Leonardo A Rivera-Rivera1, Grant S Roberts1, Laura B Eisenmenger2, Oliver Wieben1,2, Sterling C Johnson3, and Kevin M Johnson1,2
1Department of Medical Physics, University of Wisconsin - Madison, Madison, WI, United States, 2Department of Radiology, University of Wisconsin - Madison, Madison, WI, United States, 3Department of Medicine, University of Wisconsin - Madison, Madison, WI, United States
Synopsis
The coupling of brain biomechanics
and hemodynamics is complex as it includes arterial pressure pulsations, venous
and CSF flow, and tissue compliance. Experimental evidence has demonstrated
alterations of each the multiple compartments in disease; however, the relationships
and coupling between brain biomechanics (e.g. strain and stiffness) and
vascular flow dynamics is not well characterized. This study investigates the
relationships between brain blood flow, stiffness, and strain using a
multi-scale brain imaging platform that includes 4D flow, MRE, and DENSE MRI. Results
suggest strong correlations between blood flow, strain, and stiffness and age-related
changes in these parameters.
Introduction:
The interplay between cranial arterial pressure pulsations, CSF and venous flow,
and tissue compliance is complex and is implicated in mechanisms driving
glympathic flow, removing interstitial fluid and soluble metabolites from the
brain.1,2 Pathologies such as dementia can manifest with altered biomechanics in
different cranial compartments (e.g. tissues, vessel walls) and at different
scales (e.g. small displacements in tissue, fast flow in arteries).3,4
Further, normal aging is associated with decreased brain stiffness but increased
vascular stiffness.5,6 Yet, the relationships between vascular flow-induced
brain strain and tissue stiffness are poorly understood, severely limiting its
potential use for the detection of early disease and disease monitoring. Noninvasive quantitative assessment of
vascular flow, cardiac induced tissue strain, and tissue stiffness in the brain
is feasible with MRI.7,8,5 However, studies to date have not
acquired these metrics in the same study population or attempted to evaluate
their associations. In this work, we explore the correlation between
macroscopic blood flow, cardiac induced brain tissue strain, brain stiffness and
age using a multi-scale brain imaging MRI protocol that includes radial 4D
flow, 2D single-shot DENSE MRI, and EPI MR Elastography (MRE).Methods:
Subjects: A total of 32 healthy volunteers participated in this study (mean
age =51±20yrs, range =[23, 82]yrs, 13 females). MRI: Volumetric,
time-resolved phase contrast (PC) MRI data with 4-point referenced encoding
were acquired in all subjects on a 3.0T system (Signa Premier, GE Healthcare)
using a 48-channel head coil (GE Healthcare), with a 3D radially-undersampled
sequence 9, with the following imaging parameters Venc=80cm/s,
imaging volume =22x22x10cm3, TR/TE=7.7/2.5ms, 0.7mm acquired isotropic
resolution, and scan time=5.6min. Flow encoded images were reconstructed to 20 cardiac
phases using retrospective ECG gating and view sharing.10 Prospectively
gated 2D single-shot spiral DENSE images were also acquired in all 32 subjects using
a ramped flip angle approach 8, Denc=0.175mm, 1 slice,
FOV=24x24cm2, dz=1cm, 1.9x1.9mm2 in-plane resolution, 10
cardiac time frames, TR/TE~100/2.1ms and scan time~40sec. Finally, multi-slice
EPI MRE data were collected in 13 of the 32 subjects (mean age=29±6yrs, range=[23,43]yrs,
3 females) by transmitting shear waves with 60 Hz vibration frequency to the
brain using a pillow-like passive driver with eight phase offsets sampled over one period of
60 Hz motion. Additional scan parameters included imaging volume = 24x24x14cm3,
TR/TE = 3200/70ms, 3.3x3.3x3mm3 resolution, and scan time~5min. Flow,
Strain and Stiffness analysis: Phase data were unwrapped using a Laplacian
approach prior to generation of velocity and displacement images.11 Blood
flow rates from the left and right petrous internal carotid arteries were
extracted from the velocity data in MATLAB (Mathworks, Natick, MA).12
Tissue displacement was measured from DENSE images from ROIs placed in brain
tissue proximal to the lateral ventricles. Strain maps were derived by
calculating the divergence of the displacement field and quantified using the
same ROIs.8 Stiffness maps from MRE data were generated using a 3D
direct inversion algorithm and stiffness was quantified using the same ROIs.13,14
Coefficient of determination were derived from linear regression modeling. Group
differences were assessed using Student’s t-test (P<0.05). Results:
Figure 1 shows example images from a healthy volunteer including
velocity fields derived from 4D flow, displacement fields from 2D DENSE, and
strain maps from the displacement field divergence. In addition, mean values for
a group of young healthy volunteers (<40yrs, n=12) are shown. Color-coded
strain and stiffness maps at the level of the lateral ventricles are shown for
two healthy volunteers (Figure 2). Higher strain and stiffness are appreciable
in the younger volunteer (left column) (25 vs 43yrs). Figure 3 shows linear
regression models assessing the correlations between strain, flow, and
stiffness. Results showed moderate-to-strong correlation between stiffness and
average blood flow (R2=0.52) and max tissue strain (R2=0.63).
Boxplots in Figure 4 show significantly higher average and max strain in
younger subjects when compared to older subjects (P=0.033, P<0.001). Furthermore,
average blood flow was also significantly higher in younger subjects (P=0.028).
Finally, Figure 5 shows linear regression analysis correlating strain, flow,
and age. Both strain and flow decreased with age; however, both were weakly correlated,
and the highest correlation was between max strain and age (R2=0.31).Discussion and Conclusions:
This study measured and analyzed cranial blood flow, displacement,
strain, and stiffness in a healthy cohort. Through the measurements of single-shot
spiral 2D DENSE and multi-slice MRE displacement fields, brain tissue strain
and stiffness were correlated (R2=0.63). Macroscopic blood flow was
also moderately correlated with tissue stiffness (R2=0.52). Overall,
age effect analysis showed a significant decrease (P<0.05) in strain and
blood flow in older adults when compared to a younger group. These findings
agreed well with studies that observed decreased overall brain stiffness and
blood flow in older adults.5,6 Further, decreased cerebral blood
flow and brain elasticity have been observed in animal models that used drug-induced
hypotension, suggesting a need for mechanical stimuli driven by the vascular
system to sustain tissue structural integrity.15 Age-dependent
modifications of mechanical properties at the cellular and functional level also
likely lead to changes in viscoelastic properties of the brain.16 Future studies will aim to elucidate the relationship
between vascular and tissue structure to intracranial biomechanic forces.
Longitudinal data comparing these parameters across age and pathology could
offer valuable insights into underlying disease pathogenesis.Acknowledgements
We gratefully acknowledge
research support from GE Healthcare, and funding support from NIH grants
R01NS066982, R01HL136965, P50-AG033514, and R01AG021155.References
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