Table 3.
Matrix of Pearson correlation coefficients between endpoints listed in the respective rows and columns. VT and BP from the 1T-3k model were well correlated (r2>0.80) when derived using either graphical or numeric methods. Mean late-time SUV was more strongly correlated with numeric modeling endpoints (except VT 2T-5k) compared to graphical endpoints
| Graphical | Modeling | SUV | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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| VT Logan | BPLogan | BPReferenceLogan | VT 1T-3k | VT 2T-5k | BPSRTM | Mean | SD | Max | Skew | Kurtosis | AUC-CSH | ||
| Graphical | VT Logan | 1.000 | 0.897 | 0.750 | 0.812 | 0.197 | 0.854 | 0.642 | 0.580 | 0.677 | 0.022 | 0.006 | 0.020 |
| BPLogan | 1.000 | 0.877 | 0.875 | 0.641 | 0.943 | 0.756 | 0.670 | 0.792 | 0.008 | 0.000 | 0.034 | ||
| BPReferenceLogan | 1.000 | 0.842 | 0.681 | 0.984 | 0.836 | 0.621 | 0.832 | 0.000 | 0.002 | 0.009 | |||
| Modeling | VT 1T-3k | 1.000 | 0.538 | 0.870 | 0.838 | 0.699 | 0.835 | 0.008 | 0.000 | 0.035 | |||
| VT 2T-5k | 1.000 | 0.653 | 0.069 | 0.055 | 0.080 | 0.001 | 0.004 | 0.061 | |||||
| BPSRTM | 1.000 | 0.900 | 0.705 | 0.899 | 0.003 | 0.000 | 0.039 | ||||||
| SUV | Mean | 1.000 | 0.663 | 0.965 | 0.010 | 0.031 | 0.001 | ||||||
| SD | 1.000 | 0.824 | 0.124 | 0.057 | 0.191 | ||||||||
| Max | 1.000 | 0.002 | 0.003 | 0.013 | |||||||||
| Skew | 1.000 | 0.811 | 0.685 | ||||||||||
| Kurtosis | 1.000 | 0.725 | |||||||||||
| AUC-CSH | 1.000 | ||||||||||||