Background: The respiratory epithelium is frequently infected by the respiratory syncytial virus, resulting in inflammation, a reduction in cilia activity and an increase in the production of mucus.
Methods: In this study, an automatic method has been proposed to characterize the ciliary motility from cell cultures by means of a motility index using a dense optical flow algorithm. This method allows us to determine the ciliary beat frequency (CBF) together with a ciliary motility index of the cells in the cultures. The object of this analysis is to automatically distinguish between normal and infected cells in a culture.
Results: The method was applied in 2 stages. It was concluded from the first stage that the CBF is not a good enough indicator to discriminate between the control and infected cultures. However, the ciliary motility index does succeed in discriminating between the control and infected cultures using the t test with a value t = 6.46 and P < .001. In the second stage, it has been shown that the ciliary motility index did not differ significantly between patients, and the analysis of variance test gives α = 0.05, F = 1.61, P = .20. A threshold for this index has been determined using a receiver operating characteristics analysis that gives an area under the curve of 0.93.
Conclusions: We have obtained a ciliary motility index that is able to discriminate between control and infected cultures after the eighth postinfection day. After infection, there is a rapid cilia loss of the cells and the measured CBF corresponds to the remaining noninfected cells. This is why the CBF does not discriminate between the control and the infected cells.
Keywords: cell cultures; ciliary beat frequency; ciliary beat pattern; ciliary motility; dense optical flow; motility index; respiratory epithelium; respiratory syncytial virus.