ArticleBiomedical optics express2021
Machine learning for real-time optical property recovery in interstitial photodynamic therapy: a stimulation-based study.
Article in Biomedical optics express, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- Single-fiber reflectance spectroscopy system using unmodified clinical laser fibers for tissue optical property recovery for photodynamic therapy treatment planning.Journal of biomedical optics · 2026Article
- Artificial Intelligence and Natural Photosensitizer-Based Nanopharmaceuticals in Photodynamic Therapy: Advanced Modeling, Data-Driven Optimization, and Translational Perspectives.Pharmaceutics · 2026Review
- Robustness of interstitial photodynamic therapy treatment planning under power and positional uncertainties in light delivery.Scientific reports · 2026Article
- Empowering photodynamic therapy with artificial intelligence: current trends and future directions.Frontiers in oncology · 2026Review
- Artificial intelligence-assisted photodynamic diagnosis and photodynamic therapy against cancer.Frontiers in oncology · 2026Review
- Photosensitizer spatial heterogeneity and its impact on personalized interstitial photodynamic therapy treatment planning.Journal of biomedical optics · 2025Article
- Devices and Methods for Dosimetry of Personalized Photodynamic Therapy of Tumors: A Review on Recent Trends.Cancers · 2024Review
- Treatment planning for photodynamic therapy of abscess cavities using patient-specific optical properties measured prior to illumination.Physics in medicine and biology · 2024Article
- Clinical PDT dose dosimetry for pleural Photofrin-mediated photodynamic therapy.Journal of biomedical optics · 2024Article
- Integrating clinical access limitations into iPDT treatment planning with PDT-SPACE.Biomedical optics express · 2023Article
- Scalable and accessible personalized photodynamic therapy optimization with FullMonte and PDT-SPACE.Journal of biomedical optics · 2022Article
- Effects of patient-specific treatment planning on eligibility for photodynamic therapy of deep tissue abscess cavities: retrospective Monte Carlo simulation study.Journal of biomedical optics · 2022Article
- Optical property recovery with spatially-resolved diffuse reflectance at short source-detector separations using a compact fiber-optic probe.Biomedical optics express · 2021Article
- Treatment planning evolution: Comparing approaches in photodynamic and radiation therapies.Photochemistry and photobiologyReview
- Preliminary measurements of optical properties in human abscess cavities prior to methylene blue photodynamic therapy.Proceedings of SPIE--the International Society for Optical EngineeringArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the continued development of non-toxic photosensitizer drugs, interstitial photodynamic therapy (iPDT) is showing more favorable outcomes in recent clinical trials. IPDT planning is crucial to further increase the treatment efficacy. However, it remains a major challenge to generate a high-quality, patient-specific plan due to uncertainty in tissue optical properties (OPs),
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.