Table 3.
Diagnostic performances of DL-DCCP, Xception and RA-CEUS for the vulnerability evaluation of carotid plaque
| N | AUC (95% CI) |
Sensitivity (%) (95% CI) |
Specificity (%) (95% CI) |
PPV (%) (95% CI) |
NPV (%) (95% CI) |
LR+ (95% CI) |
LR− (95% CI) |
||
| DL-DCCP | Train | 136 | 0.85 (0.80 to 0.90) | 80.5 (69.9 to 88.7) | 76.3 (63.4 to 86.4) | 81.6 (71.0 to 89.6) | 75.0 (62.1 to 85.3) | 3.4 (2.1 to 5.4) | 0.3 (0.2 to 0.4) |
| Holdout validation | 69 | 0.87 (082 to 0.92) | 79.2 (57.9 to 92.9) | 84.4 (70.5 to 93.5) | 73.1 (52.2 to 88.4) | 88.4 (74.9 to 96.1) | 5.1 (2.5 to 10.4) | 0.2 (0.1 to 0.5) | |
| Xception | Train | 136 | 0.82 (0.76 to 0.88) | 74.0 (62.8 to 83.4) | 78.0 (65.3 to 87.7) | 81.4 (70.3 to 89.7) | 69.7 (57.2 to 80.4) | 3.4 (2.0 to 5.5) | 0.3 (0.2 to 0.5) |
| Holdout validation | 69 | 0.77 (0.71 to 0.83) | 75.0 (53.3 to 90.2) | 75.6 (60.5 to 87.1) | 62.1 (42.0 to 79.3) | 85.0 (0.70 to 0.94) | 3.1 (1.7 to 5.4) | 0.3 (0.2 to 0.7) | |
| RA-CEUS | Train | 136 | 0.69 (0.61 to 0.75) | 89.6 (82.8 to 96.4) | 47.5 (34.7 to 60.2) | 69.0 (59.9 to 78.1) | 77.8 (64.2 to 91.4) | 1.7 (1.3 to 2.2) | 0.2 (0.1 to 0.4) |
| Holdout validation | 69 | 0.66 (0.56 to 0.76) | 87.5 (74.3 to 100) | 44.4 (29.9 to 59.0) | 45.7 (31.3 to 60.0) | 87.0 (73.2 to 100) | 1.5 (1.1 to 2.1) | 0.2 (0.1 to 0.8) |
AUC, area under the curve; DL-DCCP, deep learning-based detection and classification of carotid plaque; LR−, negative diagnostic likelihood ratio; LR+, positive diagnostic likelihood ratio; NPV, negative predictive value; PPV, positive predictive value; RA-CEUS, classification of carotid plaque by radiologists manually examination contrast-enhanced ultrasound video.