title: Simulation-based validation for four- dimensional multi-channel ultrasound current source density imaging.
abstract: Ultrasound current source density imaging (UCSDI), which has application to the heart and brain, exploits the acoustoelectric (AE) effect and Ohm's law to detect and map an electrical current distribution. In this study, we describe 4-D UCSDI simulations of a dipole field for comparison and validation with bench-top experiments. The simulations consider the properties of the ultrasound pulse as it passes through a conductive medium, the electric field of the injected dipole, and the lead field of the detectors. In the simulation, the lead fields of detectors and electric field of the dipole were calculated by the finite element (FE) method, and the convolution and correlation in the computation of the detected AE voltage signal were accelerated using 3-D fast Fourier transforms. In the bench-top experiment, an electric dipole was produced in a bath of 0.9% NaCl solution containing two electrodes, which injected an ac pulse (200 Hz, 3 cycles) ranging from 0 to 140 mA. Stimulating and recording electrodes were placed in a custom electrode chamber made on a rapid prototype printer. Each electrode could be positioned anywhere on an x-y grid (5 mm spacing) and individually adjusted in the depth direction for precise control of the geometry of the current sources and detecting electrodes. A 1-MHz ultrasound beam was pulsed and focused through a plastic film to modulate the current distribution inside the saline-filled tank. AE signals were simultaneously detected at a sampling frequency of 15 MHz on multiple recording electrodes. A single recording electrode is sufficient to form volume images of the current flow and electric potentials. The AE potential is sensitive to the distance from the dipole, but is less sensitive to the angle between the detector and the dipole. Multi-channel UCSDI potentially improves 4-D mapping of bioelectric sources in the body at high spatial resolution, which is especially important for diagnosing and guiding treatment of cardiac and neurologic disorders, including arrhythmia and epilepsy.
authors.forename: Zhaohui
authors.initials: Z
authors.lastname: Wang
authors.forename: Russell S
authors.initials: RS
authors.lastname: Witte
mesh_terms: D000465:Algorithms; D000818:Animals; D018780:Body Surface Potential Mapping / Q000379:methods*; D003198:Computer Simulation; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008954:Models, Biological; D010992:Plethysmography, Impedance / Q000379:methods*; D011829:Radiation Dosage; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014463:Ultrasonography / Q000379:methods*