###### Abstract  
Among potential factors affecting the surgical resection in pituitary tumors, the role of tumor three-dimensional (3D) features is still unexplored. The aim of this study is to introduce the use of 3D virtual modeling for geometrical and morphological characterization of pituitary tumors and to evaluate its role as a predictor of total tumor removal. A total of 75 patients operated for a pituitary tumor have been retrospectively reviewed. Starting from patient imaging, a 3D tumor model was reconstructed, and 3D characterization based on tumor volume (Vol), area, sphericity (Spher), and convexity (Conv) was provided. The extent of tumor removal was then evaluated at post-operative imaging. Mean values were obtained for Vol (9117 \(\pm\) 8423 mm\({}^{3}\)), area (2352 \(\pm\) 1571 mm\({}^{2}\)), Spher (0.86 \(\pm\) 0.08), and Conv (0.88 \(\pm\) 0.08). Total tumor removal was achieved in 57 (75%) cases. The standard prognostic Knosp grade, Vol, and Conv were found to be independent factors, significantly predicting the extent of tumor removal. Total tumor resection correlated with lower Knosp grades (\(p\) = 0.032) and smaller Vol (\(p\) = 0.015). Conversely, tumors with a more irregular shape (low Conv) have an increased chance of incomplete tumor removal (\(p\) = 0.022). 3D geometrical and morphological features represent significant independent prognostic factors for pituitary tumor resection, and they should be considered in pre-operative planning to allow a more accurate decision-making process. p 2022 2022 2022 2022 2022 2022 2022 2022 2022 2022 2022 2022 2022 2022 2022 2022 2022 2022 2022 2022 2022 2022 2022 2022 2022 2022 202 2022 2022 2022 2022 2022 2022 2022 2022 2022 2022 22022 2022 2022 2022 2022 202 at post-operative neuroimaging remains an open issue [1, 3, 4, 5, 6, 7]. These neoplastic residuals may require a close follow-up, especially for peculiar histotypes, which have been demonstrated to be at higher risk of progression (i.e., sparsely granulated somatotroph, lactotroph, Crooke's cell, silent corticotroph, or plurihormonal Pit-1-positive tumors), or for tumors with higher Trouillas grades, such as 1B or 2B, according to a recently proposed score [8, 9, 10, 11]. Moreover, the incomplete tumor resection would lead to a lack of control of hormonal hyper-secretion, requiring adjunctive therapies such as specific endocrinological medications, radiation treatments, or second surgeries, or to the possible partial or full persistence of compressive symptoms [12, 13]. Many studies have focused on the possibility to pre-operatively predict the risk of incomplete tumor resection, in order to improve the pre-surgical planning and the overall treatment strategy and to guide the patient's counseling [14, 15, 16, 17, 18, 19]. One of the more relevant prognostic factors has been found to be the cavern sinus (CS) invasion, expressed by the Knosp grade [14, 15, 16, 17, 18, 19]. Indeed, the removal of adenomas extends into this peculiar anatomical structure, which contains cranial nerves (CNs), the internal carotid artery (ICA), and which receives the venous drainage from a large portion of the skull base, is often impaired [14, 15, 16, 17, 18, 19]. Moreover, the extensive infiltration of the bone or dural structures, the large or gigantic size of the adenoma, previous surgeries or radiotherapies, and fibrous consistency are reported as other negative prognostic factors for tumor resection [9, 14, 18, 20, 21, 22, 23, 24]. Among these studies, few have focused on the possible predictive role of three-dimensional (3D) geometry and morphology of the tumor [14, 15, 16, 17, 18, 19, 20, 22, 24]. In particular, they have not investigated if any 3D morphological feature could be associated with a higher risk of incomplete tumor removal, limiting to qualitative investigations [14, 15, 16, 17, 18, 19, 20, 21, 22, 24].