Congenital heart defects (CHDs) are the most common birth defect, affecting between 4 and 75 per 1,000 live births depending on the inclusion criteria. Many of these defects can be traced to defects of cardiac cushions, critical structures during development that serve as precursors to many structures in the mature heart, including the atrial and ventricular septa, and all four sets of cardiac valves. Epithelial-mesenchymal transition (EMT) is the process through which cardiac cushions become populated with cells. Altered cushion size or altered cushion cell density has been linked to many forms of CHDs, however, quantitation of cell density in the complex 3D cushion structure poses a significant challenge to conventional histology. Optical coherence tomography (OCT) is a technique capable of 3D imaging of the developing heart, but typically lacks the resolution to differentiate individual cells. Our goal is to develop an algorithm to quantitatively characterize the density of cells in the developing cushion using 3D OCT imaging. First, in a heart volume, the atrioventricular (AV) cushions were manually segmented. Next, all voxel values in the region of interest were pooled together to generate a histogram. Finally, two populations of voxels were classified using either K-means classification, or a Gaussian mixture model (GMM). The voxel population with higher values represents cells in the cushion. To test the algorithm, we imaged and evaluated avian embryonic hearts at looping stages. As expected, our result suggested that the cell density increases with developmental stages. We validated the technique against scoring by expert readers.
Siyao Yu, Shi Gu, Xiaowei Zhao, Yehe Liu, Michael W. Jenkins, Michiko Watanabe, and Andrew M. Rollins, "3D characterization of EMT cell density in developing cardiac cushions using optical coherence tomography (Conference Presentation)," Proc. SPIE 10053, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXI, 100530Q (Presented at SPIE BiOS: January 31, 2017; Published: 19 April 2017); https://doi.org/10.1117/12.2254924.5371723140001.
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