Comparison of noninvasive photodynamic therapy dosimetry methods using a dynamic model of ALA-PDT of human skin
Bibliographic record
Abstract
A numerical model of ALA photodynamic therapy of human skin was used to calculate photosensitizer fluorescence and singlet-oxygen luminescence (SOL) observable at the skin surface during treatment. From the emissions, three practical dose metrics were calculated: the fractional fluorescence bleaching metric (FFBM) given by F(0)/F, where F is photosensitizer protoporphyrin IX (PpIX) fluorescence and F(0) is its initial value, the absolute fluorescence bleaching metric (AFBM) given by F(0)-F, and the cumulative SOL (CSOL). These three metrics can be measured during clinical PDT treatment, but their relation to actual singlet-oxygen distribution in the skin is complex and may depend on treatment parameters such as irradiance. Using the model, the three metrics were compared to the average singlet-oxygen dose in the dermis. Despite the complex dependence of (1)O(2) concentration on depth, a roughly linear correlation was found for all three dose metrics. The correlation for the FFBM was not robust when treatment parameters were varied and this metric was especially sensitive to the initial PpIX concentration and its depth dependence. The AFBM was less sensitive to treatment conditions but CSOL demonstrated the best overall performance.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Simulation or modeling | low |
| opus | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Simulation or modeling | medium |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".