The assessment of CSF spaces volume and distribution may help to characterise hydrocephalus.

No abstract

A key problem in the practical use of high intensity focused ultrasound (HIFU) as a tool for cancer treatment is the non-invasive characterization of the regions of tissue that have successfully been necrosed. Previously, we proposed an approach to image guidance, based on the use of RF data obtained from a diagnostic ultrasound transducer and a shape-based inverse scattering approach. Specifically, it was assumed that the lesion has an ellipsoidal shape defined by its center, size, orientation, and contrast (in sound-speed and attenuation) compared to the background. An inverse-type method was used to identify the ellipsoid parameters from the RF data. In this work we explore the robustness of this approach to a variety of conditions likely to be encountered in practice, specifically, the presence of an aberatting layer in the path, the formation of non-ellipsoidal lesions, for example, a ‘‘tadpole’’ shaped lesion that is commonly formed during HIFU, and the presence of multiple objects. Experiments using a clinical scanner and tissue phantoms are reported and we evaluate the method’s efficiency to different shapes and number of objects. [Work supported by NIH and CenSSIS.]

This paper presents a spectral autoregressive method dedicated to the detection of ultrasound contrast agents (USCA) from radiofrequency (rf) data. The method is based on second-order autoregressive (AR) modeling of the rf signal. Contrast agents induce a second harmonic, which may be efficiently detected through the AR spectrum using the magnitude of the second AR spectral peak (SM2). In contrast to multipulse methods that process two or more rf frames, our method processes a single rf frame. The method is tested by numerical simulation and on in vitro data for contrast agent concentrations ranging from 10(3) to 50 x 10(3) bubbles/ml (2 x 10(-6) to 10(-4) volumic concentration) and mechanical index (MI) ranging from 0.1 to 0.36. The results show that the proposed parameter SM2 enables one to detect correctly the contrast agent, in particular at low concentration and MI (the minimum difference in SM2 between tissue and USCA is 10 dB). Furthermore, the in-vitro data demonstrates that an adapted smoothing technique reduces the variability of SM2 and provides accurate and stable segmentation of the contrast agent perfusion region.