Probing the in vivo changes in oxygen saturation with photoacoustic imaging as a non-invasive means of assessing treatment progression
Bibliographic record
Abstract
In vivo photoacoustic estimations of tumor oxygenation were used to assess the therapeutic efficacy of a thermosensitive liposome treatment in a pre-clinical mouse model. The treated group (n = 12) was administered doxorubicin-loaded, heat sensitive liposomes and exposed to mild hyperthermia (43°C) in order to deliver doxorubicin locally within the tumor micro-vessels. Control groups received systemic doxorubicin (n = 7) or saline (n = 12). The changes in tumor blood vessels after treatment were probed by analyzing the frequency content of the photoacoustic radiofrequency signals. Tumor oxygenation dropped by 15-20% during the first 30 minutes post-treatment when the tumors were exposed to encapsulated (Heat-Activated cyToxic – HaT-DOX) or free doxorubicin (DOX). The early (30 minutes to 5 hours) decrease in oxygen saturation strongly correlated to the reduction in tumor size assessed by caliper measurements. Control animals did not exhibit significant changes in tumor oxygenation at the early time points. The oxygenation at 7 days increased significantly for all groups. Measurements of the spectral slope from the normalized power spectra of the photoacoustic signals could also be used to differentiate between responder and non-responder mice. The results of this study suggest that photoacoustic imaging of tumors undergoing vascular-targeted cancer therapy can be used to assess treatment response early (hours) post-treatment through a combined analysis of oxygen saturation and photoacoustic radiofrequency spectroscopy.
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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 | 0.001 | 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 | 0.001 |
| 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".