Monitoring T2 and ADC at 9.4 T following fractionated external beam radiation therapy in a mouse model
Bibliographic record
Abstract
The purpose of this study is to investigate the response of transverse relaxation time (T2) and apparent diffusion coefficient (ADC) in human glioma tumor xenografts during and after fractionated radiotherapy. Tumor-bearing mice were divided into four treatment groups (n=6 per group) that received a total dose of 800 cGy of 200 kVp x-rays, given over two or three fractions, with a fraction spacing of either 24 or 72 h. A fifth treatment group received 800 cGy in a single fraction, and a sixth group of mice served as an untreated control. All mice were scanned pretreatment, before each fraction and at multiple points after treatment using a 9.4 T magnetic resonance imaging (MRI) system. Quantitative T2 and ADC maps were produced. All treated groups showed an increase in mean tumor ADC, though the time for this response to reach a maximum and return toward baseline was delayed in the fractionated groups. The highest ADC was measured 7 days after the final fraction of treatment for all groups. There were no significant differences in the maximum measured change in ADC between any of the treated groups, with the average measured maximum value being 20.5% above baseline. After treatment, all groups showed an increase in mean tumor T2, with the average measured maximum T2 being 4.7% above baseline. This increase was followed by a transition to mean T2 values below baseline values, with the average measured tumor T2 being 92.4% of the pretreatment value. The transition between elevated and depressed T2 values was delayed in the cases of fractionated therapies and occurred between 3.6 and 7.3 days after the last fraction of treatment. These results further the understanding of the temporal evolution of T2 and ADC during fractionated radiotherapy and support their potential use as time-sensitive biomarkers for tumor response.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".