## 3 Results  
For a single DBT image set, feature values deviated within <1% from the value averaged over the slices and over the GLCM direction calculation. This low deviation justified taking the average value for each feature, corresponding to a single DBT image set. A total of 15 features were extracted and five of them (all belonging to the second-order group, i.e., GLCM features) showed significant differences between ST and HR images (see Table 2). The scenario was unchanged when the analysis was repeated after varying the bits' resampling amplitude (i.e., 5-bit, 6-bit and 7-bit). The correlation matrix of the features showing a significant difference between ST and HR images is reported in Figure 2. The Correlation feature was not correlated with any other feature. The Contrast feature was strongly correlated with other features (Spearman-\(\rho\) = \(\pm\) 0.99 with a \(p\)-value < 0.001) except the Correlation feature (Spearman-\(\rho\) = 0.31 with a \(p\)-value = 0.14). Again, this scenario was unchanged for 5-bit, 6-bit and 7-bit resampling amplitudes. For this reason, further analysis only took into consideration the not correlated GLCM features, Contrast and Correlation. Figure 3 shows boxplots comparing these features in ST and HR images. Figure 4 contains boxplots of Mean and Variance features that showed no significant difference between ST and HR images. Finally, in Figure 5, we show the differences between ST and HR in 2D space employing the two most relevant features.  
\begin{table}
\begin{tabular}{c c} \hline \hline \multirow{2}{*}{**First-Order Features (Histogram)**} & Mean \\  & Variance \\  & Skewness \\  & Kurtosis \\ \hline \multirow{6}{*}{**Second-Order Features (GLCM)**} & Angular Second Moment \\  & Contrast \\  & Correlation \\  & Sum of Squares \\  & Inverse Difference Moment \\  & Sum Average \\  & Sum Variance \\  & Sum Entropy \\  & Entropy \\  & Difference Variance \\  & Difference Entropy \\ \hline \hline \end{tabular}
\end{table}
Table 1: Features considered in this study. See [22] and Supplementary Materials for definitions.  
\begin{table}
\begin{tabular}{l c c} \hline \hline  & \multicolumn{2}{c}{**\% Difference**} \\  & \multicolumn{2}{c}{**40\({}^{\circ}\)–15\({}^{\circ}\) Acquisition Angle**} \\  & \multicolumn{2}{c}{**(\(p\) < 0.05)**} \\ \hline
**First-Order Features (Histogram)** & & \\ \hline  & Contrast & +50\% \\  & Correlation & \(-\)5\% \\
**Second-Order Features (GLCM)** & Inverse Difference Moment & \(-\)14\% \\  & Difference Variance & +45\% \\  & Difference Entropy & +17\% \\ \hline \hline \end{tabular}
\end{table}
Table 2: Differences between feature median values calculated from the high-resolution (40\({}^{\circ}\) acquisition angle) and standard (15\({}^{\circ}\) acquisition angle) DBT images. Only significant differences are reported (\(p\) < 0.05, Wilcoxon signed-rank test).  
Figure 3: Boxplots of the non-correlated features Contrast (**a**) and Correlation (**b**). These features show a significant difference between 15\({}^{\circ}\) acquisition angle (standard mode) and 40\({}^{\circ}\) acquisition angle (high resolution mode) DBT images.  
Figure 2: Spearman rank correlation matrix for features showing a significant difference between 15\({}^{\circ}\) acquisition angle (standard mode) and 40\({}^{\circ}\) acquisition angle (high resolution mode) DBT images. Red and Blue elements indicate a positive and negative correlation, respectively, with a significance: \(p\) < 0.001. Crossed elements indicate that the correlation is not significant \(p\) > 0.05.