Dynamic Gd‐DTPA enhanced MRI as a surrogate marker of angiogenesis in tissue‐engineered bladder constructs: A feasibility study in rabbits
Bibliographic record
Abstract
PURPOSE: To evaluate the potential of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to assess angiogenesis in tissue-engineered bladder constructs in a blinded animal study, and compare different analysis approaches and their correlation with microvessel density (MVD). MATERIALS AND METHODS: Constructs fortified with vascular endothelial growth factor (VEGF) for enhanced vascularity were grafted onto the bladder in nine rabbits. DCE-MRI of Gd-DTPA uptake was performed and analyzed using Tofts' model, the area under the concentration time curve (AUC), and the uptake slope. DCE-MRI parameters were compared to MVD determined with CD31 immunohistochemistry. RESULTS: Significantly increased MVD was found in the high VEGF group (20 ng/g of tissue) but not at low VEGF (10 ng/g) (2.3x increase, P = 0.035 vs. 1.1x over control). Enhanced permeability at low VEGF was suggested by elevated K(trans), but overall correlation to MVD was poor. Significant correlation to MVD was obtained with AUC(8min) (r = 0.705, P = 0.034). Furthermore, AUC(8min) provided the most precise discrimination between different VEGF preparations and was the only parameter to show a significant increase (P = 0.0058) consistent with MVD changes at high VEGF. CONCLUSION: Findings support DCE-MRI for evaluating angiogenesis in bladder constructs and suggest vessel changes other than density. Future studies should incorporate larger contrast agents and permeability assessment to devise an optimal DCE-MRI strategy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".