Correlations between dynamic contrast‐enhanced magnetic resonance imaging–derived measures of tumor microvasculature and interstitial fluid pressure in patients with cervical cancer
Bibliographic record
Abstract
PURPOSE: To correlate permeability (rk(trans)), extracellular volume fraction (rv(e)), relative to muscle and initial area under the enhancement curve (IAUC(60m)) determined by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with in vivo measurements of interstitial fluid pressure (IFP) in patients with cervical cancer. MATERIALS AND METHODS: DCE-MRI and IFP measurements were performed of cervical tumors of 32 patients prior to therapy. Median tumor rk(trans) and rv(e) were derived from a bidirectional two-compartment model using an input function derived from muscle. Median IAUC(60m) was defined as the integral of tumor enhancement in the first 60 seconds divided by the similar muscle enhancement integral. These parameters were correlated with the mean tumor IFP. RESULTS: There was a significant negative correlation between IAUC(60m) and IFP (r = -0.42, P = 0.016) and between rk(trans) and IFP (r = -0.47, P = 0.008). The was no significant correlation between IFP and rv(e). CONCLUSION: There is a moderate negative correlation between IAUC(60m), rk(trans), and IFP in cervical cancer. This suggests that these parameters may be of value in assessment of tumor behavior.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".