Microparticle-Based Biochemical Sensing Using Optical Coherence Tomography and Deep Learning.

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Abstract

Advancing continuous health monitoring beyond vital signs to biochemistry will revolutionize personalized medicine. Herein, we report a biosensing platform to achieve remote biochemical monitoring using microparticle-based biosensors and optical coherence tomography (OCT). Stimuli-responsive, polymeric microparticles were designed to serve as freely dispersible biorecognition units, wherein binding with a target biochemical induces volumetric changes of the microparticle. Analytical approaches to detect these submicron changes in 3D using OCT were devised by modeling the microparticle as an optical cavity, enabling estimations far below the resolution of the OCT system. As a proof of concept, we demonstrated the 3D spatiotemporal monitoring of glucose-responsive microparticles distributed throughout a tissue mimic in response to dynamically fluctuating levels of glucose. Deep learning was further implemented using 3D convolutional neural networks to automate the vast processing of the continuous stream of three-dimensional time series data, resulting in a robust end-to-end pipeline with immense potential for continuous in vivo biochemical monitoring.