Single-Cell Biophysics: Measurement, Modulation, and Modeling

Single-Cell Biophysics: Measurement, Modulation, and Modeling

Poster Abstracts

89-POS Board 45 Detection and Characterization of Spontaneous Calcium Release Events in Cardiac Myocytes Alex Vallmitjana 1 , Carmen Tarifa 2 , Raul Benitez 1 .Leif Hove-Madsen 2 . 2 Institut Català de Ciències Cardiovasculars, Barcelona, Spain. 1 Universitat Politècnica de Catalunya, Barcelona, Spain, In cardiac function, calcium handling plays a critical role since it is responsible of the excitation- contraction coupling at the cellular level. Indeed, the spontaneous release of intracellular calcium in cardiac cells is a well-established mechanism underlying cardiac arrhythmias among other heart pathologies. An accurate, robust detection of such spatio-temporal patterns is key to further understand the cell physiology mechanisms underlying cardiac function and disease. Most cell level studies in the past have focused in linescan (X-T) images which do not capture spatial characteristics such as the release area, spatial dynamics or the localization with respect to nearby subcellular structures. We have developed an automatic image processing system that allows detecting, localizing and characterizing calcium release events from a sequence of live cell fluorescence microscopy images. The system is able to process both linescan and framescan (X-Y-T) image sequences and detect different event release types such as sparks and calcium waves. The system uses a multilevel wavelet analysis in order to identify events with a duration within a given temporal range and a modified watershed segmentation algorithm in to determine the space-time shape and centroid of the event. The event candidates are further filtered out using morphological features such as amplitude, full width at half maximum or characteristic decay time. The method has been applied to an experimental database previously validated by a human expert including a total of 621 events from 8 human atrial cardiomyocytes. As a measure of overall performance, the approach achieves an average area under the ROC curve (AUC) of 0.8 with a standard error of 0.017.

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