Optical Coherence Tomography of Spontaneous Basilar Artery Dissection in a Patient With Acute Ischemic Stroke
Bibliographic record
Abstract
The diagnosis of intracranial arterial dissection (IAD) may be challenging and multimodal imaging techniques are often needed to confirm the diagnosis. Previous studies have based their criteria for diagnosis of IAD on conventional angiography, computed tomography or magnetic resonance imaging. We report a case with acute ischemic stroke due to spontaneous basilar artery dissection in which intravascular optical coherence tomography (OCT) was used to show features of IAD. A 59-year-old woman presented with symptoms of acute ischemic stroke. Thrombosis related to basilar artery (BA) stenosis was assumed on conventional angiography; however, no clot was retrieved after mechanical thrombectomy (MT) and a restored BA caliber was observed after a rescue recanalization with the detachment of a self-expanding stent was performed. Spontaneous IAD was suspected; however, angiographic findings were ambiguous for confirming IAD. The patient remained symptom-free until 18-month follow-up. At this point, angiography showed restenosis at the proximal tapered length of the stent. In vivo OCT was performed to assess the pathological changes of the restenosis and confirm the diagnosis of IAD.OCT revealed BA dissection with the presence of remnant transverse flap, double lumen and mural hematoma. Imaging at multiple levels identified intimal disruption that originated in the right vertebral artery and extended distally to the BA. The use of intravascular imaging with OCT enabled the accurate diagnosis of IAD. Care should be taken as the procedure may add additional risks to the patient. Future studies are needed to validate the safety of OCT in IAD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".