High-resolution transcranial ultrasound imaging in humans has been a persistent challenge for ultrasound due to the imaging degradation effects from aberration and reverberation. These mechanisms depend strongly on skull morphology and have high variability across individuals. Here, we demonstrate the feasibility of human transcranial super-resolution imaging using a geometrical focusing approach to efficiently concentrate energy at the region of interest, and a phase correction focusing approach that takes the skull morphology into account. It is shown that using the proposed focused super-resolution method, we can image a 208- $\mu \text{m}$ microtube behind a human skull phantom in both an out-of-plane and an in-plane configuration. Individual phase correction profiles for the temporal region of the human skull were calculated and subsequently applied to transmit–receive a custom focused super-resolution imaging sequence through a human skull phantom, targeting the 208- $\mu \text{m}$ diameter microtube at 68.5 mm in depth and at 2.5 MHz. Microbubble contrast agents were diluted to a concentration of $1.6\times 10^{6}$ bubbles/mL and perfused through the microtube. It is shown that by correcting for the skull aberration, the RF signal amplitude from the tube improved by a factor of 1.6 in the out-of-plane focused emission case. The lateral registration error of the tube’s position, which in the uncorrected case was 990 $\mu \text{m}$ , was reduced to as low as 50 $\mu \text{m}$ in the corrected case as measured in the B-mode images. Sensitivity in microbubble detection for the phase-corrected case increased by a factor of 1.48 in the out-of-plane imaging case, while, in the in-plane target case, it improved by a factor of 1.31 while achieving an axial registration correction from an initial 1885- $\mu \text{m}$ error for the uncorrected emission, to a 284- $\mu \text{m}$ error for the corrected counterpart. These findings suggest that super-resolution imaging may be used far more generally as a clinical imaging modality in the brain.

Rationale: Structure and function of the microvasculature provides critical information about disease state, can be used to identify local regions of pathology, and has been shown to be an indicator of response to therapy. Improved methods of assessing the microvasculature with non-invasive imaging modalities such as ultrasound will have an impact in biomedical theranostics. Ultrasound localization microscopy (ULM) is a new technology which allows processing of ultrasound data for visualization of microvasculature at a resolution better than allowed by acoustic diffraction with traditional ultrasound systems. Previous application of this modality in brain imaging has required the use of invasive procedures, such as a craniotomy, skull-thinning, or scalp removal, all of which are not feasible for the purpose of longitudinal studies.

The internal deformation of the brain is far more complex than the rigid motion of the skull. An ultrasound imaging technique that we have developed has a combination of penetration, frame-rate, and motion-detection accuracy required to directly observe the formation and evolution of shear shock waves in the brain. Experiments at low impacts on the traumatic-brain-injury scale demonstrate that they are spontaneously generated and propagate within the porcine brain. Compared to the initially smooth impact, the acceleration at the shock front is amplified up to a factor of 8.5. This highly localized increase in acceleration suggests that shear shock waves are a previously unappreciated mechanism that could play a significant role in traumatic brain injury.

Recent advances in high frame rate biomedical ultrasound have led to the development of ultrasound localization microscopy (ULM), a method of imaging microbubble (MB) contrast agents beyond the diffraction limit of conventional coherent imaging techniques. By localizing and tracking the positions of thousands of individual MBs, ultrahigh resolution vascular maps are generated which can be further analyzed to study disease. Isolating bubble echoes from tissue signal is a key requirement for super-resolution imaging which relies on the spatiotemporal separability and localization of the bubble signals. To date, this has been accomplished either during acquisition using contrast imaging sequences or post-beamforming by applying a spatiotemporal filter to the B-mode images. Superharmonic imaging (SHI) is another contrast imaging method that separates bubbles from tissue based on their strongly nonlinear acoustic properties. This approach is highly sensitive, and, unlike spatiotemporal filters, it does not require decorrelation of contrast agent signals. Since this superharmonic method does not rely on bubble velocity, it can detect completely stationary and moving bubbles alike. In this work, we apply SHI to ULM and demonstrate an average improvement in SNR of 10.3-dB in vitro when compared with the standard singular value decomposition filter approach and an increase in SNR at low flow (0.27 μm/frame) from 5 to 16.5 dB. Additionally, we apply this method to imaging a rodent kidney in vivo and measure vessels as small as 20 μm in diameter after motion correction.

Glioblastoma is an aggressive brain cancer with a very poor prognosis in which less than 6% of patients survive more than 5 years post-diagnosis. The outcome of this disease for many patients may be improved by early detection. This could provide clinicians with the information needed to take early action for treatment. In this work, we present the utilization of a noninvasive, fully volumetric ultrasonic imaging method to assess microvascular change during the evolution of glioblastoma in mice. Volumetric ultrasound localization microscopy (ULM) was used to observe statistically significant (p<0.05) reduction in the appearance of functional vasculature over the course of three weeks. We also demonstrate evidence suggesting the reduction of vascular flow for vessels peripheral to the tumor. With an 82.5% consistency rate in acquiring high-quality vascular images, we demonstrate the possibility of volumetric ULM as a longitudinal method for microvascular characterization of neurological disease.