Temporal and dose dependence of T2 and ADC at 9.4 T in a mouse model following single fraction radiation therapy
Bibliographic record
Abstract
The purpose of this study is to use magnetic resonance imaging to monitor the response of human glioma tumor xenografts to single fraction radiation therapy. Mice were divided into four treatment groups (n = 6 per group) that received 50, 200, 400, or 800 cGy of 200 kVp x rays. A fifth group (n = 6) received no radiation dose and served as the control. Quantitative maps of the treated tumor tissue were produced of water apparent diffusion coefficient (ADC) and transverse relaxation time (T2). Mice were imaged before and at multiple time points after treatment. There was a statistically significant difference in tumor growth relative to that of the control for all treatment groups. Only the highest dose group showed T2 values that were significantly different at all measured time points after treatment. In this group, there was an 8.3% increase in T2 relative to controls 2 days after treatment, but when measured 14 days after treatment, mean tumor T2 had dropped to 10.1% below the initial value. ADC showed statistically significant differences from the control at all dose points. A radiation dose dependence was observed. In the highest dose group, the fractional increases in ADC were higher than those observed for T2. ADC was sensitive to radiation-induced changes in lower dose groups that did not have significant T2 change. At all doses, elevation of mean tumor ADC preceded deviations in tumor growth from the control. These observations support the potential application of ADC as a time and dose sensitive marker of tumor response to radiation therapy.
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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) | 0.000 | 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".