Review of intraluminal optical coherence tomography imaging for cerebral aneurysms
Bibliographic record
Abstract
Cerebral aneurysms are an abnormal ballooning of blood vessels which have the potential to rupture and cause hemorrhagic stroke. The diagnosis, treatment, and monitoring of cerebral aneurysms is highly dependant on high resolution imaging. As an imaging modality capable of cross-sectional resolution down to 10 μm, intraluminal optical coherence tomography (OCT) has great potential in improving care for cerebral aneurysms. The ability to assess the blood vessel microanatomy in vivo may be able to predict aneurysm growth and rupture. During treatment, intraluminal OCT may aid in assessment of treatment efficacy and complication avoidance, such as via visualization of in-stent thrombosis, stent wall apposition, and the fate of covered branch vessels. This technology can also be used in post-treatment monitoring, to assess for aneurysmal remnants or for endothelialisation and healing over the diseased segments. The goal of this clinically focused narrative review is to provide an overview of the previous applications of intraluminal OCT in cerebral aneurysms and future prospects of applying this technology to improve care in patients with cerebral aneurysms, including a specific neurovascular OCT catheter, doppler OCT for high resolution blood flow assessment, and further research endeavors.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".