Contralateral Precaruncular Approach to the Lateral Sphenoid Sinus—A Case Report Detailing a New, Multiportal Approach to Lesions, and Defects in the Lateral Aspect of Well-Pneumatized Sphenoid Sinuses
Bibliographic record
Abstract
INTRODUCTION: Conventional surgical approaches to the lateral aspect of a well-pneumatized sphenoid sinus are associated with significant surgical morbidity. Transorbital endoscopic approaches have recently gained favor as an alternative approach to the skull base. We describe the use of a contralateral precaruncular endoscopic approach to provide a surgical pathway to the lateral aspect of the sphenoid sinus, allowing for improved and direct visualization of the surgical field, with limited morbidity. CASE REPORT: A 60-year-old female patient, with a spontaneous cerebrospinal fluid leak from a Sternberg canal defect in the sphenoid sinus, underwent repair of the defect at Groote Schuur Hospital (Cape Town, South Africa). A contralateral precaruncular approach, using the left medial orbital portal, was utilized to access the defect in the lateral aspect of a well-pneumatized right sphenoid sinus. Computer modeling software was used to predetermine the surgical pathway, and the case was performed under navigation guidance. Adequate surgical access was obtained to the lateral sphenoid sinus and sinus defect, with superior visualization compared to a pure transnasal or transpterygoid approach to the lateral sphenoid sinus. CONCLUSIONS: This case validates the use of computer simulation to plan and decide on the best operative approaches in skull base surgery and describes the contralateral precaruncular approach as a surgical pathway to the lateral sphenoid sinus. Advantages of the contralateral precaruncular approach include a direct trajectory toward the sinus defect, easy access with a standard 18-cm, 4-mm, 0-degree rigid endoscope, and straight instruments, with sparing of the pterygoid base and contents of the pterygopalatine fossa.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".