Table 1 Patient characteristics
From: A convolutional neural network-based system to classify patients using FDG PET/CT examinations
| n (%) | |
|---|---|
| Total patients | 3485 |
| Males | 1954 (56.1) |
| Females | 1531 (43.9) |
| Age (in years) | |
| Mean ± SD | 63.9 ± 13.6 |
| Range | 24–95 |
| Cancer-related biomarkers | Positive/Total (%) |
| AFP | 16/167 (9.6) |
| CA19–9 | 177/591 (29.9) |
| CEA | 282/889 (31.7) |
| CYFRA | 138/402 (34.3) |
| NSE | 381/621 (61.4) |
| PIVKA-II | 24/135 (17.8) |
| Pro-GRP | 95/540 (17.6) |
| PSA | 18/55 (32.7) |
| SCC | 172/784 (21.9) |
| S-hCG | 3/3 (100) |
| Pretest diagnosis | n (%) |
| Head and neck neoplasms | 988 (28.4) |
| Hematopoietic neoplasms | 510 (14.6) |
| Neoplasms of lung, pleura, or mediastinum | 507 (14.5) |
| Hepatobiliary neoplasms | 305 (8.8) |
| Gastrointestinal neoplasms | 258 (7.4) |
| Skin neoplasms | 168 (4.8) |
| Urologic neoplasms | 135 (3.9) |
| Gynecological neoplasms | 112 (3.2) |
| Sarcoidosis | 91 (2.6) |
| Breast neoplasms | 67 (1.9) |
| Brain and spinal neoplasms | 65 (1.9) |
| Others | 279 (8.0) |