Ultrasound-stimulated microbubble radiation enhancement of tumors: Single-dose and fractionated treatment evaluation
Bibliographic record
Abstract
The use of ultrasound-stimulated microbubble therapy has successfully been used to target tumor vasculature and enhance the effects of radiation therapy in tumor xenografts in mice. Here, we further investigate this treatment using larger, more clinically relevant tumor models. New Zealand white rabbits bearing prostate tumor (PC3) xenografts received a single treatment of either ultrasound-stimulated microbubbles (USMB), ionizing radiation (XRT; 8Gy), or a combination of both treatments (USMB+XRT). Treatment outcome was evaluated 24 hours after treatment using histopathology, immunolabeling, 3D Doppler ultrasound and photoacoustic imaging. A second cohort of rabbits received multiple treatments over a period of three weeks, where USMB treatments were delivered twice weekly with daily XRT treatments to deliver a fractionated 2Gy dose five days per week. A significant decrease in vascular function, observed through immunolabeling of vascular endothelial cells, was observed in tumors receiving the combined treatment (USMB+XRT) compared to control and single treatment groups. This was associated with an increase in cell death as observed through in situ end labeling (ISEL), a decrease in vascular index measured by Power Doppler imaging, and a decrease in oxygen saturation. In rabbits undergoing the long-term fractionated combined treatment, a significant growth delay was observed after 1 week and a significant reduction in tumor size was observed after 3 weeks with combined therapy. Results demonstrated an enhancement of radiation effect and superior anti-tumor effect of the combination of USMB+XRT compared to the single treatments alone. Tumor growth was maximally inhibited with fractionated radiotherapy combined with the ultrasound-stimulated microbubble-based therapy.
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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".