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Record W4407250029 · doi:10.1055/s-0045-1803318

Impact of Removal of the Lateral Orbital Rim during Endoscopic Transorbital Approach (ETOA) on Intraorbital Pressure: A Cadaveric Study

2025· article· en· W4407250029 on OpenAlexaff
Antonio Strangio, Joel Davaine Sonfack, Marc-Olivier Comeau, Annie Moreau, Martin Côté, Pierre‐Olivier Champagne

Bibliographic record

VenueJournal of Neurological Surgery Part B Skull Base · 2025
Typearticle
Languageen
FieldMedicine
TopicMeningioma and schwannoma management
Canadian institutionsUniversité LavalCentre hospitalier de l'Université Laval
Fundersnot available
KeywordsCadaveric spasmMedicineSurgery

Abstract

fetched live from OpenAlex

Introduction: The endoscopic transorbital approach (ETOA) is being established as a new corridor for the lateral portion of the anterior and middle skull base. One of the main concerns of the approach is the risk of ophthalmological complications due to the retraction on the orbit. Removal of the lateral orbital rim (LOR) is a simple measure that widens the corridor and can potentially diminish injuries secondary to orbital retraction. The aim of the present study is to analyze the impact of removal of the LOR on the intraorbital pressure (IORP) during the various stages of ETOA. Methods: In this prospective cadaveric study, standard ETOA to the anterior and middle fossae were performed via a superior eyelid crease incision ([ Fig. 1 ]). On one side of the specimen, the LOR was preserved and one the other side LOR was removed. IORP was recorded with an intracranial pressure (ICP) probe during the entirety of the procedures ([ Fig. 2 ]). All specimens underwent a pre and post procedure CT scan to measure the volume of bone removal. Fig. 1: First steps of the procedure: (A) superior eyelid incision; (B) orbicularis oculi muscle fibers (dotted black line); (C) superolateral orbital rim (black asterisk) from the periorbita (red asterisk) with ICP probe (arrow); (D) lateral orbital rim (asterisk); (E) frontozygomatic suture (asterisk); (F) removed LOR (circle), temporal muscle (white asterisk), lateral GSW (arrow), and periorbita (black asterisk). Fig. 2 Endoscopic dissection: (A) peeling of the periorbita, (B) drilling of the GSW, (C) exposure of temporal dura, (C) peeling of lateral wall of cavernous sinus. SOF, superior orbital fissure; MOB, meningoorbital band; GG, gasserian ganglion. Results: Four specimens were used (8 sides, 4 with LOR removal, 4 without). Mean IORP was not statistically different between the two groups during the periorbita detachment step, which was prior to LOR removal (117.4 vs. 91.5 mm Hg, for the LOR removal group and LOR intact group, respectively, p = 0.217). IORP was then consistently reduced in the LOR removal group in every subsequent step ([ Fig. 3 ]): meningo-orbital band cutting (from 105.5 to 38.9 mm Hg, p = 0.002), temporal fossa drilling (from 85.3 to 69.5 mm Hg, p = 0.232), lateral greater sphenoid wing (GSW) drilling (from 99.8 to 49.9 mm Hg, p < 0.001), medial GSW drilling (from 85.6 to 17.2 mm Hg, p < 0.001), and cavernous sinus peeling (from 85.6 to 3.0 mm Hg, p < 0.001). LOR removal led to an increase in the total volume of bone removed: 6.2 to 9.4 cc ( p = 0.05). Fig. 3 IORP with and without LOR removal (statistically significant results marked with black asterisks). Conclusion: We observed a decrease in IORP with LOR removal, especially when working on the GSW and cavernous sinus and a significant increase in bone removal. These results support LOR removal to help decrease the retraction stress on the orbit and increase working corridor during ETOA. Publication History Article published online: 07 February 2025 © 2025. Thieme. All rights reserved. Georg Thieme Verlag KG Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.277
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractno

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