Comparing oxygen-sensitive MRI (BOLD R2*) with oxygen electrode measurements: A pilot study in men with prostate cancer
Bibliographic record
Abstract
PURPOSE: To explore the relationship between oxygen-sensitive Magnetic Resonance Imaging (MRI) and oxygen measurements in prostate cancer. METHODS: Nine men underwent MRI examinations followed by needle oxygen measurements of tumor bearing region within prostate gland and five men further consented to biopsy. Median pO2 and hypoxic fraction < 5 mm Hg (HP5) were derived. Biopsies were immunostained for Carbonic Anhydrase IX (CA IX), Hypoxia Inducible Factor-1 (HIF 1) and Glucose Transporter-1 (GLUT 1). Corresponding Regions-of-Interest (ROI) were delineated on T2-weighted (T2w) MRI by two observers. Median R2* was calculated for each ROI. Spearman correlation was calculated between R2* and HP5/pO2. RESULTS: MRI quality evaluation resulted in exclusion of 4/18 ROI due to motion (n = 2) and rectal air susceptibility artifact (n = 2). Quality of remaining data was validated by concordance of R2* with T2w, indices and with secondary observer R2* (r = 0.94, p = 0.005). Correlation was observed between R2* and HP5 (r = 0.76, p = 0.02) and a trend was noted between R2* and pO2 (r = -0.66, p = 0.07). GLUT 1 and HIF 1 were expressed in all patients, and CA IX was expressed in one patient with high HP5 (77%) and low pO2 (1.4 mm Hg). CONCLUSIONS: MRI using R2* quantification is a promising tool for non-invasive imaging of prostate cancer 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 | 0.001 | 0.002 |
| 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".