Novel use of differential image velocity invariants to categorize ciliary motion defects

Primary ciliary dyskinesia (PCD) is a disorder characterized by sinopulmonary disease arising from ciliary motion defects in respiratory epithelia. An essential first step in the diagnostic evaluation of PCD is the use of high-speed videomicroscopy to analyze ciliary beat patterns in nasal epithelia biopsies. This includes a quantitative assessment of ciliary beat frequency (CBF, where CBF of <; 11 Hz is referred to further diagnosis), followed by a visual examination of ciliary beat patterns to detect the presence of dyskinetic motions, such as stiff, incomplete, wavy and others. Both procedures lack standardized protocols, hence CBF is often counted manually by observing the ciliary image frames in slow motion, while a manual examination of beat patterns is subjective, cumbersome, and error-prone. We are building automated image analysis methods to address this problem. To this end, we report the use of image velocities for measuring CBF and demonstrate the effectiveness of the differential image velocity invariants, curl and deformation, in deconvolving the various motion defects.