A preliminary <i>in-vivo</i> porcine study of long pulse histotripsy for thrombolysis of intraventricular hemorrhagic clot
Bibliographic record
Abstract
Intraventricular hemorrhage is primarily a condition of premature babies where 40% will develop a form of bleeding that occupies >50% of the ventricles in the brain. Due to the fragile nature of patient, there is no treatment except the use of shunts for cerebrospinal fluid accumulation. Long pulse histotripsy (LPH) uses focused ultrasound pulses as a method to non-invasively target and mechanically break up the clot. An in-vivo IVH procine model has been developed and it is used to test the efficacy and safety of using LPH on a Philips Sonalleve. The IVH model has an average clot volume of 3986 mm3 and present in both ventricles. To simulate a neonatal patient, a craniotomy has been performed. The acoustic parameters used are as follows: freq. 1.2 MHz, 2x6 mm focus, 10 ms pulse duration, 10,000 cycles, 1% duty cycle, and acoustic power from 325 to 400 W. Sonication points were placed at the center of the IVH clot. Pre- and post-treatment T1-w, T2-w, and T2*-w MR imaging was completed. Change in the clot volume was measured by segmenting the MR images. The brains were harvested and stained with hematoxylin and eosin for histological examination. Results show that LPH targeted and reduced the clot volume by 28.5-36.7% with a phase change occurring at target. H&E staining showed that visible voids were generated in the clots. Based on early data, it appears that LPH can mechanically reduce the volume of IVH clots. Future work includes increasing the study number and conducting chronic studies to determine the changes to recovery.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".