TY - JOUR
T1 - Identification of Normal Pressure Hydrocephalus by Disease-Specific Patterns of Brain Stiffness and Damping Ratio
AU - Murphy, Matthew C.
AU - Cogswell, Petrice M.
AU - Trzasko, Joshua D.
AU - Manduca, Armando
AU - Senjem, Matthew L.
AU - Meyer, Fredric B.
AU - Ehman, Richard L.
AU - Huston, John
N1 - Funding Information:
Received for publication July 24, 2019; and accepted for publication, after revision, September 21, 2019. From the Departments of *Radiology, †Physiology and Biomedical Engineering, and ‡Neurosurgery, Mayo Clinic, Rochester, MN. Conflicts of interest and source of funding: M.C.M., A.M., R.L.E., J.H., and Mayo Clinic have a financial conflict of interest related to this research. This research has been reviewed by the Mayo Clinic Conflict of Interest Review Board and is being conducted in compliance with Mayo Clinic Conflict of Interest policies. This work was supported by the Theodore W. Batterman Family Foundation as well as National Institutes of Health (grants EB001981 and EB027064). Supplemental digital contents are available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www.investigativeradiology.com). Correspondence to: Matthew Murphy, PhD, Department of Radiology, Mayo Clinic, 333 Fourth Ave SW, Rochester, MN 55902. E-mail: murphy.matthew@mayo.edu. Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved. ISSN: 0020-9996/20/5504–0200 DOI: 10.1097/RLI.0000000000000630
Publisher Copyright:
© Wolters Kluwer Health, Inc. All rights reserved.
PY - 2020/4/1
Y1 - 2020/4/1
N2 - 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.
AB - 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.
KW - brain stiffness
KW - brain viscoelasticity
KW - magnetic resonance elastography
KW - neural network inversion
KW - normal pressure hydrocephalus
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U2 - 10.1097/RLI.0000000000000630
DO - 10.1097/RLI.0000000000000630
M3 - Article
C2 - 32058331
AN - SCOPUS:85081944239
VL - 55
SP - 200
EP - 208
JO - Investigative Radiology
JF - Investigative Radiology
SN - 0020-9996
IS - 4
ER -