Investigation on Changes of Optical Tissue Properties related to iPDT on Malignant Gliomas
Bibliographic record
Abstract
Brain tumor treatment via interstitial photodynamic therapy (iPDT) needs precise treatment light delivery, which is essential for the conduction of the therapy [1]. The light delivery and the resulting light dosimetry are highly dependent on the optical tissue properties of the tumor tissue and the surrounding brain tissue . Employing intraoperative spectral online monitoring (SOM), it looks possible to assess the treatment light transmittance between the used light applicators and monitor potential changes during therapy [2]. Changes have been observed during clinical iPDT-illumination and can be interpreted as changes in the optical tissue properties [2, 3]. In vitro experiments mimicking the clinical iPDT-illumination situation using liquid optical tissue phantoms, including blood, showed SOM intensity changes in transmittance. Due to simultaneous remission spectroscopy, this can be related to the deoxygenation of hemoglobin and its oxidation to methemoglobin (MetHb) [4]. The analysis of data from clinical iPDT-procedures confirmed this interpretation. Based on intraoperative SOM data, changes in the optical absorption coefficient have been calculated and correlated with newly diagnosed early visible intrinsic T1-hyperintensity in the treatment volume [3]. The intrinsic T1 hyperintensity is clinically an indicator of the formation of MetHb after silent hemorrhages , which may occur during iPDT. As the T1 hyperintensity was early visible in the MRI, the corresponding early appearance of MetHb was in context with the iPDT and consistent with the in vitro experiments. Further in vitro experiments showed that changes in optical tissue properties and hemoglobin oxidation is not only possible due to ROS production during iPDT but also due to a slight temperature increase during iPDT by 4°C [5]. These results give more insight into mechanisms occurring during iPDT irradiation, but the impact on treatment outcome has still to be assessed.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".