical use of the chest computed tomography (CT) subtraction technique for evaluating the degree of chest mass enhancement. Methods: Patients with suspected chest masses who underwent contrast-enhanced chest CT were retrospectively enrolled. Contrast-enhanced CT used was performed using lung subtraction. Subtraction images were reconstructed, and color fusion images of the iodine distribution in the chest masses in the arterial and venous phases were obtained after subtraction. The net enhancement value (∆Hu) was measured and calculated. The enhancement degree were divided into mild (∆Hu < 20 HU), moderate (∆Hu 20~40 HU), and significant (∆Hu > 40 HU). The CT subtraction iodine maps were visually evaluated. The net perfusion value (∆Husub) of CT lung subtraction iodine maps in arterial phase and venous phase was measured. McNemar and kappa tests were used to evaluate the difference and consistency of ∆Hu and ∆Husub degrees, respectively. The paired t test was used to compare the differences between ∆Hu and ∆Husub. Results: This study included 34 patients (37 lesions). Data measured by the three observers were in good agreement. The ∆Hu and ∆Husub degrees had no significant difference, but had good consistency. No significant differences were observed between ∆Hu and ∆Husub in the arterial and venous phases. Conclusion: Lung subtraction CT imaging can simplify the steps of image reading and report writing by reducing the measurement and calculation times for lung lesions without increasing scanning time, which contributes to improving the efficiency of diagnosis.
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