An integrated and highly sensitive ultrafast acoustoelectric imaging system for biomedical applications

Direct imaging of the electrical activation of the heart is crucial to better understand and diagnose diseases linked to arrhythmias. This work presents an ultrafast acoustoelectric imaging (UAI) system for direct and non-invasive ultrafast mapping of propagating current densities using the acoustoelectric effect. Acoustoelectric imaging is based on the acoustoelectric effect, the modulation of the medium's electrical impedance by a propagating ultrasonic wave. UAI triggers this effect with plane wave emissions to image current densities. An ultrasound research platform was fitted with electrodes connected to high common-mode rejection ratio amplifiers and sampled by up to 128 independent channels. The sequences developed allow for both real-time display of acoustoelectric maps and long ultrafast acquisition with fast off-line processing. The system was evaluated by injecting controlled currents into a saline pool via copper wire electrodes. Sensitivity to low current and low acoustic pressure were measured independently. Contrast and spatial resolution were measured for varying numbers of plane waves and compared to line per line acoustoelectric imaging with focused beams at equivalent peak pressure. Temporal resolution was assessed by measuring time-varying current densities associated with sinusoidal currents. Complex intensity distributions were also imaged in 3D. Electrical current densities were detected for injected currents as low as 0.56 mA. UAI outperformed conventional focused acoustoelectric imaging in terms of contrast and spatial resolution when using 3 and 13 plane waves or more, respectively. Neighboring sinusoidal currents with opposed phases were accurately imaged and separated. Time-varying currents were mapped and their frequency accurately measured for imaging frame rates up to 500 Hz. Finally, a 3D image of a complex intensity distribution was obtained. The results demonstrated the high sensitivity of the UAI system proposed. The plane wave based approach provides a highly flexible trade-off between frame rate, resolution and contrast. In conclusion, the UAI system shows promise for non-invasive, direct and accurate real-time imaging of electrical activation in vivo.