ArticleJournal of biomedical optics2026
Computational modeling of oxygen dynamics in port-wine stain photodynamic therapy: treatment outcome optimization and pain management.
Article in Journal of biomedical optics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
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
Significance: Port-wine stains (PWSs) are congenital capillary malformations with the incidence of in newborns of Aim: We investigated the feasibility of modulating transcutaneous oxygen delivery during photodynamic therapy of PWS to enhance therapeutic efficacy and reduce pain. Approach: A three-dimensional (3D) computational biophysical model was employed to elucidate the mechanisms through which transcutaneous oxygen modulation enhances the therapeutic efficacy of HMME-PDT and improves pain management. The model was constructed to simulate the light propagation, photosensitizer kinetics, oxygen diffusion, and reactive oxygen species (ROS) generation. A treatment optimization strategy based on epidermal oxygen regulation was proposed and evaluated in computational studies. The spatiotemporal distributions of singlet oxygen under normoxic, hypoxic, and anoxic conditions were evaluated, and their effects on treatment-induced pain and lesion-targeted cytotoxicity were analyzed. Results: Computational analysis showed that compared with normoxic conditions, hypoxia and anoxia significantly enhanced PSC, with improvements of 48% and 61%, respectively. Furthermore, these oxygen-modulated regimens attenuated treatment-associated pain, reducing photochemical pain duration of 17% (hypoxia) and 30% (anoxia). Choosing the right combination of light source irradiance and surface oxygen supply rate amplified therapeutic performance and patient comfort, achieving a 213% increase in PSC and a 57% reduction in photochemical pain duration. These findings establish a mechanistic framework for advancing precision PDT protocols with minimized iatrogenic discomfort. Conclusions: Established in this computational study, strategic epidermal oxygen restriction critically augments PDT PSC while improving patient tolerance. Computational modeling demonstrates that controlled epidermal hypoxia spatially redistributes oxygen gradients, thereby suppressing superficial ROS generation in nontargeted epidermal layers and selectively concentrating ROS within PWS vasculature. This dual mechanism-simultaneously enhancing therapeutic precision and attenuating treatment-induced pain-presents a pioneering strategy centered on an active oxygen control strategy for enhancing HMME-PDT clinical outcomes. Future research will progress from preclinical validation in animal models to clinical studies to evaluate the therapeutic efficacy and translational potential of this strategy.
Indexed as
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.