Validation of structural effects mediated by MR-guided focused ultrasound on animal kidney ex vivo model
Bibliographic record
Abstract
Introduction: MR-guided Focused Ultrasound (MRgFUS) has attracted the attention of researchers and clinicians as a potential modality for cancer treatment over the last decades. Despite recent progress, the real application of MRgFUS still remains a challenge due to problems with the optimization of ultrasound parameters and standardization of clinical protocol. In this study, we utilized an ex vivo animal model in order to elucidate the effect of focused acoustic energy on kidney tissue. Material & Methods: The explanted porcine kidney was sonicated under MR-guidance by using a clinical Focused Ultrasound (FUS) system (ExAblate 2000 Body system, InSightec, Haifa, Israel). The study employed MR-based temperature mapping (Proton Resonance Frequency method) for control of the ablation. The data of temperature measurement has been compared to histological analysis of treated tissues. Results: The temperature mapping data demonstrated a rise of temperature at the focal point up to 44 0 C (SD±1), which was thought to be sufficient enough to trigger hyperthermia effects. Histopathological analysis showed tissue destruction as a result of massive cavitation in treated tissues. The signs of mechanical damage were more pronounced in a place that was treated 240 seconds compared with the first location (sonicated 120 seconds). Conclusions: The effect of FUS on the tissues of animal kidney was investigated. The achieved level of temperature rise in the focal point was high enough to induce hyperthermia suggesting possible clinical application. Histology of treated tissue indicated that its therapeutic effect was mediated by focused ultrasound. The correlation between duration of sonication and tissue damage was demonstrated.
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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".