FMRI In Patients With Implanted Electrodes: Mitigating Imaging Artifacts

This thesis explores the integration of intracranial EEG (icEEG) with functional MRI (fMRI) in epilepsy patients with implanted electrodes, aiming to mitigate susceptibility artifacts in the resulting fMRI images and thus enhance diagnostic accuracy. Epilepsy is a complex disorder requiring precise identification of epileptogenic zones for successful treatment, particularly in drug-resistant cases. The combination of icEEG and fMRI holds great potential by providing detailed temporal and spatial information about brain activity. However, integrating fMRI with implanted intracerebral electrodes presents a significant challenge. The presence of metal electrodes in the strong magnetic field of the MRI scanner causes substantial susceptibility artifacts, which greatly distort the quality of fMRI images. To overcome these challenges, this research developed a mathematical model to understand and mitigate the susceptibility artifacts caused by icEEG electrodes. The model characterizes the magnetic field distortions induced by the electrodes and calculates the optimal echo times based on the distance from the electrodes, to minimize signal loss. Simulation results showed that optimizing the echo times led to a better contrast-to-noise ratio. A multi-echo approach was also evaluated as a practical implementation of these optimal echo times, which resulted in enhanced image quality, even in regions impacted by electrode artifacts. Although these results are encouraging, additional experimental validation is needed to confirm their efficacy in a clinical context. Nevertheless, the developed model was a required step before the imaging protocols can be considered for safety testing and eventual implementation in human subjects. If successful, these techniques could substantially improve the diagnostic capabilities of icEEG-fMRI, making it possible to detect brain activation patterns that might otherwise remain hidden and potentially improving surgical planning and treatment outcomes for epilepsy patients.

Name thesis:degree_name

Master of Science (MSc)

Discipline thesis:degree_discipline

Engineering – Biomedical

Grantor

Schulich School of Engineering

Year dc:date.issued

2025

Author dc:creator

• Weldemeskel, Iskindir Mekbib

Advisor dc:contributor.advisor

• LeVan, Pierre

Committee members dc:contributor.committeemember

• MacDonald, M. Ethan
• Pichardo, Samuel

• Epilepsy
• fMRI
• Intracranial EEG
• Susceptibility artifacts

Statement dc:rights

• Unless otherwise indicated, this material is protected by copyright and has been made available with authorization from the copyright owner. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.

Language dc:language.iso

en

DOI

https://dx.doi.org/10.11575/PRISM/48832

OAI identifier oai:identifier

oai:ucalgary.scholaris.ca:1880/121242