Value of CT diagnostic techniques based on imaging post-processing systems in the early diagnosis and treatment of lung cancer

Abstract

Objective: To evaluate the application value of CT diagnostic technology based on the Shukun Imaging Post-Processing System for early screening and diagnosis of lung cancer.

Methods: A total of 35 patients diagnosed with lung cancer postoperatively and 53 patients with benign nodules were included in this retrospective study, all of whom were treated in the Department of Thoracic and Cardiovascular Surgery of the Second Affiliated Hospital of Fujian Medical University from January 2020 to December 2023. All patients underwent chest spiral CT examinations. Original thin-slice axial CT images were processed using Shukun software for three-dimensional reconstruction of the lesions, surrounding lung tissue, and trachea. The diagnoses and malignant risk indicators of pulmonary nodules were established based on the final imaging results.

Results: Statistical analysis showed that the sensitivity of Shukun processing technology in diagnosing early-stage lung cancer was 82.86%, with a specificity of 88.46%, when compared to postoperative pathological analysis. Univariate logistic regression analysis indicated that features such as burr sign, lobulation sign, pleural traction sign, vascular convergence sign, vacuole sign, and nodule size derived from Shukun processing had significant predictive value for malignant nodules (P<0.05).

Conclusion: Shukun processing technology can effectively reconstruct ordinary CT tomographic images into three-dimensional representations, enhancing the visualization of spatial relationships between the tumor and adjacent anatomical structures, including trachea, pleura, bronchi, and blood vessels. It has high clinical diagnostic value for the early diagnosis of malignant pulmonary nodules.

Keywords: Pulmonary nodule; Shukun imaging post-processing system; chest CT; diagnostic efficacy; lung cancer.

Figure 1

Pathological classification of lung cancer patients.

Figure 2

The AUC diagram of the diagnosis of pulmonary nodules by Shukun system.

Figure 3

Classic image of lung nodules. Three-dimensional reconstruction of pulmonary nodules using CT plain scan and Shukun post-processing technology. Panels (A) and (D) show the horizontal view of the left lower pulmonary nodule, panels (B) and (E) display the coronal view, and panels (C) and (F) present the three-dimensional reconstruction of the lung nodule generated by the post-processing system.

Figure 4

Comparison of serum tumor markers CEA, NSE, and CYFRA21-1 between the two groups. Note: CEA: carcinoembryonic antigen, NSE: neuron-specific enolase; CYFRA21-1: cytokeratin fragment 19.

Figure 5

Satellite focus and calcification of pulmonary nodules. A: Pulmonary nodules satellite focus; B: Calcification image.

Figure 6

Images of pulmonary nodular lobulation sign, pleural traction sign, vascular convergence sign and vacuole sign. A: Vacuole sign; B: Lobulation sign; C: Vascular convergence sign; D: Pleural traction sign.