SignificanceThe quantification of protoporphyrin IX (PpIX) in skin can be used to study photodynamic therapy (PDT) treatments, understand porphyrin mechanisms, and enhance preoperative mapping of non-melanoma skin cancers.AimWe aim to develop a smartphone-based imager for performing simultaneous radiometric fluorescence (FL) and white light (WL) imaging to study the baseline levels, accumulation, and photobleaching of PpIX in skin.ApproachA smartphone-based dual FL and WL imager (sDUO) is introduced alongside new radiometric calibration methods for providing SI-units of measurements in both pre-clinical and clinical settings. These radiometric measurements and corresponding PpIX concentration estimations are applied to clinical measurements to understand mechanistic differences between PDT treatments, accumulation differences between normal tissue and actinic keratosis lesions, and the correlation of photosensitizer concentrations to treatment outcomes.ResultsThe sDUO alongside the developed methods provided radiometric FL measurements (nW / cm2) with a demonstrated sub nanomolar PpIX sensitivity in 1% intralipid phantoms. Patients undergoing PDT treatment of actinic keratosis (AK) lesions were imaged, capturing the increase and subsequent decrease in FL associated with the incubation and irradiation timepoints of lamp-based PDT. Furthermore, the clinical measurements showed mechanistic differences in new daylight-based treatment modalities alongside the selective accumulation of PpIX within AK lesions. The use of the radiometric calibration enabled the reporting of detected PpIX FL in units of nW / cm2 with the use of liquid phantom measurements allowing for the estimation of in-vivo molar concentrations of skin PpIX.ConclusionsThe phantom, pre-clinical, and clinical measurements demonstrated the capability of the sDUO to provide quantitative measurements of PpIX FL. The results demonstrate the use of the sDUO for the quantification of PpIX accumulation and photobleaching in a clinical setting, with implications for improving the diagnosis and treatment of various skin conditions.
The development of smartphones over the last decade has led to a growth in interest of their potential to tackle numerous point-of-care diagnostic and treatment assessment applications. Despite this interest, there has been lackluster transition of smartphones within clinical care, where the reproducibility of measurements across devices and inability to perform image analysis within the device has hampered development. Here, we present an open-source platform for performing quantitative imaging and analysis within the iOS smartphone environment. We explore the need for RAW pixel data within quantitative applications and characterize the iPhone 11 to lay the foundation for its use in scientific and point-of-care imaging applications.
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