## 3 Results
Other considered 3D-based factors, including Spher and Area, were not significantly associated with the extent of tumor resection and thus were not included in the final model. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & & **No. of Patients** & **\%** \\ \hline [PERSON] & 1 & 6 & 8\% \\  & 2 & 43 & 57.4\% \\  & 3 & 16 & 21.3\% \\  & 4 & 10 & 13.3\% \\ \hline [PERSON] & A & 33 & 44\% \\  & B & 30 & 40\% \\  & C & 3 & 4\% \\  & D & 1 & 1.3\% \\  & E & 8 & 10.7\% \\ \hline [PERSON] & 0 & 26 & 34.7\% \\  & 1 & 10 & 13.3\% \\  & 2 & 18 & 24\% \\  & 3 & 16 & 21.3\% \\  & 4 & 5 & 6.7\% \\ \hline Zurich Score & 1 & 5 & 6.7\% \\  & 2 & 59 & 78.6\% \\  & 3 & 6 & 8\% \\  & 4 & 5 & 6.7\% \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Neuoradiological pre-operative features of the patients. Knosp grade is significantly correlated with the extent of tumor resection, and the logistic regression permitted to identify that grade 4 is associated with an increased risk of incomplete tumor resection (z score = 1.94, \(p\) = 0.05). Among 3D-based parameters, the Vol was found to be directly associated with the risk of incomplete tumor resection (z score 2.44, \(p\) = 0.01), confirming that for smaller tumors, the chances of complete tumor resection are higher. Particularly, the Odds Ratio was 1.02, meaning that for each increase of 100 mm\({}^{3}\) of Vol, the probability of incomplete tumor resection increases by 2%. Conversely, the Conv was found to be inversely associated with the risk of incomplete tumor resection (z score = \(-\)2.35, \(p\) = 0.02). Indeed, this index increases for more convex tumors and decreases for lesions with many irregularities in the shape, such as hollows or indentations. Therefore, our result demonstrates that adenomas with a reduced Conv, i.e., with a more irregular shape, have an increased chance of incomplete tumor removal. To investigate the role of these three parameters (Vol, Conv, and Knosp grade) in determining the more favorable outcome, we observed that at univariate logistic regression, only the Conv confirmed its statistical significance (Table 5). Bivariate analysis combining the extent of total tumor resection with Vol and Conv, as well as with Conv and Knosp \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Parameter** & **z** & \(p\) & **95\% Conf. Interval** &
\begin{tabular}{c} **Odds** \\ **Ratio** \\ \end{tabular} \\ \hline \multicolumn{2}{c}{Sex} & \(-\)1.43 & 0.15 & 0.31 & 1.72 & \\ \hline \multicolumn{2}{c}{Pre-treat} & 1.07 & 0.29 & 0.15 & 582.45 & \\ \hline \multicolumn{2}{c}{Hardy} & \(-\)0.74 & 0.46 & 0.19 & 2.09 & \\ \hline \multirow{3}{*}{Knosp} & 2 & 0.54 & 0.59 & 0.45 & 743.09 & 18.2 \\  & 3 & 1.06 & 0.29 & 0.20 & 205.21 & 6.5 \\  & 4 & 1.94 & **0.05** & 1.6 & 1582.61 & 50.5 \\ \hline \multirow{3}{*}{Tumor} & PRL & 0.53 & 0.59 & 0.05 & 158.28 & \\  & ACTH & \(-\)0.09 & 0.93 & 0.01 & 177.43 & \\ \cline{1-1}  & NF & \(-\)1.52 & 0.13 & 0.01 & 2.06 & \\ \hline \multicolumn{2}{c}{ICD} & \(-\)0.47 & 0.54 & 0.68 & 1.27 & 0.9 \\ \hline \multicolumn{2}{c}{Vol} & 2.44 & **0.01** & 1.01 & 1.03 & 1.02 \\ \hline \multicolumn{2}{c}{Conv} & \(-\)2.35 & **0.02** & 0.69 & 0.97 & 0.8 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Results of logistic regression. The three factors that were independently significantly associated with the extent of tumor resection were Knosp grade, the tumor volume (Vol), and the tumor convexity (Conv). The other potential predictors (Age, Wilson grade, Horizontal Diameter, Sphericity, Area, Zurich Score) were not statistically significant in univariate analysis and they were not included in the final model. For Knosp grade, Odds Ratios referred to Knosp grade 1 (ICD: inter-carotid distance, Vol: volume, Conv: convexity, Pre-Treat: previous treatment, Conf. : confidence). The bold data indicating a statistically significant result.