A Post-Processing Tool and Feasibility Study for Three-Dimensional Imaging with Electrical Impedance Tomography During Deep Brain Stimulation Surgery

TL;DR

This paper explores the use of electrical impedance tomography (EIT) during deep brain stimulation surgery to improve target localization, utilizing a new post-processing tool and AI enhancement to produce rapid, high-quality images for intraoperative guidance.

Contribution

It introduces a novel EIT-based imaging approach with AI enhancement for real-time brain imaging during DBS surgery, addressing tissue shift challenges.

Findings

EIT can produce rapid, high-quality images during DBS surgery.

AI enhances the clarity and usefulness of EIT images.

The method is feasible for in-vivo application.

Abstract

Electrical impedance tomography (EIT) is a promising technique for biomedical imaging. The strength of EIT is its ability to reconstruct images of the body's internal structures through radiation-safe techniques. EIT is regarded as safe for patients' health, and it is currently being actively researched. This paper investigates the application of EIT during deep brain stimulation (DBS) surgery as a means to identify targets during operations. DBS involves a surgical procedure in which a lead or electrode array is implanted in a specific target area in the brain. Electrical stimulations are then used to modulate neural circuits within the target area to reduce disabling neurological symptoms. The main difficulty in performing DBS surgery is to accurately position the lead in the target area before commencing the treatment. Brain tissue shifts during DBS surgery can be as large as the target size when compared with the pre-operative magnetic resonance imaging (MRI) or computed tomography (CT) images. To address this problem, a solution based on open-domain EIT to reconstruct images surrounding the probe during DBS surgery is proposed. Data acquisition and image reconstruction were performed, and artificial intelligence was applied to enhance the resulting images. The results showed that the proposed method is rapid, produces valuable high-quality images, and constitutes a first step towards in-vivo study.