Passive acoustic mapping utilizing optimal beamforming in ultrasound therapy monitoring.

Passive acoustic mapping (PAM) is a promising imaging method that enables real-time three-dimensional monitoring of ultrasound therapy through the reconstruction of acoustic emissions passively received on an array of ultrasonic sensors. A passive beamforming method is presented that provides greatly improved spatial accuracy over the conventionally used time exposure acoustics (TEA) PAM reconstruction algorithm. Both the Capon beamformer and the robust Capon beamformer (RCB) for PAM are suggested as methods to reduce interference artifacts and improve resolution, which has been one of the experimental issues previously observed with TEA. Simulation results that replicate the experimental artifacts are shown to suggest that bubble interactions are the chief cause. Analysis is provided to show that these multiple bubble artifacts are generally not reduced by TEA, while Capon-based methods are able to reduce the artifacts. This is followed by experimental results from in vitro experiments and in vivo oncolytic viral therapy trials that show improved results in PAM, where RCB is able to more accurately localize the acoustic activity than TEA.

Thin-film sparse boundary array design for passive acoustic mapping during ultrasound therapy.

A new 2-D hydrophone array for ultrasound therapy monitoring is presented, along with a novel algorithm for passive acoustic mapping using a sparse weighted aperture. The array is constructed using existing polyvinylidene fluoride (PVDF) ultrasound sensor technology, and is utilized for its broadband characteristics and its high receive sensitivity. For most 2-D arrays, high-resolution imagery is desired, which requires a large aperture at the cost of a large number of elements. The proposed array's geometry is sparse, with elements only on the boundary of the rectangular aperture. The missing information from the interior is filled in using linear imaging techniques. After receiving acoustic emissions during ultrasound therapy, this algorithm applies an apodization to the sparse aperture to limit side lobes and then reconstructs acoustic activity with high spatiotemporal resolution. Experiments show verification of the theoretical point spread function, and cavitation maps in agar phantoms correspond closely to predicted areas, showing the validity of the array and methodology.

Fusion of magnetometer and gradiometer sensors of MEG in the presence of multiplicative error.

Novel neuroimaging techniques have provided unprecedented information on the structure and function of the living human brain. Multimodal fusion of data from different sensors promises to radically improve this understanding, yet optimal methods have not been developed. Here, we demonstrate a novel method for combining multichannel signals. We show how this method can be used to fuse signals from the magnetometer and gradiometer sensors used in magnetoencephalography (MEG), and through extensive experiments using simulation, head phantom and real MEG data, show that it is both robust and accurate. This new approach works by assuming that the lead fields have multiplicative error. The criterion to estimate the error is given within a spatial filter framework such that the estimated power is minimized in the worst case scenario. The method is compared to, and found better than, existing approaches. The closed-form solution and the conditions under which the multiplicative error can be optimally estimated are provided. This novel approach can also be employed for multimodal fusion of other multichannel signals such as MEG and EEG. Although the multiplicative error is estimated based on beamforming, other methods for source analysis can equally be used after the lead-field modification.

A bio-impedance probe to assess liver steatosis during transplant surgery.

This work addresses the design of a bioimpedance probe to assess steatosis on the exposed liver in the donor during liver transplant surgery. Whereas typically bioimpedance uses needle probes to avoid surface effects, for clinical reasons a non-penetrative probe is required. In addition the need to ensure that the measurement is representative of the bulk tissue suggests a larger probe than is normally used to ensure a sufficiently large measurement volume. Using a simple model, simulations and tests on bovine liver, this paper investigates the relationship between probe dimensions and depth of measurement penetration and investigates the accuracy which might be expected in a configuration suitable for use in the operating theatre on intact but exposed livers. A probe using ECG electrodes is proposed and investigated.

Model-based ultrasound temperature visualization during and following HIFU exposure.

This paper describes the application of signal processing techniques to improve the robustness of ultrasound feedback for displaying changes in temperature distribution in treatment using high-intensity focused ultrasound (HIFU), especially at the low signal-to-noise ratios that might be expected in in vivo abdominal treatment. Temperature estimation is based on the local displacements in ultrasound images taken during HIFU treatment, and a method to improve robustness to outliers is introduced. The main contribution of the paper is in the application of a Kalman filter, a statistical signal processing technique, which uses a simple analytical temperature model of heat dispersion to improve the temperature estimation from the ultrasound measurements during and after HIFU exposure. To reduce the sensitivity of the method to previous assumptions on the material homogeneity and signal-to-noise ratio, an adaptive form is introduced. The method is illustrated using data from HIFU exposure of ex vivo bovine liver. A particular advantage of the stability it introduces is that the temperature can be visualized not only in the intervals between HIFU exposure but also, for some configurations, during the exposure itself.