ADC response to radiation therapy correlates with induced changes in radiosensitivity
Bibliographic record
Abstract
PURPOSE: Magnetic resonance imaging was used to compare the responses of human glioma tumor xenografts to a single fraction of radiation, where a change in radiosensitivity was induced by use of a suture-based ligature. METHODS: Ischemia was induced by use of a suture-based ligature. Six mice were treated with 800 cGy of 200 kVp x rays while the ligature was applied. An additional six mice had the ligature applied for the same length of time but were not irradiated. Quantitative maps of each tumor were produced of water apparent diffusion coefficient (ADC) and transverse relaxation time (T2). Mice were imaged before and at multiple points after treatment. Volumetric, ADC, and T2 responses of the ligated groups were compared to previously measured responses of the same tumor model to the same radiation treatment, as well as those from an untreated control group. RESULTS: Application of the ligature without irradiation did not affect tumor ADC values, but did produce a temporary decrease in tumor T2 values. Average tumor T2 was reduced by 6.2% 24 h after the ligature was applied. Average tumor ADC increased by 9.6% 7 days after irradiation with a ligature applied. This response was significantly less than that observed in the same tumor model when no ligature is present (21.8% at 7 days after irradiation). CONCLUSIONS: These observations indicate that the response of ADC to radiation therapy is not determined entirely by physical dose deposition, but at least in part by radiosensitivity and resultant biological response.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".