Changes in apparent diffusion coefficient and T<sub>2</sub> relaxation during radiotherapy for prostate cancer
Bibliographic record
Abstract
PURPOSE: To evaluate regional and temporal changes in apparent diffusion coefficient (ADC) and T2 relaxation during radiation therapy (RT) in patients with low and intermediate risk localized prostate cancer. MATERIALS AND METHODS: Seventeen patients enrolled on a prospective clinical trial where MRI was acquired every 2 weeks throughout eight weeks of image-guided prostate IMRT (78 Gy/39 fractions). ADC and T2 quantification used entire prostate, central gland, benign peripheral zone, and tumor-dense regions-of-interest, and mean values were evaluated for common response trends. RESULTS: Overall, the RT responses were greater than volunteer measurement repeatability, and week 6 appeared to be an optimum time-point for early detection. RT effects on the entire prostate were best detected using ADC (5-7% by week 2, P < 0.0125), effects on peripheral zone were best detected using T2 (19% reduction at week 6; P = 0.004) and effects on tumors were best detected using ADC (14% elevation at week 6; P = 0.004). CONCLUSION: ADC and T2 may be candidate biomarkers of early response to RT warranting further investigation against clinical outcomes.
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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 | 0.001 |
| 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".