Real-Time Determination of Sarcomere Length of a Single Cardiomyocyte during Contraction

Abstract

Mean sarcomere length of a cardiomyocyte is an important control parameter for physiology studies on a single cell level. For instance, accurate determination of the mean sarcomere lenght in real-time is essential for performing single cardiomyocyte contraction experiments.The aim of this work is to develop an accurate and efficient computational method for determining the mean sarcomere length from transmission images of a single contracting cardiomyocyte. This algorithm has to be robust to noise in input and exact for perfectly periodic input, that is, the best algorithm must have no systematic errors.To accomplish the goal of this work we are (i) using unbiased measure of similarities to eliminate systematic errors from conventional autocorrelation function (ACF) based methods when applied to region of interest of an image, (ii) using a semi-analytical semi-numerical approach for evaluating the similarity measure to take into account spatial dependence of neighboring image pixels, (iii) and using a detrend algorithm to extract the sarcomere striation pattern content from the microscopy images.The developed mean sarcomere length estimation procedure has superior computational efficiency and estimation accuracy compared to the conventional ACF and spectral analysis based methods using Fast Fourier Transform. As shown by analyzing synthetic images with the known periodicity, the estimates obtained by the developed method are more accurate at the sub-pixel level than ones obtained using ACF analysis. When applied in practice on rat cardiomyocytes, our method was found to be robust to the choice of the region of interest that may (i) include projections of carbon fibers and nucleus, (ii) have uneven background, and (iii) be slightly disoriented with respect to average direction of sarcomere striation pattern. The developed method is implemented in open-source software, see http://iocbio.googlecode.com.