Automated detection and analysis of Ca(2+) sparks in x-y image stacks using a thresholding algorithm implemented within the open-source image analysis platform ImageJ

Previous studies have used analysis of Ca(2+) sparks extensively to investigate both normal and pathological Ca(2+) regulation in cardiac myocytes. The great majority of these studies used line-scan confocal imaging. In part, this is because the development of open-source software for automatic detection of Ca(2+) sparks in line-scan images has greatly simplified data analysis. A disadvantage of line-scan imaging is that data are collected from a single row of pixels, representing only a small fraction of the cell, and in many instances x-y confocal imaging is preferable. However, the limited availability of software for Ca(2+) spark analysis in two-dimensional x-y image stacks presents an obstacle to its wider application. This study describes the development and characterization of software to enable automatic detection and analysis of Ca(2+) sparks within x-y image stacks, implemented as a plugin within the open-source image analysis platform ImageJ. The program includes methods to enable precise identification of cells within confocal fluorescence images, compensation for changes in background fluorescence, and options that allow exclusion of events based on spatial characteristics.