Intraoperative indocyanine green videoangiography to guide decision making regarding need for vessel bypass: A case report and technical note
Bibliographic record
Abstract
BACKGROUND: Indocyanine green (ICG) videoangiography is an intraoperative technique recently used in vascular neurosurgery to assess the presence or absence of blood flow during critical times of a procedure. These include, but are not limited to, detecting whether daughter branches or perforators are patent after placing a vascular clip or determining whether an aneurysm has been completely isolated from the cerebral circulation after clipping. We present a case of a less-commonly reported application of ICG videoangiography involving the selection of a vessel to act as the bypass recipient once the need is identified during the surgical treatment of a complex intracranial aneurysm. CASE DESCRIPTION: A 51-year-old male presented with a ruptured dissecting superior cerebellar artery (SCA) aneurysm that had two branches arising from the dome. Due to the difficult morphology of this aneurysm, a superficial temporal artery to SCA bypass was planned. We used ICG videoangiography to identify the branch that had insufficient retrograde flow via collateral circulation, to which the bypass was performed, followed by the isolation of the aneurysm from the cerebral circulation using permanent surgical clips. CONCLUSION: Our case represents a possible use of ICG videoangiography during the operative treatment of a difficult aneurysm. Our patient suffered no infarcts postoperatively. In the correct clinical context, this method represents a possible treatment option for complex aneurysms requiring a bypass.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.008 | 0.005 |
| 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".