Prevention and early detection of atherosclerosis are critical for protection against subsequent circulatory disease. In this study, an automated two-dimensional ultrasonic-measurement-integrated (2D-UMI) blood flow analysis system for clinical diagnosis was developed, and the feasibility of the system for hemodynamic analysis in a carotid artery was revealed. The system automatically generated a 2D computational domain based on ultrasound color Doppler imaging and performed a UMI simulation of blood flow field to visualize hemodynamics in the domain. In the UMI simulation, compensation of errors was applied by adding feedback signals proportional to the differences between Doppler velocities by measurement and computation while automatically estimating the cross-sectional average inflow velocity. The necessity of adjustment of the feedback gain was examined by analyzing blood flow in five carotid arteries: three healthy, one sclerosed, and one stenosed. The same feedback gain was generally applicable for the 2D-UMI simulation in all carotid arteries, depending on target variables. Thus, the present system was shown to be versatile in the sense that the parameter is patient independent. Moreover, the possibility of a new diagnostic method based on the hemodynamic information obtained by the 2D-UMI simulation, such as a waveform of the cross-sectional average inflow velocity and wall shear stress distributions, was suggested.

Two-dimensional ultrasonic-measurement-integrated (2D-UMI) simulation correctly reproduces hemodynamics even with an inexact inflow velocity distribution. This study aimed to investigate which is superior, a two-dimensional ordinary (2D-O) simulation with an accurate inflow velocity distribution or a 2D-UMI simulation with an inaccurate one. 2D-O and 2D-UMI simulations were performed for blood flow in a carotid artery with four upstream velocity boundary conditions: a velocity profile with backprojected measured Doppler velocities (condition A), and velocity profiles with a measured Doppler velocity distribution, a parabolic one, and a uniform one, magnitude being obtained by inflow velocity estimation (conditions B, C, and D, respectively). The error of Doppler velocity against the measurement data was sensitive to the inflow velocity distribution in the 2D-O simulation, but not in the 2D-UMI simulation with the inflow velocity estimation. Among the results in conditions B, C, and D, the error in the worst 2D-UMI simulation with condition D was 31 % of that in the best 2D-O simulation with condition B, implying the superiority of the 2D-UMI simulation with an inaccurate inflow velocity distribution over the 2D-O simulation with an exact one. Condition A resulted in a larger error than the other conditions in both the 2D-O and 2D-UMI simulations.

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