MRI monitoring of Avastin™ antiangiogenesis therapy using B22956/1, a new blood pool contrast agent, in an experimental model of human cancer
Bibliographic record
Abstract
PURPOSE: To evaluate the diagnostic and prognostic potential of a new protein-binding contrast medium, B22956/1, for quantitatively characterizing tumor microvessels by MRI and monitoring response to antiangiogenic therapy. MATERIALS AND METHODS: Dynamic contrast-enhanced MRI (DCE-MRI) was performed in an experimental cancer model with the use of the novel protein-binding agent B22956/1, a low molecular contrast agent (ProHance), and a macromolecular contrast medium, albumin-(Gd-DTPA). MDA-MB-435, a human cancer cell line, was implanted in 22 athymic rats. Animals were assigned randomly to a control (saline) or drug-treated (Avastin) group. MRI was performed at baseline and after nine days of treatment. The transendothelial permeability (KPS) and the fractional blood volume (fBV) were estimated from the kinetic analysis of dynamic MR data using a two-compartment model. Tumor growth was also measured from volumetric MRI. RESULTS: Tumors grew more slowly, although not significantly (P=0.07), in the drug-treated group. The KPS determined for B22956/1 decreased significantly in the drug-treated group compared to baseline (P <0.05), and progressed significantly in the control group. However, no significant changes were resolved with the use of ProHance or albumin-(Gd-DTPA). CONCLUSION: With the use of appropriate contrast media, the therapeutic effects of an anti-VEGF antibody on tumor microvessels can be monitored by dynamic MRI. The dynamic range of permeability to B22956/1, and the sensitivity to change of this parameter suggest a potential application in the clinical setting.
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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 | 0.000 |
| 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".