Image Correlation-Based Method to Assess Ciliary Beat Frequency in Human Airway Organoids

Abstract

Ciliary movements within the human airway are essential for maintaining a clean lung environment. Motile cilia have a characteristic ciliary beat frequency (CBF). However, CBF measurement with current video microscopic techniques can be error-prone due to the use of the single-point Fourier transformation, which is often biased for ciliary measurements. Herein, we describe a new video microscopy technique that harnesses a metric of motion-contrast imaging and image correlation for CBF analysis. It can provide objective and selective CBF measurements for individual motile cilia and generate CBF maps for the imaged area. The measurement performance of our methodology was validated with in vitro human airway organoid models that simulated an actual human airway epithelium. The CBF determined for the region of interest (ROI) was equal to that obtained with manual counting. The signal redundancy problem of conventional methods was not observed. Moreover, the obtained CBF measurements were robust to optical focal shifts, and exhibited spatial heterogeneity and temperature dependence. This technique can be used to evaluate ciliary movement in respiratory tracts and determine whether it is non-synchronous or aperiodic in patients. Therefore, our observations suggest that the proposed method can be clinically adapted as a screening tool to diagnose ciliopathies.