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PIV-MyoMonitor: an accessible particle image velocimetry-based software tool for advanced contractility assessment of cardiac organoids.

ABSTRACT: Induced pluripotent stem cell (iPSC)-derived cardiac organoids offer a versatile platform for personalized cardiac toxicity assessment, drug screening, disease modeling, and regenerative therapies. While previous image-based contractility analysis techniques allowed the assessment of contractility of two-dimensional cardiac models, they face limitations, including encountering high noise levels when applied to three-dimensional organoid models and requiring expensive equipment. Additionally, they offer fewer functional parameters compared to commercial software. To address these challenges, we developed an open-source, particle image velocimetry-based software (PIV-MyoMonitor) and demonstrated its capacity for accurate contractility analysis in both two- and three-dimensional cardiac models using standard lab equipment. Comparisons with four other open-source software programs highlighted the capability of PIV-MyoMonitor for more comprehensive quantitative analysis, providing 22 functional parameters and enhanced video outputs. We showcased its applicability in drug screening by characterizing the response of cardiac organoids to a known isotropic drug, isoprenaline. In sum, PIV-MyoMonitor enables reliable contractility assessment across various cardiac models without costly equipment or software. We believe this software will benefit a broader scientific community.

SUBMITTER: Lee H

PROVIDER: S-EPMC10964252 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature

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PIV-MyoMonitor: an accessible particle image velocimetry-based software tool for advanced contractility assessment of cardiac organoids.

Lee Hoyeon H Kim Boyoung B Yun Jiyue J Bae Jinseung J Park Sungsu S Jeon Junseok J Jang Hye Ryoun HR Lee Jaecheol J Lee Soah S

Frontiers in bioengineering and biotechnology 20240312

Induced pluripotent stem cell (iPSC)-derived cardiac organoids offer a versatile platform for personalized cardiac toxicity assessment, drug screening, disease modeling, and regenerative therapies. While previous image-based contractility analysis techniques allowed the assessment of contractility of two-dimensional cardiac models, they face limitations, including encountering high noise levels when applied to three-dimensional organoid models and requiring expensive equipment. Additionally, the ...[more]

PMID: 38532875

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Project description:BackgroundThe technical development of imaging techniques in life sciences has enabled the three-dimensional recording of living samples at increasing temporal resolutions. Dynamic 3D data sets of developing organisms allow for time-resolved quantitative analyses of morphogenetic changes in three dimensions, but require efficient and automatable analysis pipelines to tackle the resulting Terabytes of image data. Particle image velocimetry (PIV) is a robust and segmentation-free technique that is suitable for quantifying collective cellular migration on data sets with different labeling schemes. This paper presents the implementation of an efficient 3D PIV package using the Julia programming language-quickPIV. Our software is focused on optimizing CPU performance and ensuring the robustness of the PIV analyses on biological data.ResultsQuickPIV is three times faster than the Python implementation hosted in openPIV, both in 2D and 3D. Our software is also faster than the fastest 2D PIV package in openPIV, written in C++. The accuracy evaluation of our software on synthetic data agrees with the expected accuracies described in the literature. Additionally, by applying quickPIV to three data sets of the embryogenesis of Tribolium castaneum, we obtained vector fields that recapitulate the migration movements of gastrulation, both in nuclear and actin-labeled embryos. We show normalized squared error cross-correlation to be especially accurate in detecting translations in non-segmentable biological image data.ConclusionsThe presented software addresses the need for a fast and open-source 3D PIV package in biological research. Currently, quickPIV offers efficient 2D and 3D PIV analyses featuring zero-normalized and normalized squared error cross-correlations, sub-pixel/voxel approximation, and multi-pass. Post-processing options include filtering and averaging of the resulting vector fields, extraction of velocity, divergence and collectiveness maps, simulation of pseudo-trajectories, and unit conversion. In addition, our software includes functions to visualize the 3D vector fields in Paraview.

Project description:An experimental set-up is presented for the in vitro characterization of the fluid dynamics in personalized phantoms of healthy and stenosed coronary arteries. The proposed set-up was fine-tuned with the aim of obtaining a compact, flexible, low-cost test-bench for biomedical applications. Technically, velocity vector fields were measured adopting a so-called smart-PIV approach, consisting of a smartphone camera and a low-power continuous laser (30 mW). Experiments were conducted in realistic healthy and stenosed 3D-printed phantoms of left anterior descending coronary artery reconstructed from angiographic images. Time resolved image acquisition was made possible by the combination of the image acquisition frame rate of last generation commercial smartphones and the flow regimes characterizing coronary hemodynamics (velocities in the order of 10 cm/s). Different flow regimes (Reynolds numbers ranging from 20 to 200) were analyzed. The smart-PIV approach was able to provide both qualitative flow visualizations and quantitative results. A comparison between smart-PIV and conventional PIV (i.e., the gold-standard experimental technique for bioflows characterization) measurements showed a good agreement in the measured velocity vector fields for both the healthy and the stenosed coronary phantoms. Displacement errors and uncertainties, estimated by applying the particle disparity method, confirmed the soundness of the proposed smart-PIV approach, as their values fell within the same range for both smart and conventional PIV measured data (≈5% for the normalized estimated displacement error and below 1.2 pixels for displacement uncertainty). In conclusion, smart-PIV represents an easy-to-implement, low-cost methodology for obtaining an adequately robust experimental characterization of cardiovascular flows. The proposed approach, to be intended as a proof of concept, candidates to become an easy-to-handle test bench suitable for use also outside of research labs, e.g., for educational or industrial purposes, or as first-line investigation to direct and guide subsequent conventional PIV measurements.

Project description:BackgroundUnderstanding the hemodynamics of an abdominal aortic aneurysm (AAA) is crucial for risk assessment and treatment planning. This study introduces a low-cost, patient-specific in vitro AAA model to investigate hemodynamics using particle image velocimetry (PIV) and flow-simulating circuit, validated through fluid-structure interaction (FSI) simulations.MethodsIn this study, 3D printing was employed to manufacture a flexible patient-specific AAA phantom using a lost-core casting technique. A pulsatile flow circuit was constructed using off-the-shelf components. A particle image velocimetry (PIV) setup was built using an affordable laser source and global shutter camera, and finally, the flow field inside the AAA was analyzed using open-source software. Fluid-structure interaction (FSI) simulations were performed to enhance our understanding of the flow field, and the results were validated by PIV analysis. Both steady-state and transient flow conditions were investigated.ResultsOur experimental setup replicated physiological conditions, analyzing arterial wall deformations and flow characteristics within the aneurysm. Under constant flow, peak wall deformations and flow velocities showed deviations within - 12% to + 27% and - 7% to + 5%, respectively, compared to FSI simulations. Pulsatile flow conditions further demonstrated a strong correlation (Pearson coefficient 0.85) in flow velocities and vectors throughout the cardiac cycle. Transient phenomena, particularly the formation and progression of vortex structures during systole, were consistently depicted between experimental and numerical models.ConclusionsBy bridging high-fidelity experimental observations with comprehensive computational analyses, this study underscores the potential of integrated methodologies in enhancing our understanding of AAA pathophysiology. The convergence of realistic AAA phantoms, precise PIV measurements at affordable cost point, and validated FSI models heralds a new paradigm in vascular research, with significant implications for personalized medicine and bioengineering innovations.

Dataset Information

PIV-MyoMonitor: an accessible particle image velocimetry-based software tool for advanced contractility assessment of cardiac organoids.

Publications

PIV-MyoMonitor: an accessible particle image velocimetry-based software tool for advanced contractility assessment of cardiac organoids.

Similar Datasets

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