## 3 Results  
### Overall Survival Analysis  
The 2-year OS was 69% for the entire study cohort. Results of OS univariate Kaplan-Meier analyses of clinical characteristics and image features are summarized in Table 2 and Figure 3. For Kaplan-Meier analysis, HPV-positive (SR: 92.3%) showed a better prognosis of OS than HPV-negative (SR: 57%; \(p=0.037\)). In the same way, cases with TLG (\(p=0.029\)) lower than the optimal cut-off resulted in a higher survival rate (SR: 82.4%) compared to the high-value subgroup (SR: 50%). However, results were not statistically significant after multiple-testing correction. OS curves are shown for clinical characteristics and SUV\({}_{\text{max}}\) in Figure 3.  
Several textural and conventional features proved to be significant in predicting clinical outcomes in OS (See Table 3). Firstly, TLG (HR = 1.006 (1.003-1.009), \(p=0.001\)) was the most significant parameter. Shape and size parameters such as MTV (HR = 1.075 (1.025-1.126), \(p=0.003\)), with the highest HR, and Surface (HR = 1.000 (1.000-1.001), \(p=0.001\)) were also significant features. Three textural parameters corresponding to the GLRLM and GLZLM matrices were statistically significant. Nevertheless, none of the clinical features were statistically significant. Additionally, a multivariate Cox analysis was computed, including  
Figure 2: Fifty-eight-year-old male with squamous cell carcinoma of the right tonsil, which is shown to invade adjacent spaces of the oropharynx; especially significant is the invasion of muscular and adipose tissue nearby. Moreover, the tumor causes a reduction of the airway diameter. Intense and homogeneous [18]FFDG uptake is seen in all the malignant tissue as usually identified in these tumors. PET-CT in this case was also used for radiotherapy planning and as a basal study for therapeutic response in subsequent studies.  
only significant features in univariate analysis after multiple-testing correction. Only the TLG was retained in the multivariate model (HR = 1.006 (1.002-1.009), \(p\) = 0.001).  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Optimal Cut-off Value** & **Survival Rate (\%)** & \(p\)**-Value (Log-Rank Testb)** \\ \hline \multirow{3}{*}{HPV} & Negative (\(-\)) & 57.0 & \multirow{3}{*}{0.037} \\  & Positive (\(+\)) & 92.3 & & 0.037 \\ \cline{3-3}  & III & - & \\ \cline{3-3}  & IV & 63.2 & & 0.100 \\ \cline{3-3}  & Non-Tonsis & 73.0 & & \\ \cline{3-3}  & Tonsils & 65.0 & & 0.553 \\ \cline{3-3}  & Smoker & 66.3 & & 0.270 \\ \cline{3-3}  & Non-Smoker & - & & \\ \cline{3-3}  & \(<\)21.82 & 74.8 & & \\ \cline{3-3}  & \(\geq\)21.82 & 60.0 & & \\ \cline{3-3}  & \(<\)122.29 & 82.4 & & \\ \cline{3-3}  & \(\geq\)122.29 & 50.0 & & 0.029 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Univariate overall survival rates and log-rank tests for 2-year follow-up of relevant clinical characteristics, SUV\({}_{\text{max}}\), and significant image features before multiple-testing correction by means of the Benjamini–Hochberg procedure. No \(p\)-value was significant after multiple-testing correction.  
Figure 3: Kaplan-Meier curves of OS analysis for 2-year follow-up. Relevant clinical features are shown. **(a)**: HPV; **(b)**: tumor stage; **(c)**: tumor location; **(d)**: SUV\({}_{\text{max}}\). The Kaplan-Meier curve for smokers is not included due to the lack of representativeness of the non-smoker group.