Comparison of Bolus Versus Dual-Syringe Administration Systems on Glass Yttrium-90 Microsphere Deposition in an In Vitro Microvascular Hepatic Tumor Model
Bibliographic record
Abstract
Purpose To utilize an in vitro microvascular hepatic tumor model to compare the deposition characteristics of glass yttrium-90 microspheres using the dual-syringe (DS) and traditional bolus administration methods. Materials and Methods The microvascular tumor model represented a 3.5-cm tumor in a 1,400-cm 3 liver with a total hepatic flow of 160 mL/min and was dynamically perfused. A microcatheter was placed in a 2-mm artery feeding the tumor model and 2 additional nontarget arteries. Glass microspheres with a diameter of 20–30 μm were administered using 2 methods: ( a ) DS delivery at a concentration of 50 mg/mL in either a single, continuous 2-mL infusion or two 1-mL infusions and ( b ) bolus delivery (BD) of 100 mg of microspheres in a single 3-mL infusion. Results Overall, the degree of on-target deposition of the microspheres was 85% ± 11%, with no significant differences between the administration methods. Although the distal penetration into the tumor arterioles was approximately 15 mm (from the second microvascular bifurcation of the tumor model) for all the cases, the distal peak particle counts were significantly higher for the DS delivery case (approximately 5 × 10 5 microspheres achieving distal deposition vs 2 × 10 5 for the BD case). This resulted in significantly higher deposition uniformity within the tumor model (90% for the DS delivery case vs 80% for the BD case, α = 0.05). Conclusions The use of this new in vitro microvascular hepatic tumor model demonstrated that the administration method can affect the deposition of yttrium-90 microspheres within a tumor, with greater distal deposition and more uniform tumor coverage when the microspheres are delivered at consistent concentrations using a DS delivery device. The BD administration method was associated with less favorable deposition characteristics of the microspheres.
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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 | 0.001 |
| 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) | 0.001 | 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".