Volumetric measurement of paranasal sinuses and its clinical significance in pituitary neuroendocrine tumors operated using an endoscopic endonasal approach

Author:

Nakaya Masato,Tamura Ryota,Takahara Kento,Senuma Takumi,Yoshida Keisuke,Kitamura Yohei,Ueda Ryo,Toda Masahiro

Abstract

ObjectiveEndoscopic endonasal surgery (EES) for deep intracranial lesions has gained popularity following recent developments in endoscopic technology. The operability of invasive pituitary neuroendocrine tumors (PitNETs) depends on the anatomy of the nasal cavity and paranasal sinus. This study aimed to establish a simple volume reconstruction algorithm of the nasal cavity and paranasal sinus. Additionally, this is the first study to demonstrate the relationship between the segmentation method and the clinical significance in patients with PitNET.MethodsPre-and postoperative tumor volumes were analyzed in 106 patients with primary (new-onset) PitNETs (80 nonfunctioning and 26 functioning) who underwent EES. The efficiency and accuracy of the semiautomatic segmentation with manual adjustments (SSMA) method was compared with other established segmentation methods for volumetric analysis in the nasal cavity and paranasal sinuses. Correlations between the measured nasal cavity and paranasal sinus volumes and the extent of tumor removal were evaluated.ResultsThe SSMA method yielded accurate and time-saving results following the volumetric analyses of nasal cavity and paranasal sinuses with complex structures. Alternatively, the manual and semiautomatic segmentation methods proved time-consuming and inaccurate, respectively. The sphenoid sinus volume measured by SSMA was significantly correlated with the extent of tumor removal in patients with nonfunctioning Knosp grade 3 and 4 PitNET (r = 0.318; p = 0.015).ConclusionThe volume of sphenoid sinus potentially could predict the extent of resection due to better visualization of the tumor for PitNETs with CS invasion.

Publisher

Frontiers Media SA

Subject

Neurology (clinical),Neurology

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