## 3 Results
### Texture Analysis  
No texture features showed statistically significant variation between pre- and post-RT on both the ADC maps and CE-MRI T1w sequences in group 1 (\(p\)-value \(>\) 0.01). The same results were found for group 2 on the CE-MRI T1w sequences (\(p\)-value \(>\) 0.01). On the contrary, in group 2, the ADC map values of the parotid and submandibular glands observed before RT were significantly different than those observed after RT (\(p\)-value \(<\) 0.01) (Table 4). \begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**Patients**} & \multicolumn{3}{c}{**Stage**} \\ \cline{2-3}  & **T** & **N** \\ \hline Group 1 & & \\ Patient 1 & 3 & 2c \\ Patient 2 & 3 & 3 \\ Patient 3 & 2 & 1 \\ Patient 4 & 3 & 2b \\ Patient 5 & 4a & 2b \\ Patient 6 & 3 & 0 \\ Patient 7 & 2 & 0 \\ Patient 8 & 4b & 0 \\ Patient 9 & 2 & 2b \\ Patient 10 & 4a & 2b \\ Patient 11 & 2 & 2c \\ Patient 12 & 4a & 2a \\ Patient 13 & 4a & 1 \\ Patient 14 & 3 & 0 \\ Patient 15 & 2 & 0 \\ Patient 16 & 2 & 2a \\ Patient 17 & 2 & 1 \\ Patient 18 & 3 & 2c \\ \hline Group 2 & & \\ Patient 19 & 3 & 2c \\ Patient 20 & 3 & 1 \\ Patient 21 & 2 & 2b \\ Patient 22 & 4a & 2c \\ Patient 23 & 1 & 2b \\ Patient 24 & 1 & 2b \\ Patient 25 & 3 & 2a \\ Patient 26 & 4a & 2c \\ Patient 27 & 1 & 2b \\ \hline \hline \end{tabular}
\end{table} 
Table 1: T and N stages at baseline for the patients with mild xerostomia (Group 1) and moderate xerostomia (Group 2). Two features were statistically significant for the parotid glands:  
* Informational measure of correlation 1 (IMC 1)--Gray level co-occurrence matrix class. * Informational measure of correlation 2 (IMC 2)--Gray level co-occurrence matrix class. Three features were statistically significant for the submandibular glands:
* Informational measure of correlation 2 (IMC 2)--First-order class. * Gray Level Non-uniformity Normalized (GLNN)--First-order class. * Gray Level Non-uniformity Normalized (GLNN)--Gray Level Run Length Matrix class. After producing ROC curves on the pre-RT values, only the feature IMC 1 for the parotid glands showed an acceptable level of diagnostic accuracy (AUC = 0.727) (Figure 4). The cut-off value defined by the ROC curve for IMC 1 in the pre-RT population was \(-1.473\)\(\times\)\(10^{-11}\), which allowed the distinction between group 1 and group 2 with 73% sensitivity, 75% specificity, and 75% diagnostic accuracy. Values lower than \(-1.473\)\(\times\)\(10^{-11}\) corresponded to moderate xerostomia (group 2), and values higher than \(-1.473\)\(\times\)\(10^{-11}\) corresponded to mild xerostomia (group 1). \begin{table}
\begin{tabular}{c c} \hline
**Feature Name** & _p_**-Value** \\ \hline \hline \multicolumn{2}{c}{Parotid} \\ Informational measure of correlation 1 (Gray Level Run Length Matrix) & 0.002 \\ Informational measure of correlation 2 (Gray Level Run Length Matrix) & 0.003 \\ \hline \multicolumn{2}{c}{Submandibular} \\ Gray Level Non-Uniformity Normalized (First Order) & 0.002 \\ Informational measure of correlation 2 (First Order) & 0.006 \\ Gray Level Non-Uniformity Normalized (Gray Level Run Length Matrix) & 0.006 \\ \hline \end{tabular}
\end{table} 
Table 4: _p_-values for statistically significant texture features. See Table A1 (Appendix A) for the definition of First Order and Gray Level Run Length Matrix. \begin{table}
\begin{tabular}{c c} \hline \hline \multicolumn{2}{c}{**Parameter**} & \multicolumn{2}{c}{_p_**-Value**} \\ \cline{2-3}  & **Group 1** & **Group 2** \\ \hline \hline \multicolumn{2}{c}{DWI MRI} \\ \multicolumn{2}{c}{ADC Parotid} & 0.82 & 0.18 \\ \multicolumn{2}{c}{ADC Submandibular} & 0.60 & 0.54 \\ \hline \hline \multicolumn{2}{c}{DCE-PWI MRI} \\ \multicolumn{2}{c}{AUC PAROTID} & 0.07 & 0.03 \\ \multicolumn{2}{c}{AUC SUBMANDIBULAR} & 0.26 & 0.21 \\ \multicolumn{2}{c}{KTRANS PAROTID} & 0.18 & 0.13 \\ \multicolumn{2}{c}{KTRANS SUBMANDIBULAR} & 0.65 & 0.82 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _p_-values for the parameters studied in group 1 (mild xerostomia) and group 2 (moderate xerostomia) on DWI and DCE-PWI sequences.