4.7 Article

Smartphone-based particle image velocimetry for cardiovascular flows applications: A focus on coronary arteries

Journal

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fbioe.2022.1011806

Keywords

Hemodynamics; PIV; stenosis; flow visualization; in vitro experiment

Funding

  1. Italian Ministry of Education, University and Research
  2. [FISR 2019_03221]

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This study presents an experimental set-up for characterizing the fluid dynamics in healthy and stenosed coronary arteries. The proposed smart-PIV approach, using a smartphone camera and low-power laser, provides both qualitative flow visualizations and quantitative results. Comparisons with conventional PIV measurements show good agreement, making smart-PIV a promising and low-cost methodology for cardiovascular flow characterization.
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 (& AP;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.

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