Identification of Normal Pressure Hydrocephalus by Disease-Specific Patterns of Brain Stiffness and Damping Ratio

Matthew C. Murphy, Petrice M. Cogswell, Joshua D. Trzasko, Armando Manduca, Matthew L. Senjem, Fredric Meyer, Richard L. Ehman, John Huston

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Objectives The aim of this study was to perform a whole-brain analysis of alterations in brain mechanical properties due to normal pressure hydrocephalus (NPH). Materials and Methods Magnetic resonance elastography (MRE) examinations were performed on 85 participants, including 44 cognitively unimpaired controls, 33 with NPH, and 8 who were amyloid-positive with Alzheimer clinical syndrome. A custom neural network inversion was used to estimate stiffness and damping ratio from patches of displacement data, accounting for edges by training the network to estimate the mechanical properties in the presence of missing data. This learned inversion was first compared with a standard analytical approach in simulation experiments and then applied to the in vivo MRE measurements. The effect of NPH on the mechanical properties was then assessed by voxel-wise modeling of the stiffness and damping ratio maps. Finally, a pattern analysis was performed on each individual's mechanical property maps by computing the correlation between each person's maps with the expected NPH effect. These features were used to fit a classifier and assess diagnostic accuracy. Results The voxel-wise analysis of the in vivo mechanical property maps revealed a unique pattern in participants with NPH, including a concentric pattern of stiffening near the dural surface and softening near the ventricles, as well as decreased damping ratio predominantly in superior regions of the white matter (family-wise error corrected P < 0.05 at cluster level). The pattern of viscoelastic changes in each participant predicted NPH status in this cohort, separating participants with NPH from the control and the amyloid-positive with Alzheimer clinical syndrome groups, with areas under the receiver operating characteristic curve of 0.999 and 1, respectively. Conclusions This study provides motivation for further development of the neural network inversion framework and demonstrates the potential of MRE as a novel tool to diagnose NPH and provide a window into its pathogenesis.

Original languageEnglish (US)
Pages (from-to)200-208
Number of pages9
JournalInvestigative radiology
Volume55
Issue number4
DOIs
StatePublished - Apr 1 2020

Keywords

  • brain stiffness
  • brain viscoelasticity
  • magnetic resonance elastography
  • neural network inversion
  • normal pressure hydrocephalus

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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