OPTICAL CHARACTERISTICS OF THE CANINE PROSTATE AT 665 NM SENSITIZED WITH TIN ETIOPURPURIN DICHLORIDE: NEED FOR REAL-TIME MONITORING OF PHOTODYNAMIC THERAPY
Bibliographic record
Abstract
PURPOSE: Photodynamic therapy (PDT) is an emerging, minimally invasive therapy for prostate cancer that depends on the sequestration of a photosensitizing drug within targeted tissue. The photosensitizer is subsequently activated by light of a specific wavelength, resulting in destruction of the targeted tissue. Successful treatment requires knowledge of the optical properties of the target tissue, a critical element for therapy. MATERIALS AND METHODS: Adult canines were injected with tin etiopurpurin dichloride (1.0 mg/kg) as a liposome emulsion vehicle in saline 24 hours prior to light treatment. Laser light was delivered to the prostate via a 400 microm optical fiber fitted with a 2.0 cm cylindrical diffuser and optical properties of the prostate were measured. RESULTS: In this study we determined the attenuation coefficient and critical fluence in the canine prostate. Our studies shown that the attenuation coefficient is not uniform but higher at the base (average for all animals 2.59 to 2.79 cm-1) than in the mid section or apex of the prostate (1.71 to 1.90 cm-1). Significant differences among dogs (0.11 to 12.70 cm-1) were found. In some cases we observed a fluctuation of the attenuation coefficient during treatment. We also established experimentally the minimum energy (1449 mJ/cm2) needed (critical fluence) to produce necrosis. Experimentally establishing the values of effective attenuation and critical fluence is necessary to predict the area of ablation during PDT and protect surrounding organs from over treatment. CONCLUSIONS: Based on our results it is evident that for PDT of the prostate to be successful the optical parameters of the prostate must be measured and monitored during treatment. We suggest that the optimum way of doing this is real-time computerized monitoring combined with simulation PDT.
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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) | 0.000 | 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 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".