Artificial intelligence-based lung nodule detection for pulmonary arteriovenous fistulas on chest computed tomography

Figure 1 Enrollment flow chart. Flow diagram illustrating the selection of patients and lesions included in the study. PAVFs: Pulmonary arteriovenous fistulas; CT: Computed tomography; CAD: Computer-aided detection.

Figure 2 Detection and measurement of a pulmonary arteriovenous fistula using an artificial intelligence-based computer-aided detection system. A representative example of a pulmonary arteriovenous fistula detected on chest computed tomography by the artificial intelligence-based computer-aided detection (CAD) system is shown. The CAD system automatically identified the pulmonary arteriovenous fistula and provided quantitative measurements, including maximum lesion length and lesion volume. The lower panel shows a magnified view of the detected lesion, demonstrating the quantitative parameters generated by the CAD system.

Figure 3 Correlation of lesion measurements between the computer-aided detection system and manual assessment. Pearson’s correlation coefficient (r) and corresponding P values are shown. A and B: Scatter plots demonstrating the correlation between computer-aided detection-measured maximum lesion length and computer-aided detection-measured lesion volume and the manually measured maximum lesion length. CAD: Computer-aided detection.