How to optimize intracardiac blood flow tracking by echocardiographic particle image velocimetry? Exploring the influence of data acquisition using computer-generated data sets.

Aims: Echocardiographic particle image velocimetry (EPIV) has been used for tracking contrast-enhanced intracavitary blood flow. Little is known, however, how basic imaging parameters (line density, frame rate, contrast bubble density) affect the quality of such tracking results. Our study aimed at investigating this by using simulated echo data sets.

Methods And Results: A computational three-dimensional (3D) blood flow field of the left ventricle (LV) was built using Fluent 12.1 (ANSYS Inc., USA). Then, the 3D motion of contrast microbubbles was simulated and 2D B-mode image loops were obtained (f = 4.5 MHz; 50 sector angle) and analysed using flow tracking software (Omega Flow, Siemens, USA). Vorticity and the resulting in-plane velocity vector field was calculated at different frame rates (227, 113, 76, and 57 fps) and bubble densities (100, 63, 36, 19, 10, and 3 bubbles/mL) and compared with the ground truth known from the computational LV flow model. The normal distribution of the amplitude error and angle error histograms confirmed the overall good performance of the tracking method. In the standard deviation analysis of error histograms, tracked velocity amplitudes correlated best with the ground truth at 10 bubbles/mL and 227 fps (45.81 ± 3.43%, P < 0.05), while the best performance of flow direction estimates was at 10 bubbles/mL and 76 fps (25.41 ± 1.22°, P < 0.05). The correlation of estimated and true vorticity tended to grow with increasing frame rate and was optimal at 19 bubbles/mL and 113 fps (r = 0.79 ± 0.02).

Conclusion: To achieve accurate vorticity measurements, frame rate acquisitions as 113 fps and contrast bubble density of 19 bubbles/mL are needed.