## 4 Discussion
The observation that the resection of tumors invading the CS is challenging dates back to 1955, when [PERSON] et al. defined this, and it has remained valid until today [3; 17; 19; 44]. Particularly, considering the predictive roles of the different Knosp grades, we have found that the higher grade (grade 4) was associated with a significantly worse outcome. This can be explained considering that, as shown by [PERSON] et al. [3], and recently confirmed by other studies, only for Knosp 4 grade is it possible to pre-operatively predict the presence of an effective CS invasion by the tumor [3; 17; 19]. Indeed, in a previous paper of our group, we found that for the grades from 1 to 3B, only 43% of cases were found to be invasive at surgical inspection [19]. However, the Knosp grading system essentially remains an evaluation performed on planar (2D) images. In previous works, the possible benefit of a 3D-based evaluation has been mainly limited to qualitative studies, mostly based on the surgeon's judgment of the tumor morphology at the pre-operative MRI, with consequent limitations to correlate and quantify the role of specific 3D parameters with the tumor resection rate [16; 20; 21; 22; 23; 44]. As was expected, the tumor volume (Vol) also presented an independent prognostic role. Indeed, larger tumors, particularly gigantic ones, are often a challenge for the surgeon. Our observation that Conv has a major prognostic role for tumors with the same Vol confirms the conclusion by [PERSON] et al. that giant pituitary tumors can be effectively approached through an EEA, when they present a regular profile [50]. Therefore, we can conclude that it could be extremely useful to analyze the tumor using a 3D approach, since it allows to take into account the presence of a multi-lobular shape or irregularities in its profile, as well as to evaluate possible CS invasion and size via commonly used 2D-based grading systems. This may help the surgeon to plan a correct treatment of a pituitary adenoma. With this study, we would like to emphasize the prognostic role of tumor 3D geometry and morphology, which are usually underestimated in comparison to standard parameters such as size or invasiveness. As a future perspective of this pilot study, a software tool may be provided to automatically calculate the Spher and Conv parameters starting from reconstructed 3D models of the tumor. The adoption of this tool may be included in the clinical image-based evaluation path of the patient, thus allowing the surgeon to have an additional aid during pre-operative planning for a more accurate decision-making process. As previously suggested in similar experiences reported for urological surgery [51; 52], the proposed 3D-based approach should be considered complementary to the existing staging/scoring system, since the 3D-derived features may provide additional volumetric and morphological parameters that could not be evaluated on 2D images. The combination of 3D and 2D indexes may be used to define new scoring systems for better characterizing and understanding the complexity of tumors and for predicting complications, thus helping surgeons in planning the surgical approach. The major limitations of this study are its retrospective nature and the number of cases enrolled. Indeed, although our very strict selection criteria for pre-operative MRI quality have permitted us to collect a homogenous cohort, this has led to a reduction in the sample size. Due to this limitation, the confidence intervals observed in the statistical analysis for some parameters are large. Moreover, due to a possible selection bias, few cases were not naive, and this may have affected the correct interpretation of the prognostic role of this condition. A further bias is the lack of consideration of tumor consistency or histotypes, which have not been included in the analysis because they are not predictable before surgery, and our aim was to assess what pre-operative factors can be effectively adopted to predict the surgical outcome.