Stiffness and Beyond: What MR Elastography Can Tell Us About Brain Structure and Function Under Physiologic and Pathologic Conditions

• Published in: Topics in magnetic resonance imaging Vol. 27; no. 5; pp. 305 - 318
• Main Authors: Yin, Ziying, Romano, Anthony J., Manduca, Armando, Ehman, Richard L., Huston, John
• Format: Journal Article
• Language: English
• Published: United States Copyright Wolters Kluwer Health, Inc. All rights reserved 01.10.2018
• Subjects: Algorithms; Brain - diagnostic imaging; Brain - pathology; Brain - physiology; Brain Diseases - diagnostic imaging; Brain Diseases - pathology; Brain Diseases - physiopathology; Elasticity Imaging Techniques - methods; Humans; Magnetic Resonance Imaging - methods; Viscosity
• ISSN: 0899-3459; 1536-1004; 1536-1004
• DOI: 10.1097/RMR.0000000000000178

ABSTRACTBrain magnetic resonance elastography (MRE) was developed on the basis of a desire to “palpate by imaging” and is becoming a powerful tool in the investigation of neurophysiological and neuropathological states. Measurements are acquired with a specialized MR phase-contrast pulse sequence that can detect tissue motion in response to an applied external or internal excitation. The tissue viscoelasticity is then reconstructed from the measured displacement. Quantitative characterization of brain viscoelastic behaviors provides us an insight into the brain structure and function by assessing the mechanical rigidity, viscosity, friction, and connectivity of brain tissues. Changes in these features are associated with inflammation, demyelination, and neurodegeneration that contribute to brain disease onset and progression. Here, we review the basic principles and limitations of brain MRE and summarize its current neuroanatomical studies and clinical applications to the most common neurosurgical and neurodegenerative disorders, including intracranial tumors, dementia, multiple sclerosis, amyotrophic lateral sclerosis, and traumatic brain injury. Going forward, further improvement in acquisition techniques, stable inverse reconstruction algorithms, and advanced numerical, physical, and preclinical validation models is needed to increase the utility of brain MRE in both research and clinical applications.