Measuring the Characteristic Topography of Brain Stiffness with Magnetic Resonance Elastography

Matthew C Murphy, John Huston, Clifford R Jack, Kevin J Glaser, Matthew L Senjem, Jun Chen, Armando Manduca, Joel P Felmlee and Richard L Ehman

PLOS ONE, 2013, vol. 8, issue 12, 1-

Abstract: Purpose: To develop a reliable magnetic resonance elastography (MRE)-based method for measuring regional brain stiffness. Methods: First, simulation studies were used to demonstrate how stiffness measurements can be biased by changes in brain morphometry, such as those due to atrophy. Adaptive postprocessing methods were created that significantly reduce the spatial extent of edge artifacts and eliminate atrophy-related bias. Second, a pipeline for regional brain stiffness measurement was developed and evaluated for test-retest reliability in 10 healthy control subjects. Results: This technique indicates high test-retest repeatability with a typical coefficient of variation of less than 1% for global brain stiffness and less than 2% for the lobes of the brain and the cerebellum. Furthermore, this study reveals that the brain possesses a characteristic topography of mechanical properties, and also that lobar stiffness measurements tend to correlate with one another within an individual. Conclusion: The methods presented in this work are resistant to noise- and edge-related biases that are common in the field of brain MRE, demonstrate high test-retest reliability, and provide independent regional stiffness measurements. This pipeline will allow future investigations to measure changes to the brain’s mechanical properties and how they relate to the characteristic topographies that are typical of many neurologic diseases.

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0081668

DOI: 10.1371/journal.pone.0081668

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