Quantitative MRI assessment of VX2 tumour oxygenation changes in response to hyperoxia and hypercapnia
Bibliographic record
Abstract
Magnetic resonance imaging (MRI) relaxation times provide indirect estimates of tissue O(2) for monitoring tumour oxygenation. This study provides insight into mechanisms underlying longitudinal (R(1) = 1/T(1)) and transverse effective (R(2)* = 1/T(2)*) relaxation rate changes during inhalation of 100% O(2) and 3%, 6% and 9% CO(2) (balanced O(2)) in a rabbit tumour model. Quantitative R(1), R(2)*, and dynamic contrast-enhanced (DCE) imaging was performed in six rabbits 12-23 days following implantation of VX2 carcinoma cells in the quadricep muscle. Invasive measurements of tissue partial pressure of O(2) (pO(2)) and perfusion were also performed, which revealed elevated pO(2) levels in all tumour regions for all hyperoxic gases compared to baseline (air) and reduced perfusion for carbogen. During 100% O(2) breathing, an R(1) increase and R(2)* decrease consistent with elevated pO(2) were observed within tumours. DCE-derived blood flow was weakly correlated with R(1) changes from air to 100% O(2). Further addition of CO(2) (carbogen) did not introduce considerable changes in MR relaxation rates, but a trend towards higher R(1) relative to breathing 100% O(2) was observed, while R(2)* changes were inconsistent. This observation supports the predominance of dissolved O(2) on R(1) sensitivity and demonstrates the value of R(1) over R(2)* for tissue oxygenation measures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".