A Porcine Model of Transvertebral Ultrasound and Microbubble-Mediated Blood-Spinal Cord Barrier Opening
Bibliographic record
Abstract
Blood-spinal cord barrier opening, using focused ultrasound and microbubbles, has the potential to improve drug delivery for the treatment of spinal cord pathologies.Delivering and detecting ultrasound through the spine is a challenge for clinical translation.We have previously developed short burst, phase keying exposures, which can be used in a dual-aperture configuration to address clinical scale targeting challenges.Here we demonstrate the use of these pulses for blood-spinal cord barrier opening, in vivo in pigs. Methods:The spinal cords of Yorkshire pigs (n=8) were targeted through the vertebral laminae, in the lower thoracic to upper lumbar region using focused ultrasound (486 kHz) and microbubbles.Four animals were treated with a combination of pulsed sinusoidal exposures (1.0-4.0MPa, non-derated) and pulsed short burst, phase keying exposures (1.0-2.0MPa, non-derated).Four animals were treated using ramped short burst, phase keying exposures (1.8-2.1 MPa, non-derated).A 250 kHz narrowband receiver was used to detect acoustic emissions from microbubbles.Blood-spinal cord barrier opening was assessed by the extravasation of Evans blue dye.Histological analysis of the spinal cords was used to assess tissue damage and excised vertebral samples were used in benchtop experiments.Results: Ramped short burst, phase keying exposures successfully modified the blood-spinal cord barrier at 16/24 targeted locations, as assessed by the extravasation of Evans blue dye.At 4 of these locations, opening was confirmed with minimal adverse effects observed through histology.Transmission measurements through excised vertebrae indicated a mean transmission of (47.0 ± 7.0 %) to the target.Conclusions: This study presents the first evidence of focused ultrasound-induced blood-spinal cord barrier opening in a large animal model, through the intact spine.This represents an important step towards clinical translation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".