4.4 Article

SmartPDT®: Smartphone enabled real-time dosimetry via satellite observation for daylight photodynamic therapy

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ELSEVIER
DOI: 10.1016/j.pdpdt.2020.101914

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Daylight photodynamic therapy; Photodynamic therapy; Dosimetry; Live dosimetry

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资金

  1. Innovate UK award
  2. Medical Laser Research Fund [SC037390]

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Background: Actinic keratosis (AK) affects one quarter of over 60 year olds in Europe with the risk of transforming into invasive squamous cell carcinoma. Daylight photodynamic therapy (dPDT) is an effective and patient preferred treatment that uses sunlight to clear AK. Currently, there is no standardised method for measuring the light received during treatment. Methods: SmartPDT (R) is a smartphone-based application and web-portal, developed by siHealth Ltd, enabling remote delivery of dPDT. It uses satellite imagery and computational algorithms to provide real-time determination of exposure to PpIX-effective solar radiation (light dose). The application also provides forecast of expected radiant exposures for 24- and 48-hs prior to the treatment period. Validation of the real-time and forecasted radiant exposure algorithms was performed against direct ground-based measurement under all weather conditions in Chilton, UK. Results: Agreement between direct ground measurements and satellite-determined radiant exposure for 2-h treatment was excellent at - 0.1 % +/- 5.1 % (mean +/- standard deviation). There was also excellent agreement between weather forecasted radiant exposure and ground measurement, 1.8 % +/- 17.7 % at 24-hs and 1.6 % +/- 25.2 % at 48-hs. Relative Root Mean Square of the Error (RMSEr) demonstrated that agreement improved as time to treatment reduced (RMSEr = 22.5 % (48 -hs), 11.2 % (24-hs), 5.2 % (real-time)). Conclusion: Agreement between satellite-determined, weather-forecasted and ground-measured radiant exposure was better than any existing published literature for dPDT. The SmartPDT (R) application and web-portal has excellent potential to assist with remote delivery of dPDT, an important factor in reducing risk in an elderly patient population during the Covid-19 pandemic.

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