Automated quantitative analysis of multiple cardiomyocytes at the single‐cell level with three‐dimensional holographic imaging informatics

Abstract

Cardiomyocytes derived from human pluripotent stem cells are a promising tool for disease modeling, drug compound testing, and cardiac toxicity screening. Bio-image segmentation is a prerequisite step in cardiomyocyte image analysis by digital holography (DH) in microscopic configuration and has provided satisfactory results. In this study, we quantified multiple cardiac cells from segmented 3-dimensional DH images at the single-cell level and measured multiple parameters describing the beating profile of each individual cell. The beating profile is extracted by monitoring dry-mass distribution during the mechanical contraction-relaxation activity caused by cardiac action potential. We present a robust two-step segmentation method for cardiomyocyte low-contrast image segmentation based on region and edge information. The segmented single-cell contains mostly the nucleus of the cell since it is the best part of the cardiac cell, which can be perfectly segmented. Clustering accuracy was assessed by a silhouette index evaluation for k-means clustering and the Dice similarity coefficient (DSC) of the final segmented image. 3D representation of single of cardiomyocytes. The cell contains mostly the nucleus section and a small area of cytoplasm.

Measuring Absolute Cell Volume Using Quantitative-Phase Digital Holographic Microscopy and a Low-Cost, Open-Source, and 3D-Printed Flow Chamber

“…This determination results from an extensive analysis of 37 turnovers, randomly positioned over the entire imaging slit of the four different sample holders. Compared to the originally reported φ c stabilization time of 30-60 s for the mannitol-Nycodenz transition, this represents a reduction by at least a factor of three to six [16,25]. The fabrication parameter having the most restrictive tolerance to obtain the reported performances on the washout process is the concentric alignment of the axes of the channels to insert the microtubes.…”

“…Alternatively, quantitative-phase imaging (QPI) consists of an ensemble of microscopy techniques offering the possibility of performing label-free, non-invasive, high-resolution, and real-time imaging of transparent microscopic specimens such as living cells in culture [10,11]. QPI measures the minute phase shift, namely the quantitative-phase signal (QPS), that transparent specimens induce on the diffracted wave-front, as long as the observed sample is a weakly-scattering object, i.e., differing from the surrounding medium only by a slight difference of refractive index [12][13][14][15][16][17]. The QPS, proportional to the optical path length (OPL), thus depends on both the intracellular refractive index (IRI) and the cell thickness.…”

Diffraction-based technology for the monitoring of contraction dynamics in 3D and 2D tissue models

“…Cardiac dynamic of 2D-cell cultures were studied using holographic microscopy, revealing its vertical compound. Despite the ability of holography to reveal 3D dynamic, this technology is neither applicable to real 3D tissue with multiple cell layers nor simple enough for parallelization [10][11][12].…”

Automated quantification study of human cardiomyocyte synchronization using holographic imaging

“…of studying s ues available, . This techniqu croorganism id changes in blo ganism by in-li nd assessmen is used to exa iac muscle cel vel [28]. The st communicate scular wall.…”

“…Therefore, it does not address the single-cell level quantification study. The study in [28] proposes a method to segment CMs and extract single cells to shows the quantification for individual cells. DHM is capable of imaging cells by recording the phase retardation of a coherent or semicoherent light wave transmitted through the transparent sample, wherein the transparent specimens shift the phase of light instead of intensity alternations.…”