A model and method to accurately estimate the local speed of sound in tissue from pulse-echo ultrasound data is presented. The model relates the local speeds of sound along a wave propagation path to the average speed of sound over the path, and allows one to avoid bias in the sound-speed estimates that can result from overlying layers of subcutaneous fat and muscle tissue. Herein, the average speed of sound using the approach by Anderson and Trahey is measured, and then the authors solve the proposed model for the local sound-speed via gradient descent. The sound-speed estimator was tested in a series of simulation and ex vivo phantom experiments using two-layer media as a simple model of abdominal tissue. The bias of the local sound-speed estimates from the bottom layers is less than 6.2 m/s, while the bias of the matched Anderson's estimates is as high as 66 m/s. The local speed-of-sound estimates have higher standard deviation than the Anderson's estimates. When the mean local estimate is computed over a 5-by-5 mm region of interest, its standard deviation is reduced to less than 7 m/s.

We explore the possibility of using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) to discern microstructural abnormalities in the hippocampus indicative of mesial temporal sclerosis (MTS) at the subfield level. Methods:We analyzed data from 57 patients with refractory epilepsy who previously underwent 3.0-T magnetic resonance imaging (MRI) including DTI as a standard part of presurgical workup. We collected information about each subject's seizure semiology, conventional electroencephalography (EEG), highdensity EEG, positron emission tomography reports, surgical outcome, and available histopathological findings to assign a final diagnostic category. We also reviewed the radiology MRI report to determine the radiographic category. DTIand NODDI-based metrics were obtained in the hippocampal subfields.Results: By examining diffusion characteristics among subfields in the final diagnostic categories, we found lower orientation dispersion indices and elevated axial diffusivity in the dentate gyrus in MTS compared to no MTS. By similarly examining among subfields in the different radiographic categories, we found all diffusion metrics were abnormal in the dentate gyrus and CA1. We finally examined whether diffusion imaging would better inform a radiographic diagnosis with respect to the final diagnosis, and found that dentate diffusivity suggested subtle changes that may help confirm a positive radiologic diagnosis. Significance:The results suggest that diffusion metric analysis at the subfield level, especially in dentate gyrus and CA1, maybe useful for clinical confirmation of MTS.

patients undergoing SLAH. Independent of surgery type, seizure freedom is associated with improved non-verbal memory outcome.

Maladaptive myelination may be related to the increasing frequency of absence seizures. To explore this connection, we performed MRI microstructural measurements in ex vivo mouse brains from the Scn8amed+/- model of absence epilepsy in two cohorts of mice at two points of their development, both before and after seizures were well established. Our MRI g-ratio results strongly agree with our previous findings based on electron microscopy and show a clear alteration of myelination throughout the anterior portion of the corpus callosum.

We performed subfield characterization of Mesial Temporal Sclerosis (MTS) using diffusion metrics. Analysis of MRI from 57 temporal lobe epilepsy patients was based on categorization from medical records, initial clinical radiological reads, and diagnostic changes after subfield DTI analyses. We observed differences in mean diffusivity, axial diffusivity and orientation dispersion in the dentate gyrus of patients with MTS. Differences between MTS and control patients were more pronounced in left MTS.  We demonstrate how these methods may aid in the MRI identification of MTS.