Evaluation of <sup>18</sup>F-EF5 for detection of hypoxia in localized adenocarcinoma of the prostate
Bibliographic record
Abstract
Background A common feature of solid tumours that are resistant to therapy is the presence of regions with low oxygen content (i.e., hypoxia). Oxygen electrode studies suggest that localized prostate adenocarcinoma is commonly hypoxic, although conflicting data have been reported between immunohistochemical detection of hypoxia-induced proteins in biopsy specimens and positron emission tomography (PET) imaging of 18F-labeled hypoxia reporters. Although the 2-nitroimidazole 18F-EF5 is well-established to label hypoxic tumour cells in pre-clinical tumour models and clinical trials of multiple primary tumour sites, it has yet to be tested in prostate cancer. The purpose of this study was to evaluate the feasibility of using 18F-EF5 to detect hypoxia in clinical prostate tumours.Material and methods Patients with localized adenocarcinoma of the prostate were recruited for pre-treatment 18F-EF5 PET scans. Immunohistochemistry was conducted on diagnostic biopsies to assess the expression of glucose transporter 1 (GLUT1), osteopontin (OPN), and carbonic anhydrase IX (CAIX). Immunoreactivity scores of staining intensity and frequency were used to indicate the presence of tumour hypoxia.Results We found low tumour-to-muscle ratios of 18F-EF5 uptake that were not consistent with tumour hypoxia, causing early termination of the study. However, we observed GLUT1 and OPN expression in all prostate tumour biopsies, indicating the presence of hypoxia in all tumours.Conclusion Our data do not support the use of 18F-EF5 PET to detect hypoxia in prostate adenocarcinoma, and suggest the use of immunohistochemistry to quantify expression of the hypoxia-inducible proteins GLUT1 and OPN as indications of prostate tumour hypoxia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".