TABLE 4.
Performance comparison of the Slice CNN methods by using different MRI parameters
| Model | Parameters | ACC | SEN | SPC | PPV | NPV | AUC |
|---|---|---|---|---|---|---|---|
| The single parameter model | Clinical | 0.659 | 0.778 | 0.613 | 0.420 | 0.885 | 0.680 |
| DWI | 0.667 | 0.579 | 0.690 | 0.333 | 0.860 | 0.609 | |
| CBF | 0.742 | 0.625 | 0.78 | 0.476 | 0.867 | 0.689 | |
| CBV | 0.667 | 0.929 | 0.58 | 0.417 | 0.967 | 0.702 | |
| MTT | 0.833 | 1.000 | 0.78 | 0.592 | 1.000 | 0.945 | |
| TTP | 0.818 | 0.875 | 0.80 | 0.583 | 0.952 | 0.889 | |
| The multi parameter model | MT | 0.853 | 0.925 | 0.827 | 0.658 | 0.969 | 0.896 |
| MTC | 0.863 | 0.882 | 0.859 | 0.556 | 0.973 | 0.913 | |
| DMT | 0.871 | 0.818 | 0.919 | 0.786 | 0.932 | 0.921 | |
| DMTC | 0.873 | 0.850 | 0.878 | 0.630 | 0.960 | 0.932 | |
| DMTC* | 0.871 | 0.820 | 0.865 | 0.611 | 0.943 | 0.927 |
Abbreviations: ACC, accuracy; AUC, area under the receiver‐operating characteristic curve; CBF, cerebral blood flow; CBV, cerebral blood volume; CNN, convolutional neural network; DMT, DWI & MTT &TTP; DMTC*, DWI & MTT & TTP & clinical of external validation set; DMTC, DWI & MTT & TTP & clinical; DWI, diffusion‐weighted imaging; MT, MTT&TTP; MTC, MTT&TTP& Clinical; MTT, mean transit time; NPV, negative predictive value; PPV, positive predictive value; SEN, sensitivity; SPC, specificity; TTP, time to peak.