A Road Map to the Internal Carotid Artery in Expanded Endoscopic Endonasal Approaches to the Ventral Cranial Base
Bibliographic record
Abstract
BACKGROUND: Injuring the internal carotid artery (ICA) is a feared complication of endoscopic endonasal approaches. OBJECTIVE: To introduce a comprehensive ICA classification scheme pertinent to safe endoscopic endonasal cranial base surgery. METHODS: Anatomic dissections were performed in 33 cadaveric specimens (bilateral). Anatomic correlations were analyzed. RESULTS: Based on anatomic correlations, the ICA may be described as 6 distinct segments: (1) parapharyngeal (common carotid bifurcation to ICA foramen); (2) petrous (carotid canal to posterolateral aspect of foramen lacerum); (3) paraclival (posterolateral foramen lacerum to the superomedial aspect of the petrous apex); (4) parasellar (superomedial petrous apex to the proximal dural ring); (5) paraclinoid (from the proximal to the distal dural rings); and (6) intradural (distal ring to ICA bifurcation). Corresponding surgical landmarks included the Eustachian tube, the fossa of Rosenmüller, and levator veli palatini for the parapharyngeal segment; the vidian canal and V3 for the petrous segment; the fibrocartilage of foramen lacerum, foramen rotundum, maxillary strut, lingular process of the sphenoid bone, and paraclival protuberance for the paraclival segment; the sellar floor and petrous apex for the parasellar segment; and the medial and lateral opticocarotid and lateral tubercular recesses, as well as the distal osseous arch of the carotid sulcus for the paraclinoid segment. CONCLUSION: The proposed endoscopic classification outlines key anatomic reference points independent of the vessel's geometry or the sinonasal pneumatization, thus serving as (1) a practical guide to navigate the ventral cranial base while avoiding injury to the ICA and (2) further foundation for a modular access system.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".