A Novel Quantitative MRI Tool for Diagnosing Alzheimer’s Disease

Who am I?

An academic lecturer and a 2nd year PhD candidate under the supervision of Dr. Noam Ben-Eliezer in the department of biomedical engineering at Tel-Aviv University.

My research is focused on the development of computational methods for studying neurodegenerative diseases with a specific focus on Alzheimer’s disease (AD). Specifically, I aim to develop advanced MRI-based tools to support clinicians in the detection and decision-making processes, and to allow reliable assessment of treatment-response. The developed tools will be based on advanced signal models and quantification of MRI relaxation times – a key contrast mechanism, relating directly to tissue viability and microstructural composition.

About the project:

Alzheimer’s disease (AD) is a leading cause of death and is the main cause of dementia worldwide. Amyloid plaques are the hallmark of AD, with Positron Emission Tomography (PET) being the gold-standard tool for assessing amyloid plaque load in AD patients. Notwithstanding its high sensitivity to plaque load, PET is inherently limited in spatial resolution (bounded to ~4 mm) and involves harming radiation.

Quantitative MRI (qMRI) is a new, highly sensitive approach, allowing to quantify clinical microscopic neurodegenerative processes including amyloid deposits in an accurate and reproducible manner. In our project we intend to harness qMRI to establish a non-ionizing MRI tool that would replace Amyloid PET scans for diagnosing AD.

To study the relationship between MRI signal and amyloid deposits we will extract quantitative parametric maps of imaging parameters that are typically used to generate qualitative contrast in MR images and integrate new capabilities for analyzing MRI signal at a sub-voxel level to study tissue microstructure. Based on the gained knowledge we will design an open access, online, cross-vendor interface for human studies involving AD patients.