Fluorescence detection of deep intramucosal cancer excited by green light for photodynamic diagnosis using protoporphyrin IX induced by 5-aminolevulinic acid: an ex vivo study

Deep learning based depth map estimation of protoporphyrin IX in turbid media using dual wavelength excitation fluorescence

This study presents a depth map estimation of fluorescent objects in turbid media, such as biological tissue based on fluorescence observation by two-wavelength excitation and deep learning-based processing. A U-Net-based convolutional neural network is adapted for fluorophore depth maps from the ratiometric information of the two-wavelength excitation fluorescence. The proposed method offers depth map estimation from wide-field fluorescence images with rapid processing. The feasibility of the proposed method was demonstrated experimentally by estimating the depth map of protoporphyrin IX, a recognized cancer biomarker, at different depths within an optical phantom.

Mathematical modelling for antimicrobial photodynamic therapy mediated by 5-aminolaevulinic acid: An in vitro study

BACKGROUND

Antimicrobial photodynamic therapy (aPDT) using aminolaevulinic acid (ALA) is a promising alternative to antibiotic therapy. ALA administration induces protoporphyrin IX (PpIX) accumulation in bacteria, and light excitation of the accumulated PpIX generates singlet oxygen to bacterial toxicity. Several factors, including drug administration and light irradiation conditions, contribute to the antibiotic effect. Such multiple parameters should be determined moderately for effective aPDT in clinical practice.

METHODS

A mathematical model to predict bacterial dynamics in ALA-aPDT following clinical conditions was constructed. Applying a pharmacokineticspharmacodynamics (PK-PD) approach, which is widely used in antimicrobial drug evaluation, viable bacteria count by defining the bactericidal rate as the concentration of singlet oxygen produced when PpIX in bacteria is irradiated by light.

RESULTS

The in vitro experimental results of ALA-aPDT for Pseudomonas aeruginosa demonstrated the PK-PD model validity. The killing rate has an upper limit, and the lower power density for a long irradiation time can suppress the viable bacteria number when the light dosages are the same.

CONCLUSIONS

This study proposed a model of bacterial viability change in ALA-aPDT based on the PK-PD model and confirmed, by in vitro experiments using PA, that the variation of bacterial viability with light-sensitive substance concentration and light irradiation power densities could be expressed. Further validation of the PK-PD model with other gram negative and gram positive strains will be needed.

Ultracompact fluorescence smartphone attachment using built-in optics for protoporphyrin-IX quantification in skin

Smartphone-based fluorescence imaging systems have the potential to provide convenient quantitative image guidance at the point of care. However, common approaches have required the addition of complex optical attachments, which reduce translation potential. In this study, a simple clip-on attachment appropriate for fluorescence imaging of protoporphyrin-IX (PpIX) in skin was designed using the built-in light source and ultrawide camera sensor of a smartphone. Software control for image acquisition and quantitative analysis was developed using the 10-bit video capability of the phone. Optical performance was characterized using PpIX in liquid tissue phantoms and endogenously produced PpIX in mice and human skin. The proposed system achieves a very compact form factor (<30 cm3) and can be readily fabricated using widely available low-cost materials. The limit of detection of PpIX in optical phantoms was <10 nM, with good signal linearity from 10 to 1000 nM (R2 >0.99). Both murine and human skin imaging verified that in vivo PpIX fluorescence was detected within 1 hour of applying aminolevulinic acid (ALA) gel. This ultracompact handheld system for quantification of PpIX in skin is well-suited for dermatology clinical workflows. Due to its simplicity and form factor, the proposed system can be readily adapted for use with other smartphone devices and fluorescence imaging applications. Hardware design and software for the system is made freely available on GitHub (https://github.com/optmed/CompactFluorescenceCam).