Continuous transcranial ultrasound in large vessel stroke: Image guidance for high‐intensity focused sonothrombolysis
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Sonothrombolysis is a potential adjunctive therapy for large vessel occlusion (LVO) stroke. Bedside ultrasound image-guided high-intensity focused ultrasound (HIFU) therapy could deliver higher energy therapeutic ultrasound to the thrombus with higher precision than what was previously accomplished in human trials. The aim is to test the feasibility of diagnostic transcranial contrast-enhanced ultrasound (CEUS) to image the occlusion site and continuously maintain the guidance image on-target for a sufficient exposure time for HIFU to be effective during LVO stroke evaluation and treatment. METHODS: This prospective, single center, observational cohort study included adult patients, presenting within 6 hours of stroke symptom onset, with LVO identified on computed tomography angiography (CTA). A hand-held CEUS imaging study was initiated following CTA and lasted up to 30 minutes. The primary outcome is the proportion of patients where a guidance CEUS image of the occlusion was achieved. RESULTS: A CEUS image of the occluded artery was obtained in 32/35 of the included patients. The median total imaging time was 23 minutes (interquartile range 15-30). Patients undergoing thrombectomy had a lower total imaging time (17 vs. 29.5 minutes, p = .002). When imaging was successful, on-target image was maintained for only 58% (standard deviation 23.8%) of total imaging time. No complications related to CEUS were observed. CONCLUSIONS: This feasibility study explored the use of diagnostic transcranial CEUS for continuous imaging of occlusion sites in LVO strokes. Challenges in maintaining target image during HIFU were identified, highlighting the need for technical advances for clinical application.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".