Advancements in MRI-based quantitative measurement of slow physiological flows: Applications in neurological and vascular disease

This dissertation advances the field of Magnetic Resonance Imaging (MRI) by developing and validating innovative techniques for the quantitative measurement of slow fluid kinetics, including flows, which are critical for diagnosing neurological and vascular disorders. Flow is examined in three domains, including: dynamic contrast enhanced MRI for measuring vascular parameters in peripheral muscles, contrast agent dynamics in measuring glymphatic flow in the brain, and the development of a novel acquisition to measure very slow fluid flows in shunts in the brain. For slow flow in shunts, no other non-invasive method exists to enable clinical care teams to evaluate the flow in a suspected shunt failure in a pediatric patient. This results in many invasive surgeries to confirm and replace shunts. Using Dynamic Contrast-Enhanced MRI (DCE-MRI), the dissertation explores the slow fluid dynamics of the glymphatic system and also assesses blood flow in ischemic conditions under a peripheral arterial disease (PAD) model with advanced parametric mapping. Central to this dissertation is the development and application of a slow flow measurement technique, the Shunt Flow Enhancement of Signal Intensity (shunt-FENSI) technique, meticulously designed to improve cerebrospinal fluid (CSF) flow diagnostics within ventriculoperitoneal (VP) shunt systems. This work not only refines the clinical project structure for shunt-FENSI but also integrates novel sequence programming and signal post-processing techniques. By designing signal processing methods such as the "Phase-Sweep" technique to reduce the influence of field inhomogeneity and deploying noise analysis to confirm flow detection limits, this research offers quantitative insights into measurement of slow flow, non-invasively, for pediatric shunt patients. Establishing simulated prediction models of the flow inside VP shunt based on MR physics is essential in developing accurate, nonlinear conversions of MR signals into flow rates. The findings from extensive preclinical and clinical acquisitions from these projects are discussed, providing a comparative analysis of the developed methodologies and their application across different clinical scenarios, thereby making substantial contributions to medical imaging and diagnostics.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Bioengineering

Grantor

University of Illinois Urbana-Champaign

Year dc:date

2025

Author dc:creator

• Zhang, Mingxiao

Contributors dc:contributor

• Sutton, Bradley
• Insana, Michael F
• Lam, Fan
• Pappu, Suguna

• MRI
• Slow Flow Measurement
• CSF
• Glymphatic System
• Quantitative MRI

Statement dc:rights

• Copyright 2025 Mingxiao Zhang

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/129662

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F129662