Adaptive Ultrasound Neuroimaging

Abstract

Ultrasound imaging is a widespread clinical tool, known best for prenatal examinations of developing human embryos. Recently, a technological breakthrough has revolutionized the field of ultrasound imaging by enabling imaging at thousands of frames per second. This increase in temporal resolution has opened the door to many new applications, such as monitoring the subtle motion of heart walls, measuring electromechanical waves in muscles and detecting the stiffness of organs. Furthermore, the fast frame rates have significantly improved ultrasound sensitivity to small vessels and enables monitoring of local changes in blood flow. This has let to the development of functional ultrasound imaging (fUS) in 2011.

Functional ultrasound is a new neuroimaging modality that allows imaging of brain function at high spatial and temporal resolution. fUS measures variations in cerebral blood flow that occur in response to neuronal activation, a phenomenon known as neurovascular coupling, and therefore provides an indirect measure of brain activity. The underlying principle is similar as what is measured in functional magnetic resonance imaging (fMRI), the current clinical standard for brain imaging. Compared to fMRI, fUS offers several advantages, it is portable, cost-effective, higher temporal resolution, and higher sensitivity to cerebral blood flow. This makes it a promising tool for both preclinical neuroscience, and clinical application. However, there remain significant challenges to overcome before fUS can be widely adopted in clinical settings.

First, the brain is protected by the skull, which poses a barrier for ultrasound waves. The skull bone distorts and attenuates ultrasound signals, leading to decreased transcranial image quality. Therefore, most studies to date are restricted to animal models, where the skull can be surgically removed or thinned. In humans, fUS has been applied during intraoperative procedures, where the skull is removed, and the brain is exposed.
Second, fUS generates enormous amounts of data, which complicates its use in real-time applications.

This thesis addresses both challenges. It focuses on enhancing transcranial image quality, bringing us closer to fully noninvasive, high resolution brain imaging. In addition, it introduces methods for reconfigurable functional imaging, aimed at reducing data rates to enable real time decoding of brain activity into actionable outputs. Together, these advances increase the translational potential of fUS and lower the barrier for clinical and neuroscience adoption.

The field of aberration correction consist in improving image quality by compensating for distortions caused by the medium through which the ultrasound waves travel. In this thesis, we apply aberration correction to restore transcranial image quality.
Aberration correction starts with knowing the exact properties of the ultrasound probe. Chapter 2 introduces a simple method to estimate the speed and thickness of the silicone lens on 1D transducers. This calibration is essential to accurately estimate the speed of sound in a medium, independent of imaging depth and transmission parameters. Using optimal lens parameters, and the estimated sound speed, we demonstrated an improvement in image resolution and contrast.

In chapter 3, attention shifts to the challenge of restoring transcranial image quality. An adaptive aberration correction approach is presented, using ray tracing through four tissue layers: transducer lens, skin, skull, and brain. This model estimates wave speeds in each layer, then reconstructs images based on the actual (refracted) wave paths. Applied to Doppler imaging in rats, the method improves both resolution and sensitivity, especially in cortical areas where skull induced aberrations are strongest.

Chapter 4 takes on the problem of high data rates in 3D imaging. Since functional activation in the brain is typically sparse, volumetric imaging often captures unnecessary data. Here, a new technique called selective-plane fUS is introduced. It combines focused wave transmission with a Row-Column Addressed (RCA) transducer to target only the brain regions of interest. This significantly reduces the computational and data transfer load and potentially paves the way for lightweight, portable brain-machine interfaces based on fUS.

In chapter 5, the thesis explores imaging of cellular activity and capillary flow using ultrasound contrast agents. We introduce a technique called Nonlinear Sound-sheet Microscopy (NSSM), that enables high resolution imaging of contrast agents within thin planes. This approach captures both vascular and gene expression data in living tissue and extends ultrasound imaging toward cellular resolution in opaque organs.

Together, these chapters lay the technical foundation for next-generation functional and biomolecular ultrasound: systems that are more accurate, less invasive, and better suited for high resolution brain imaging in real time. By addressing both the physical challenges of wave distortion and the computational load of volumetric data, this thesis brings fUS a step closer to clinical and translational neuroscience applications.