Table 5.

The $p$ values indicating whether the addition of a particular feature significantly improved classification ability over using the MRD alone when individual ROI pairs were used in the training of each model ($M_{\mathrm{Ind}}$). During validation, averages of changes in feature values were used.

Feature	A1	IBEX	Pyradiomics
Mean	$p<0.002$	$p<0.002$	$p<0.002$
Min	0.024	$\mathit{p}<\mathbf{0.002}$	0.024
Median	$p<0.002$	$p<0.002$	$p<0.002$
Entropy	$p<0.002$	$p<0.002$	$p<0.002$
GLCM sum average	$p<0.002$	$p<0.002$	$p<0.002$
GLCM sum entropy	$p<0.002$	$p<0.002$	$p<0.002$
GLCM difference entropy	$\mathit{p}<\mathbf{0.002}$	$\mathit{p}<\mathbf{0.002}$	$p<0.002$
GLCM entropy	$\mathit{p}<\mathbf{0.002}$	$\mathit{p}<\mathbf{0.002}$	$p<0.002$

Note: Bolded $p$-values indicate features that were considered significantly correlated with RP for $M_{\mathrm{Ind}}$ models but not for $M_{\mathrm{Avg}}$ models.