Weather-informed Light-tissue Model-Based Dose Planning for Indoor Daylight Photodynamic Therapy

Area of Science:

• Dermatology
• Photomedicine
• Biophysics

Background:

• Daylight photodynamic therapy (PDT) is a widely adopted, effective, and less painful treatment for skin lesions compared to traditional red or blue light activation.
• Challenges in daylight PDT include seasonal variations and unpredictable weather, complicating accurate light dose estimations for effective treatment planning.

Purpose of the Study:

• To develop a simplified method for daylight PDT dose planning that minimizes clinical staff burden.
• To integrate site-specific spectral measurements with real-time weather data for accurate optical dose estimation.

Main Methods:

• A one-time site assessment was conducted to gather spectral measurements for characterizing sunlight exposure.
• Automated weather reports (satellite cloud coverage, UV index) were used to track transient atmospheric conditions.
• A dose-planning model was employed to estimate photodynamic dose at tissue depth using integrated spectral and weather data.

Main Results:

• A strong correlation (R²: 0.87) was observed between directly measured light exposure and automated weather indexes (satellite cloud coverage, UV index).
• Automated weather data can serve as reliable surrogates for estimating daylight PDT optical dose.
• The proposed method allows for dose planning without significant clinical staff involvement.

Conclusions:

• A standardized, automated method for estimating daylight PDT light dose is feasible and effective.
• This approach can improve inter-site reproducibility and potentially minimize treatment times for daylight PDT.
• Integrating site assessment with real-time weather data offers a practical solution for optimizing daylight PDT protocols.