Quantitative Anatomic Comparison of Microsurgical Transcranial, Endoscopic Endonasal, and Transorbital Approaches to the Spheno-Orbital Region

2021 ◽  
Author(s):  
Edoardo Agosti ◽  
Mario Turri-Zanoni ◽  
Giorgio Saraceno ◽  
Francesco Belotti ◽  
Apostolos Karligkiotis ◽  
...  

Abstract BACKGROUND The spheno-orbital region (SOR) is a complex anatomic area that can be accessed with different surgical approaches. OBJECTIVE To quantitatively compare, in a preclinical setting, microsurgical transcranial approaches (MTAs), endoscopic endonasal transpterygoid approach (EEA), and endoscopic transorbital approaches (ETOAs) to the SOR. METHODS These approaches were performed in 5 specimens: EEA, ETOAs (superior eyelid and inferolateral), anterolateral MTAs (supraorbital, minipterional, pterional, pterional-transzygomatic, and frontotemporal-orbitozygomatic), and lateral MTAs (subtemporal and subtemporal transzygomatic). All specimens underwent high-resolution computed tomography; an optic neuronavigation system with dedicated software was used to quantify working volume and exposed area for each approach. Mixed linear models with random intercepts were used for statistical analyses. RESULTS Anterolateral MTAs offer a direct route to the greater wings (GWs) and lesser wings (LWs); only they guarantee exposure of the anterior clinoid. Lateral MTAs provide access to a large area corresponding to the GW, up to the superior orbital fissure (SOF) anteriorly and the foramen rotundum medially. ETOAs also access the GW, close to the lateral portion of SOF, but with a different angle of view as compared to lateral MTAs. Access to deep and medial structures, such as the lamina papyracea and the medial SOF, is offered only by EEA, which exposes the LW and GW only to a limited extent. CONCLUSION This is the first study that offers a quantitative comparison of the most used approaches to SOR. A detailed knowledge of their advantages and limitations is paramount to choose the ideal one, or their combination, in the clinical setting.

2013 ◽  
Vol 74 (S 01) ◽  
Author(s):  
Francisco A. Filho ◽  
Rodrigo Cavalcante ◽  
Milton Rastelli ◽  
Omar Ramirez ◽  
Alessandro Paluzzi ◽  
...  

2013 ◽  
Vol 38 (4) ◽  
pp. 624-631
Author(s):  
Chang-You LIU ◽  
Bao-Jie FAN ◽  
Zhi-Min CAO ◽  
Yan WANG ◽  
Zhi-Xiao ZHANG ◽  
...  

1990 ◽  
Vol 73 (6) ◽  
pp. 1612-1624 ◽  
Author(s):  
J.L. Foulley ◽  
D. Gianola ◽  
M. San Cristobal ◽  
S. Im

2015 ◽  
Vol 54 (1) ◽  
pp. 101-109 ◽  
Author(s):  
Jurgita Židanavičiūtė ◽  
Audrius Vaitkus

The data were collected by researchers at the Road Research Institute, in a study investigating the impact of differentfactors on road surface strength. In this statistical analysis, we apply linear mixed models (LMMs) to clustered longitudinal data, inwhich the units of analysis (points in the road) are nested within clusters (sample of four different road segments), and repeatedmeasures of road strength in these different points are collected over time with unequally spaced time intervals. The data arebalanced – each cluster has the same number of units, which are measured at the same number of time points. Because of correlateddata and different clusters in which data could be correlated, linear regression models are not appropriate here, and therefore linearmixed models are applied.


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