Table 7.
Summary for the validation BRATS dataset for low grade gliomas (LGG) and high grade gliomas (HGG) with the centrality metrics, clustering coefficient, and average path length for the tumor connectomes modeled. Results are shown with mean with standard deviation. MCC = Matthew Correlation Coefficient, AUC-PR = Precision Recall with Bootstrap Confidence Interval (CI).
| Glioblastoma | Degree Centrality | Betweenness Centrality | Eigenvector Centrality | Node Strength | Average Path Length | IsoSVM |
|---|---|---|---|---|---|---|
| Low Grade | 0.61 ± 0.15 | 0.00035 ± 0.00030 | 0.00021 ± 0.0003 | 0.10 ± 0.03 | 1.55 ± 0.31 | −0.56 ± 1.04 |
| High-Grade | 0.47 ± 0.17 | 0.00044 ± 0.00033 | 0.00042 ± 0.0004 | 0.13 ± 0.04 | 1.88 ± 0.41 | 0.53 ± 1.06 |
| p value | 0.000001 | 0.0025 | 0.0001 | 0.0001 | 0.0001 | 0.0001 |
| Sensitivity (%) | 67 | 77 | 77 | 68 | 71 | 72 |
| Specificity (%) | 75 | 43 | 63 | 72 | 71 | 75 |
| MCC | 0.41 | 0.22 | 0.19 | 0.40 | 0.41 | 0.46 |
| AUC-ROC | 0.75 (CI = 0.70–0.79) |
0.61 (CI = 0.56–0.65) |
0.57 (CI = 0.53–0.62) |
0.74 (CI = 0.69–0.77) |
0.74 (CI = 0.70–0.78) |
0.77 (CI = 0.73–0.81) |
| AUC-PR | 0.82 (CI = 0.77–0.86) |
0.67 (CI = 0.61–0.72) |
0.61 (CI = 0.55–0.67) |
0.80 (CI = 0.75–0.85) |
0.80 (CI = 0.74–0.84) |
0.82 (CI = 0.77–0.86) |