Integrating Ultrasound Neuromodulation and Imaging

Abstract

Vagus nerve stimulation (VNS) has been proven to be an effective treatment for patients suffering from drug­-resistant epilepsy. Current vagus nerve stimulators are either implantable devices or bulky, handheld devices. The implant consists of a pulse generator beneath the skin of the chest, connected to electrodes that are wired to the cervical vagus nerve. While capable of delivering localized electrical impulses, the implantation is highly invasive. Handheld devices do not ask for a risky surgery, but their imprecise targeting of the neck reduces efficiency and provokes additional side effects.

Ultrasound has been widely used in clinical applications ranging from focused ultrasound (FUS) tissue ablation to medical imaging. Much research is being carried out on the use of FUS neuromodulation as a low-­cost, non-invasive alternative to electrical VNS. The combination of using ultrasound for neuromodulation as well as imaging allows for image-­guided FUS where automated tracking of the nerve location improves the targeting of the vagus nerve.

In this thesis, the design of an ultrasound vagus nerve stimulator with combined imaging capabilities is presented. The novel architecture combines FUS for vagus nerve neuromodulation and plane wave imaging (PWI) with optimized sparse receive sub­arrays to obtain the location of the nerve within the neck.

A 2D array of piezoelectric transducers with λ/2-pitch poses a strict constraint on the pixel area. The goal of the system design is to minimize the area consumption of the on­-pixel electronics by making use of already present circuit blocks. A shared delay­-locked loop generates the required continuous phases for FUS neuromodation, while a row-­column pulse control block generates a single pulse from the available phases for use in PWI. This way the on-­pixel transmit hardware is reduced to a multiplexer and high­-voltage driver.

The receiver consists of an analog front­-end and analog-­to­-digital converter and is shared among a sub-­array of receive elements. Different degrees of random sparsity are explored for the optimal implementation of the receive sub-­arrays within the full array. Synthetic aperture imaging allows the multiplexing of multiple receive elements to the shared front-­end and reduces the time spent on imaging using dynamic beamforming on a single data set.

The full system­-level architecture of a complementary metal­-oxide­-semiconductor (CMOS) interface is proposed and the receiver front-end has been designed and simulated.