A Smartphone-Fluidic Digital Imaging Analysis System for Pancreatic Islet Mass Quantification - Yu, Xiaoyu; Zhang, Pu; He, Yi; Lin, Emily; Ai, Huiwang; Ramasubramanian, Melur K.; Wang, Yong; Xing, Yuan; Oberholzer, José (Frontiers in Bioengineering and Biotechnology, 2021)
Islet beta-cell viability, function, and mass are three decisive attributes that determine the efficacy of human islet transplantation for type I diabetes mellitus (T1DM) patients. Islet mass is commonly assessed manually, which often leads to error and bias. Digital imaging system analysis (DIA) has shown its potential as an alternative, but it has some associated limitations. In this work, a Smartphone-fluidic Digital Imaging Analysis (SFDIA) System, in combination with microfluidic technique and Python-based video processing software, was developed for islet mass assessment. Utilizing the SFDIA system, we quantified islets by tracking multiple moving islets in a microfluidic channel and received a relatively consistent result. The counting numbers from the two methods showed an average difference of 2.91% ± 1.50%. Furthermore, the software can analyze and extract key human islet mass parameters, including quantity, size, volume, IEq, morphology, and purity, which are not fully obtainable from the traditional manual counting methods. The readings in our experiments showed that the islet sample we tested had an average diameter of 99.88 ± 53.91 µm, an average circularity of 0.591 ± 0.133, and an average solidity of 0.853 ± 0.107. By analyzing the dithizone-stained islets in our system, top-layer islets presented a higher islet tissue percentage than middle-layer islets, 0.735 ± 0.213 and 0.576 ± 0.223, respectively. Results indicate that the SFDIA system has the potential to be used as a multi-parameter islet mass assay that shows superiority in accuracy and consistency when compared to conventional manual technique.