Visualizing Drosophila Melanogaster heart beating in 4D through Optical Coherence Tomography

Introduction:: The heart is a dynamic organ with complex beating patterns and morphology, the understanding of which is critical to understanding the mechanisms underlying cardiac diseases. Drosophila Melanogaster is a powerful tool for cardiac research due to its genome having homologs to many human diseases, and its short life cycle, making it a useful tool to study heart development. Its cardiac function has been studied using optical coherence tomography (OCT), which can capture M-mode images of two dimensions over time by taking repeated images in the same location. Recently, Faubert, et al. developed an open-source code for the 4D synchronization (3D volume over time) of OCT images of repeated cardiac motion using the time difference cardiogram (TDCG), which they demonstrated using mouse embryos [2]. This algorithm measures the difference between successive pixels as well as overall high frequency and low frequency components of the image sequences in order to determine the overall heart period. In this study, we generate 4D videos of Drosophila heart beating, providing volumetric snapshots at each point in the cardiac cycle in order to characterize heart development and abnormal heart function.


Materials and Methods:: Wild type Drosophila pupa were imaged on a piece of double-sided tape attached to a glass slide, with the dorsal side containing the heart tube facing the incident light. 400 A-scans by 400 B-scans were collected, with each B scan location containing 50 repeated frames. The frame rate was 40 Hz, compared to the measured pupal heart rate of 2.5 Hz, allowing for each B scan location to capture between 2 to 3 heartbeat cycles. Images were then inputted into the TDCG synchronization algorithm, which calculated a heart period of 20 frames and synchronized the images accordingly, creating a stack of images with one heart tube volume per each time point sampled. The output image stack contained one synchronized heartbeat at each depth, which was later segmented and visualized using ImageJ.

Results, Conclusions, and Discussions:: The TDCG algorithm was able to synchronize heart beating videos, providing snapshots of the heart shape at each point in the cardiac cycle. Fig 1. A) shows three B scans at different locations from a heart volume generated from dataset which was not synchronized. The cardiac cycle is not the same at every B scan in volume, and because of motion of the heart during collection, both systolic (smallest area) and diastolic (largest area) period are shown in the images. Fig 1. B) shows the same analysis in the same pupa after the image set was synchronized, where the heart is in diastole. There is a smooth transition between successive images in depth, as all images are at the same point in the cardiac cycle. This segmentation can be repeated between all different points in the cardiac cycle to provide a quantitative measurement of stroke volume.
This study was able to synchronize a 3D beating Drosophila pupa heart over time, allowing for the study of heart tube morphology without motion artifacts. In future studies, this will be able to study how the heart morphology changes over time in cardiac disease models or under cardiac optogenetic stimulation, which alters the baseline beating pattern. Once videos are generated, the stroke volume and cardiac output can also be more accurately measured, providing a better characterization of abnormal cardiac function.


Acknowledgements (Optional): : This work was supported by NIH grants R01EB025209, R01HL156265, R21EB03268401A1.

References (Optional): : [1]Men J, et al. J Vis Exp. 2016 Dec 12;(118):55002. [2] Faubert A, et al. Biomed Opt Express. 2022 Dec 14;14(1):163-181.