Functional CT imaging of angiogenesis in rabbit VX2 soft-tissue tumour
Bibliographic record
Abstract
Functional parameters such as blood flow (BF), microvessel permeability surface area product (PS), blood volume (BV) and mean transit time (MTT) are physiological markers related to the changes associated with angiogenesis. In the current study we present a functional CT technique for the simultaneous measurement of these four functional parameters and the display of each parameter as a functional image over an entire tissue slice. New Zealand White rabbits with implanted VX2 thigh tumours were scanned using CT with contrast media injection. The ex vivo method of radioactive microspheres was used to evaluate the accuracy of BF measurements with the functional CT technique. There was a significant linear correlation (R = 0.96) between regional CT and microsphere-measured BF values, with a slope not significantly different from unity (0.98 +/- 0.02, P < 0.0001). The precision of our CT technique was determined by the repeated scanning under steady-state conditions. The precision of CT-measured BF, PS. BV and MTT was 14%, 18%, 20% and 24%, respectively. In conclusion, BF can be measured accurately and BF, PS, BV and MTT reproducibly using our functional CT technique. Functional CT can be readily incorporated into existing imaging protocols to assess tumour angiogenesis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".