Assessment of heart function in zebrafish larvae using electrocardiography (ECG) is a potentially useful tool in developing cardiac treatments and the assessment of drug therapies. In order to better understand how a measured ECG waveform is related to the structure of the heart, its position within the larva and the position of the electrodes, a 3D model of a 3 days post fertilisation (dpf) larval zebrafish was developed to simulate cardiac electrical activity and investigate the voltage distribution throughout the body. The geometry consisted of two main components; the zebrafish body was modelled as a homogeneous volume, while the heart was split into five distinct regions (sinoatrial region, atrial wall, atrioventricular band, ventricular wall and heart chambers). Similarly, the electrical model consisted of two parts with the body described by Laplace’s equation and the heart using a bidomain ionic model based upon the Fitzhugh-Nagumo equations. Each region of the heart was differentiated by action potential (AP) parameters and activation wave conduction velocities, which were fitted and scaled based on previously published experimental results. ECG measurements in vivo at different electrode recording positions were then compared to the model results. The model was able to simulate action potentials, wave propagation and all the major features (P wave, R wave, T wave) of the ECG, as well as polarity of the peaks observed at each position. This model was based upon our current understanding of the structure of the normal zebrafish larval heart. Further development would enable us to incorporate features associated with the diseased heart and hence assist in the interpretation of larval zebrafish ECGs in these conditions.

Automatic analysis of larval zebrafish electrocardiographs (ECG) is essential for high-throughput measurements in environmental toxicity assays, cardiotoxicity measurements and drug screening. We have developed a MATLAB based software is built on methods that have previously been used to analyze human ECG, such as the Pan-Tompkins algorithm and Wavelet. For the first time these sophisticated tools have been applied to larval zebrafish ECG to automatically characterize the heart-beat waveforms. The ability of the automated algorithm to detect the QT interval for both normal and pharmacologically altered larval ECG is found and compared to previously used software that is built into LabChart® (AD Instruments). Using wavelet transforms it is shown that the typical larval ECG features are within the frequency range of 1 to 31 Hz. It is also shown that the automated software is capable of detecting QTc (heartrate corrected heartbeat interval) changes within pharmacologically altered zebrafish larval ECG. The automated process is a significant improvement on the approaches that were previously applied to the zebrafish ECG. The automated process described here that is based on established techniques of analyzing ECG can sensitively measure pharmacologically induced changes in the ECG. The novel, automated software is faster, more sensitive at detecting ECG changes and less dependent on user involvement, thus minimizing user error and human bias. The automated process can also be applied to human ECG.