TABLE II.

AUC values comparing performance of RADISTAT (ϱ) against region-wise and voxel-wise radiomic descriptors, as well as combinations thereof, via an LDA classifier. Discovery AUCs (across 50 runs of 3-fold cross validation) as well as hold-out validation AUCs are shown for each classification task, with the top-performing strategy bolded.

Classification Task			Top 4 Voxel-wise GLCM ξ	Top 4 Region-wise GLCM ς	RADISTAT ϱ	Top 4 Voxel-wise GLCM + RADISTAT [ξ, ϱ]	Top 4 Region-wise GLCM + RADISTAT [ς, ϱ]
RCa: Metastatic vs Non-metastatic	2D	Discovery (μ ± σ)	0.52 ± 0.08	0.51 ± 0.08	0.81 ± 0.04*, **	0.77 ± 0.04*	0.74 ± 0.05**
		Validation	0.49	0.51	0.72	0.70	0.57
	3D	Discovery (μ ± σ)	0.62 ± 0.08	0.50 ± 0.08	0.78 ± 0.04*, **	0.74 ± 0.04*	0.69 ± 0.07**
		Validation	0.67	0.51	0.72	0.75	0.57
GBM: Progression vs PsP	2D	Training (μ ± σ)	0.50 ± 0.06	0.52 ± 0.05	0.68 ± 0.03*, **	0.65 ± 0.04*	0.67 ± 0.04**
		Validation	0.52	0.63	0.68	0.60	0.72
	3D	Training (μ ± σ)	0.59 ± 0.06	0.49 ± 0.07	0.62 ± 0.06*, **	0.67 ± 0.04 *	0.64 ± 0.06**
		Validation	0.61	0.59	0.63	0.59	0.60

μ: mean AUC; σ: standard deviation of AUC (across all cross-validation runs)

^*: adjusted p ≤ 0.05 when comparing AUCs between a descriptor and ξ

^**: adjusted p ≤ 0.05 when comparing AUCs between a descriptor and ς

All p-values corrected for multiple comparisons using Bonferonni’s correction