  Local Ca Releases (LCRs) are crucial events involved in cardiac pacemaker
cell function. However, specific algorithms for automatic LCR detection and
analysis have not been developed in live, spontaneously beating pacemaker
cells. Here we measured LCRs using a high-speed 2D-camera in spontaneously
contracting sinoatrial (SA) node cells isolated from rabbit and guinea pig and
developed a new algorithm capable of detecting and analyzing the LCRs spatially
in two-dimensions, and in time. Our algorithm tracks points along the midline
of the contracting cell. It uses these points as a coordinate system for affine
transform, producing a transformed image series where the cell does not
contract. Action potential-induced Ca transients and LCRs were thereafter
isolated from recording noise by applying a series of spatial filters. The LCR
birth and death events were detected by a differential (frame-to-frame)
sensitivity algorithm. An LCR was detected when its signal changes sufficiently
quickly within a sufficiently large area. The LCR is considered to have died
when its amplitude decays substantially, or when it merges into the rising
whole cell Ca transient. Our algorithm provides major LCR parameters such as
period, signal mass, duration, and path area. As LCRs propagate within cells,
the algorithm identifies splitting and merging behaviors, indicating the
importance of Ca-induced-Ca-release for the fate of LCRs and for generating a
powerful ensemble Ca signal. Thus, our new computer algorithms eliminate motion
artifacts and detect 2D local spatiotemporal Ca release events from recording
noise and global signals. While the algorithms detect LCRs in sinoatrial nodal
cells, they have the potential to be used in other applications in biophysics
and cell physiology, for example, to detect Ca wavelets (abortive waves),
sparks and embers in muscle cells and Ca puffs and syntillas in neurons.
