Copyright: ©Author(s) 2026.
World J Radiol. Apr 28, 2026; 18(4): 119851
Published online Apr 28, 2026. doi: 10.4329/wjr.v18.i4.119851
Published online Apr 28, 2026. doi: 10.4329/wjr.v18.i4.119851
Table 1 Baseline characteristics of the study population
| Characteristic | Value | |
| Age (years) | 59 (16-85) | |
| Sex | Male | 6 |
| Female | 15 | |
| Underlying disease | Hereditary hemorrhagic telangiectasia | 2 |
| Symptoms | Dyspnea | 4 |
| Hemoptysis | 1 | |
| Asymptomatic | 16 | |
| Comorbidities | Heart failure | 2 |
| Cerebral infarction | 3 | |
| SpO2 (%) | 96 (94-99) | |
| Treatment | Endovascular embolization | 14 |
| Surgery | 2 | |
| Conservative management | 5 | |
Table 2 Differences in computer-aided detection rates according to imaging conditions, n (%)
| Imaging conditions | Overall (image series, | Detection success (image series, n = 44) | Detection failure (image series, n = 30) | P value | |
| Contrast | Non-contrast | 33 | 19 (58) | 14 (42) | 0.29 |
| Pulmonary arterial phase | 24 | 17 (71) | 7 (29) | ||
| Parenchymal phase | 17 | 8 (47) | 9 (53) | ||
| Window setting | Lung window | 31 | 19 (61) | 12 (39) | 0.79 |
| Mediastinal window | 43 | 25 (58) | 18 (42) | ||
Table 3 Comparison of variables between successful and failed computer-aided detection
| Characteristic | Factors | Overall (n = 26) | Detection success (n = 17) | Detection failure (n = 9) | P value |
| Location | Right upper lobe | 7 | 3 | 4 | - |
| Right middle lobe | 3 | 2 | 1 | ||
| Right lower lobe | 4 | 3 | 1 | ||
| Left upper lobe | 3 | 2 | 1 | ||
| Lingular segment | 6 | 4 | 2 | ||
| Left lower lobe | 3 | 3 | 0 | ||
| Contact with adjacent structures | Present | 19 | 13 (68) | 6 (32) | 0.63 |
| Absent | 6 | 3 (50) | 3 (50) | ||
| Morphology1 | Simple type | 22 | 13 (59) | 9 (41) | 0.26 |
| Complex type | 4 | 4 (100) | 0 (0) | ||
| Treatment indication2 | Present | 18 | 13 (72) | 5 (28) | 0.38 |
| Absent | 8 | 4 (50) | 4 (50) | ||
| Feeding artery diameter (mm) | 3.4 (3.0, 4.0) | 3.4 (2.4, 4.8) | 0.47 | ||
| Maximum lesion length (mm) | 6.5 (4.9, 9.6) | 5.5 (2.5, 11.0) | 0.65 | ||
- Citation: Azama K, Tsuchiya N, Toyosato S, Yonemoto K, Nishie A. Artificial intelligence-based lung nodule detection for pulmonary arteriovenous fistulas on chest computed tomography. World J Radiol 2026; 18(4): 119851
- URL: https://www.wjgnet.com/1949-8470/full/v18/i4/119851.htm
- DOI: https://dx.doi.org/10.4329/wjr.v18.i4.119851
