Table 1.
Clinical studies on computer-aided detection (CADe) for colorectal polyps.
| Author | Study design | CADe system | AI method | Study subjects, n | Outcomes, % |
|---|---|---|---|---|---|
| Park and Sargent 7 | Retrospective ex vivo | – | CNN | Training and testing sets: 562 images | Sensitivity 86 Specificity 85 |
| Billah and colleagues 8 | Retrospective ex vivo | – | CNN | Combined training and testing sets: 14,000 still images | Sensitivity 99 Specificity 99 |
| Yu, 2017 | Retrospective ex vivo | – | CNN | Training set: ASU-Mayo 20 videos Testing set: ASU-Mayo 18 videos |
Sensitivity 71 PPV 88 |
| Zhang, 2017 | Retrospective ex vivo | – | CNN | Training set: 2262 still images Testing set: 150 random + 30 NBI still images |
Sensitivity 98 PPV 99 Accuracy 86 |
| Misawa and colleagues 11 | Retrospective ex vivo | – | CNN | Training set: 411 videos Testing set: 135 videos |
Per-polyp sensitivity 94 Per-frame sensitivity 90 Specificity 63 False Positive 60 Accuracy 76 |
| Urban and colleagues 12 | Retrospective ex vivo | – | CNN | Multiple training sets: 8641 images, 1330 images, 9 videos, 53,588 images from videos, 11 challenging videos Testing set: 20 colonoscopy videos |
Sensitivity 90 AUC 0.991 Accuracy 96 False positive 7 |
| Yamada, 2018 13 | Retrospective ex vivo | – | CNN | Training set: 139,983 video images Testing set: 4840 video images |
Sensitivity 97 specificity 99 AUC 0.975 |
| Misawa and colleagues 14 | Ex vivo | – | CNN | Training set: 3,017,088 frames Testing set: 64 videos |
Sensitivity 86 False positive 26 |
| Klare and colleagues 15 | Prospective in vivo | – | CNN | Training set: not reported Testing set: 55 live colonoscopies |
Per-polyp sensitivity 75 ADR 29 (31 in endoscopist) |
| Ozawa and colleagues 16 | Ex vivo | – | CNN | Training set: 16,418 images Testing set: 7,077 still images |
Sensitivity 92 PPV 93 Accuracy 85 |
| Wang and colleagues 17 | Single-center RCT in vivo | EndoScreener | CNN | CADe patients with adenoma 151, total patients 522 Control patients with adenoma 109, total patients 536 |
ADR: WLI 20 vs CADe 29 |
| Wang and colleagues 18 | Single-center RCT in vivo | EndoScreener | CNN | CADe patients with adenoma 165, total patients 484 Control patients with adenoma 134, total patients 478 |
ADR: WLI 28 vs CADe 34 |
| Gong and colleagues 19 | Single-center RCT in vivo | ENDOANGEL | CNN | CADe patients with adenoma 54, total patients 324 Control patients with adenoma 26, total patients 318 |
ADR: WLI 8 vs CADe 16 |
| Repici and colleagues 20 | Multicenter RCT in vivo | GI-Genius | CNN | CADe group patients with adenoma 187, total patients 341 Control group patients with adenoma 139, total patients 348 |
ADR: WLI 40, 40.4 vs CADe 54 |
| Liu and colleagues 21 | Single-center RCT in vivo | HenanTongyu | CNN | CADe patients with adenoma 199, total patients 508 WLI patients with adenoma 124, total patients 518 |
ADR: WLI 24 vs CADe 39 |
| Su and colleagues 22 | Single-center RCT in vivo | AQCS | CNN | CADe group patients with adenoma 89, total patients 308 Control group patients with adenoma 52, total patients 315 |
ADR: WLI 16 vs CADe 28 |
| Wang and colleagues 23 | Single-center RCT in vivo | EndoScreener | CNN | CADe group patients with adenoma 124, total patients 184 Control group patients with adenoma 72, total patients 185 |
ADR: WLI 39 vs CADe 67 |
ADR, adenomas during colonoscopy; AI, artificial intelligence; AQCS, Automatic Quality Control System; AUC, area under the curve; CADe, computer-aided detection; CNN, convolutional neural network; NBI, narrow band imaging; PPV, positive predictive value; RCT, randomized controlled trials; WLI, white light imaging.