Comparing Deposition Characteristics of Various Embolic Particles Using an In Vitro Prostate Microvasculature Model
Bibliographic record
Abstract
PURPOSE: To compare spatial distributions of radiopaque glass (RG) microspheres, tris-acryl gelatin (TAG) microspheres, and polyvinyl alcohol (PVA) nonspherical foam particles within a planar in vitro microvascular model of the hyperplastic hemiprostate. MATERIALS AND METHODS: A microvascular model simulating hyperplastic hemiprostate was perfused with a water-glycerin mixture. A microcatheter was positioned distal to the model's prostatic artery origin, and embolic particles (RG, 50 μm, 100 μm, and 150 μm; TAG, 100-300 μm and 300-500 μm; and PVA, 90-180 μm and 180-300 μm) were administered using a syringe pump. Microscopic imaging and subsequent semantic segmentation were performed to quantify particle distributions within the models. Distal penetrations were quantified statistically via modal analysis of the particle distributions. RESULTS: Maximum distal penetration was observed for RG microspheres of 50 μm, followed by RG microspheres of 100 μm and then TAG microspheres of 100-300 μm and RG microspheres of 150 μm. TAG microspheres of 300-500 μm, PVA particles of 90-180 μm, and PVA particles of 180-300 μm exhibited the lowest distal penetrations. The distal penetration metrics between groups were significantly different (P < .05) except between TAG microspheres of 100-300 μm and RG microspheres of 150 μm and between PVA particles of 90-180 and 180-300 μm. CONCLUSIONS: Comparing the spatial distributions of embolic particles in an in vitro microvascular model simulating the hyperplastic hemiprostate revealed that noncompressible particles and those with narrower size calibrations and smaller relative diameters exhibited higher degrees of distal packing. The embolization front was less distinct for particles with wider size calibrations, which resulted in smaller, more distal emboli along with larger, more proximal emboli. Both PVA particles and TAG microspheres of 300-500 μm exhibited relatively low overall distal penetration.
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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 | 0.000 |
| 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 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".