Acoustofluidics-based microscopic examination for automated and point-of-care urinalysis

Abstract

Urinalysis is a heavily used diagnostic test in clinical laboratories, while it is chronically holden back by urine sediment microscopic examination. Current instruments are bulky and expensive to be widely adopted, making microscopic examination a procedure that still relies on manual operations and requires large time and labor costs. To improve the efficacy and automation of urinalysis, this study develops an acoustofluidics-based microscopic examination system. The system utilizes the combination of acoustofluidic manipulation and passive hydrodynamic mechanism thus achieves high throughput (1000 Lmin-1) and high concentration factor (95.2±2.1 fold) simultaneously, fulfilling the demands for urine examination. The concentrated urine sample is automatically dispensed into a hemocytometer chamber and the images are then analyzed by machine learning algorithm. The whole process is completed within 3 minutes with detection accuracies of erythrocytes and leukocytes at 94.6±3.5% and 95.1±1.8% respectively. The examination outcome of urine samples from 50 volunteers by this device shows a correlation coefficient of 0.96 compared to manual microscopic examination. Our system offers a promising tool for automated urine microscopic examination, thus it is of potential to save large amount of time and labor in clinical laboratories, as well as to promote point-of-care urine testing applications in and beyond hospitals.