FDG-PET imaging for the evaluation of antiglioma agents in a rat model
Bibliographic record
Abstract
The increasing development of novel anticancer agents demands parallel advances in the methods used to rapidly assess their therapeutic efficacy (TE) in the preclinical phase. We evaluated the ability of small-animal PET, using the (18)F-fluoro-deoxy-D-glucose (FDG) radiotracer, to predict the TE of a number of anticancer agents in the rat C6 glioma model following 3 days of treatment. Semi-quantitative measurements of changes in FDG uptake during the course of treatment (standardized uptake value response [SUV(r)]) were found to be significantly lower in tumors treated with the hypoxia-inducible factor-1alpha inhibitor YC-1 (15 mg/kg) than in tumors in the control group. No significant SUV(r) change was observed following a similar 3-day regimen with the proapoptotic agent NS1619 (20 microg/kg), the combination of YC-1 and NS1619, or the alkylating agent temozolomide (7.5 mg/kg). Quantitative immunohistochemical studies demonstrated significantly lower levels of glucose transporter-1 (GLUT-1) expression in the YC-1-treated tumors, thereby correlating with the low SUV(r) observed in this group. The ability of SUV(r) to predict gold-standard outcomes of TE was further validated as YC-1-treated tumors had decreased volumes compared to control tumors. As such, we successfully demonstrated the ability of FDG-PET to rapidly determine the TE of novel agents for the treatment of glioma in the preclinical phase of evaluation.
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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".