Automatically digital extracellular vesicles analyzer for size‐dependent subpopulation analysis in surface plasmon resonance microscopy
Feng Xie, Chunhui Zhai, Jiaying Xu, Yuting Yang, Hui Yu
Abstract
Abstract The heterogeneity in extracellular vesicles (EVs) introduces an extra level of complexity in small EV‐based liquid biopsy for cancer diagnosis. Surface plasmon resonance microscopy (SPRM) offers sensitive and multifunctional analysis for single tiny EVs. However, the EV SPRM image analysis has been extremely laborious and time‐consuming due to the low contrast and bad signal‐to‐noise ratio. Herein, we present a digital EV analyzer (DEA), a software package, for the automatic analysis of EV data in the SPRM platform. This package enabled fully automated single EV identification, digital counting, sizing EV, and quantification of dwell time. Integrated with a classification algorithm and intelligent searching algorithm for subpopulation analysis, DEA was able to accurately group EVs with five different origins. We hope this software tool would largely promote the application of SPRM technology into cancer diagnosis with EVs.