Abstract
The objective is to explore the value of artificial intelligence (AI) diagnostic system-assisted CT examination combined with serum tumor markers in the diagnosis of benign and malignant pulmonary nodules. 150 patients with pulmonary nodules diagnosed and treated in our hospital from April 2021 to September 2022 were selected and divided into benign group (n = 48) and malignant group (n = 102) according to postoperative pathological examination results. Logistic regression analysis was applied to analyze relationships among clinical and imaging features as well as benign and malignant pulmonary nodules. To observe the diagnostic value of AI-assisted CT combined with serum tumor markers for benign and malignant pulmonary nodules. Results showed that the multi-variate Logistic regression analysis indicated that spicule sign, vascular convergence sign and calcification were risk factors for malignant pulmonary nodules (P < 0.05). The sensitivity (97.06%) and accuracy (91.33%) of serum tumor markers combined with CT in the diagnosis of benign and malignant pulmonary nodules were higher than those of each alone. The Kappa index of combined diagnosis was higher than that of single diagnosis. Kappa index = 0.793, which was in good consistency with pathological diagnosis results. The conclusion is that the sensitivity and accuracy of AI diagnostic system-assisted CT examination combined with serum tumor markers in the diagnosis of benign and malignant pulmonary nodules are high, which has perfect consistency with pathological diagnosis results.
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Data availability
The labeled dataset used to support the findings of this study are available from the corresponding author upon request.
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The study was approved by the Institutional Review Board and Research Ethics Committee of the Shaanxi Provincial People’s Hospital, and was conducted in accordance to the tenets of the Declaration of Helsinki.
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Fan, W., Liu, H., Zhang, Y. et al. Value of CT examination combined with serum tumor markers assisted with artificial intelligence diagnostic system in the diagnosis of benign and malignant pulmonary nodules. Soft Comput (2023). https://doi.org/10.1007/s00500-023-09249-8
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DOI: https://doi.org/10.1007/s00500-023-09249-8