Dynamic contrast‐enhanced MRI in mouse tumors at 11.7 T: comparison of three contrast agents with different molecular weights to assess the early effects of combretastatin A4
Bibliographic record
Abstract
Dynamic contrast-enhanced (DCE)-MRI is useful to assess the early effects of drugs acting on tumor vasculature, namely anti-angiogenic and vascular disrupting agents. Ultra-high-field MRI allows higher-resolution scanning for DCE-MRI while maintaining an adequate signal-to-noise ratio. However, increases in susceptibility effects, combined with decreases in longitudinal relaxivity of gadolinium-based contrast agents (GdCAs), make DCE-MRI more challenging at high field. The aim of this work was to explore the feasibility of using DCE-MRI at 11.7 T to assess the tumor hemodynamics of mice. Three GdCAs possessing different molecular weights (gadoterate: 560 Da, 0.29 mmol Gd/kg; p846: 3.5 kDa, 0.10 mmol Gd/kg; and p792: 6.47 kDa, 0.15 mmol Gd/kg) were compared to see the influence of the molecular weight in the highlight of the biologic effects induced by combretastatin A4 (CA4). Mice bearing transplantable liver tumor (TLT) hepatocarcinoma were divided into two groups (n = 5-6 per group and per GdCA): a treated group receiving 100 mg/kg CA4, and a control group receiving vehicle. The mice were imaged at 11.7 T with a T1 -weighted FLASH sequence 2 h after the treatment. Individual arterial input functions (AIFs) were computed using phase imaging. These AIFs were used in the Extended Tofts Model to determine K(trans) and vp values. A separate immunohistochemistry study was performed to assess the vascular perfusion and the vascular density. Phase imaging was used successfully to measure the AIF for the three GdCAs. In control groups, an inverse relationship between the molecular weight of the GdCA and K(trans) and vp values was observed. K(trans) was significantly decreased in the treated group compared with the control group for each GdCA. DCE-MRI at 11.7 T is feasible to assess tumor hemodynamics in mice. With K(trans) , the three GdCAs were able to track the early vascular effects induced by CA4 treatment.
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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 | 0.001 |
| 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".