MP20-12 IMPROVING THE SAFETY AND EFFICACY OF PHOTODYNAMIC THERAPY FOR NMIBC– INTRAVESICAL RUTHENIUM (II)-PHOTOSENSITIZER AND LIGHT DOSIMETRY IN A PHASE 1B CLINICAL TRAIL
Bibliographic record
Abstract
You have accessJournal of UrologySurgical Technology & Simulation: Instrumentation & Technology III (MP20)1 Apr 2019MP20-12 IMPROVING THE SAFETY AND EFFICACY OF PHOTODYNAMIC THERAPY FOR NMIBC– INTRAVESICAL RUTHENIUM (II)-PHOTOSENSITIZER AND LIGHT DOSIMETRY IN A PHASE 1B CLINICAL TRAIL Lothar Lilge*, Angelica Manalac, Leonid Vesselov, Wayne Embree, Arkady Mandel, Vaughn Betz, Michael Jewett, and Girish Kulkani Lothar Lilge*Lothar Lilge* More articles by this author , Angelica ManalacAngelica Manalac More articles by this author , Leonid VesselovLeonid Vesselov More articles by this author , Wayne EmbreeWayne Embree More articles by this author , Arkady MandelArkady Mandel More articles by this author , Vaughn BetzVaughn Betz More articles by this author , Michael JewettMichael Jewett More articles by this author , and Girish KulkaniGirish Kulkani More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000555520.34010.edAboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: To achieve a pre-defined photosensitizer dose and photon irradiance for PDT of NMIBC, independent of a patient’s bladder volume, shape and bladder wall optical properties, a new dosimeter approach was developed and tested in a phase IB clinical trial. METHODS: 6 patients were enrolled in an open-label PDT study. Half received 0.35 mg/cm2, and the others 0.70 mg/cm2 of a TLD1433 solution in water instilled intravesically. The photosensitizer does not cross the intact urothelium but diffuses rapidly up to 1.5 mm into tissue when the Urothelium is compromised. 525 nm photosensitizer activation light was used to attain a steep PDT dose gradient. The activation light was delivered via an optical fiber with spherical diffuser positioned centrally in the bladder void. The target radiance exposure was 90 J/cm2, and the irradiance [mW/cm2] was monitored at up to 12 positions, allowing for optimum diffuser positioning and treatment time control. Measured irradiances were compared to light propagation simulations based on the patients’ CT images used to create tetrahedral meshes of the bladder and adjacent soft tissues. Simulations using the FullMonte simulation software provided the bladder wall surface irradiance and the fluence-rate in-depth and dose-surface-histograms. RESULTS: Instillation of TLD1433 for one hour resulted in a patchy discolouration of the bladder wall, often co-localized with known presence of carcinomas. In situ monitoring of the irradiance at the bladder wall surface ensured reaching the target radiant exposure in all 6 patients, independent of the bladder volume, shape and optical properties. The measured median irradiance varied from 5.7 to 32 mW/cm2. Matching of the in situ measured irradiances with the simulated dose-surface histograms was possible by adjusting the tissue optical properties, absorption and light scattering, of the bladder wall and also of the bladder void. Light scattering by protein aggregates inside the bladder was identified as a cause for low irradiance measurements on the bladder wall surface. Bladder void light scattering caused by proteinaceous materials ranged from 0.2 to 1.42 cm-1. Time to achieve 90 J/cm2 required between 68 min and 165 min. CONCLUSIONS: Variations in the bladder wall’s optical properties varied between individuals and over the course of TLD-1433 mediated PDT. Bladder shapes influence the ability to achieve flat dose-surface-histogram. Monitoring of the irradiance or radiant exposure is strongly recommended for accurate PDT dosimetry. Source of Funding: Theralase Technologies Inc. and the Government of Ontario Toronto, Canada© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e287-e288 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Lothar Lilge* More articles by this author Angelica Manalac More articles by this author Leonid Vesselov More articles by this author Wayne Embree More articles by this author Arkady Mandel More articles by this author Vaughn Betz More articles by this author Michael Jewett More articles by this author Girish Kulkani More articles by this author Expand All Advertisement PDF downloadLoading ...
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.035 | 0.005 |
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".