Fractionated versus Standard Continuous Light Delivery in Interstitial Photodynamic Therapy of Dunning Prostate Carcinomas
Bibliographic record
Abstract
PURPOSE: The study aims to compare the standard/continuous light delivery with fractionated light delivery for interstitial photodynamic therapy (PDT) of prostate cancer. EXPERIMENTAL DESIGN: Dunning R3327 prostate tumor models were established in male syngeneic rats. When tumors reached approximately 3,000 mm3, animals were randomized to various treatment groups. Three hours after QLT0074 injection, tumors were illuminated by 690-nm light delivered by a computer-controlled switch, which sequentially directed light to one of the seven optical fibers in cycles. For comparison, tumors were treated with continuous illumination. Tumors treated with light-only served as control. Dynamic contrast-enhanced magnetic resonance imaging was used to monitor tumor perfusion changes before and after PDT. RESULTS: Tumor response (animal survival) to PDT with fractionated light delivery was PDT dose dependent in both tumor models. Rats bearing anaplastic tumor treated by fractionated light (PDT dose: 1.5 mg/kg QLT0074, 900 J light) had a median survival of 51 days with 25% tumor cures compared with that of 26 days with no tumor cure by continuous illumination (P = 0.015) and 14 days by light-only (P = 0.0001). Rats bearing well-differentiated tumor treated by fractionated light had a median survival of 82 days compared with 65 days by continuous illumination (P = 0.001) and 37 days by light-only. PDT with fractionated light generated a perfusion reduction of 80% compared with 52% for continuous illumination in well-differentiated tumors. CONCLUSIONS: Fractionated light delivery is more effective than continuous light delivery in PDT of prostate cancer (solid tumors). These results warrant further investigation in clinical trials.
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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".