Ruptured pial-pial collateral aneurysm associated with left internal carotid artery occlusion: nuances of surgical management. Illustrative case
Bibliographic record
Abstract
BACKGROUND: Carotid occlusion often leads to the formation of a collateral network. On rare occasions, due to hemodynamic influence, aneurysms can occur. Here, the authors describe a 69-year-old male presenting with intracerebral hemorrhage secondary to a ruptured aneurysm within such a network. OBSERVATIONS: The patient presented to the emergency department with an altered level of consciousness. Imaging showed a left temporal lobe hemorrhage extending into the ventricle, subdural hematoma, and evidence of contrast extravasation. Digital subtraction angiography revealed an occluded left internal carotid artery with the left middle cerebral artery territory reconstituted by flow through an external carotid artery-internal carotid artery anastomosis. The latter was formed by the superficial temporal artery-superior orbital artery, as well as pial-pial collaterals from the posterior temporal artery. Notably, a 4-mm aneurysm arising from the pial-pial collateral network was identified. Surgical intervention involved a left temporal craniectomy and aneurysm excision, with special attention paid to preserving the anastomotic flow through the superficial temporal artery. LESSONS: This case underscores the importance of recognizing and preserving collateral vascular pathways in cases of carotid occlusion with an associated aneurysm. It emphasizes the necessary balance between managing aneurysm risk and maintaining cerebral perfusion, highlighting the need for careful preoperative planning and intraoperative caution.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.003 |
| 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".