Longitudinal tumor hypoxia imaging with [18F]FAZA-PET provides early prediction of nanoliposomal irinotecan (nal-IRI) treatment activity
Bibliographic record
Abstract
BACKGROUND: Non-invasive measurement of tumor hypoxia has demonstrated potential for the evaluation of disease progression, as well as prediction and assessment of treatment outcome. [(18)F]fluoroazomycin arabinoside (FAZA) positron emission tomography (PET) has been identified as a robust method for quantification of hypoxia both preclinically and clinically. The goal of this investigation was to evaluate the feasibility and value of repeated FAZA-PET imaging to quantify hypoxia in tumors that received multi-dose chemotherapy. METHODS: FAZA-PET imaging was conducted over a 21-day period in a mouse xenograft model of HT-29 human colorectal carcinoma, following multi-dose chemotherapy treatment with irinotecan (CPT-11) or nanoliposomal irinotecan (nal-IRI, MM-398). RESULTS: Tumors treated with 10 mg/kg nal-IRI maintained significantly lower levels of hypoxia and smaller hypoxic fractions compared to tumors that received 50 mg/kg CPT-11. Specifically, differences in FAZA uptake were detectable 9 days before any significant differences in tumor volume were observed between the treatment groups. CONCLUSIONS: These findings highlight the potential use of FAZA-PET as an early marker of treatment response following multi-dose chemotherapy.
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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 | 0.000 |
| 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".