# Viscoelastic Property of the Brain Assessed With Magnetic Resonance Elastography and Its Association With Glymphatic System in Neurologically Normal Individuals

Bio Joo, So Yeon Won, Ralph Sinkus, Seung-Koo Lee

► To cite this version:

Bio Joo, So Yeon Won, Ralph Sinkus, Seung-Koo Lee. Viscoelastic Property of the Brain Assessed With Magnetic Resonance Elastography and Its Association With Glymphatic System in Neurologically Normal Individuals. Korean Journal of Radiology, 2023, 24 (6), pp.564. 10.3348/kjr.2022.0992. hal-04301742

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# Viscoelastic Property of the Brain Assessed With Magnetic Resonance Elastography and Its Association With Glymphatic System in Neurologically Normal Individuals

Bio Joo<fnref n="1" />, So Yeon Won<fnref n="2" />, Ralph Sinkus<fnref n="3" />,<fnref n="4" />, Seung-Koo Lee<fnref n="5" />

**Objective:** To investigate the feasibility of assessing the viscoelastic properties of the brain using magnetic resonance elastography (MRE) and a novel MRE transducer to determine the relationship between the viscoelastic properties and glymphatic function in neurologically normal individuals.

**Materials and Methods:** This prospective study included 47 neurologically normal individuals aged 23-74 years (male-to-female ratio, 21:26). The MRE was acquired using a gravitational transducer based on a rotational eccentric mass as the driving system. The magnitude of the complex shear modulus |G*| and the phase angle φ were measured in the centrum semiovale area. To evaluate glymphatic function, the Diffusion Tensor Image Analysis Along the Perivascular Space (DTI-ALPS) method was utilized and the ALPS index was calculated. Univariable and multivariable (variables with *P* < 0.2 from the univariable analysis) linear regression analyses were performed for |G*| and φ and included sex, age, normalized white matter hyperintensity (WMH) volume, brain parenchymal volume, and ALPS index as covariates.

**Results:** In the univariable analysis for |G*|, age (*P* = 0.005), brain parenchymal volume (*P* = 0.152), normalized WMH volume (*P* = 0.011), and ALPS index (*P* = 0.005) were identified as candidates with *P* < 0.2. In the multivariable analysis, only the ALPS index was independently associated with |G*|, showing a positive relationship (β = 0.300, *P* = 0.029). For φ, normalized WMH volume (*P* = 0.128) and ALPS index (*P* = 0.015) were identified as candidates for multivariable analysis, and only the ALPS index was independently associated with φ (β = 0.057, *P* = 0.039).

**Conclusion:** Brain MRE using a gravitational transducer is feasible in neurologically normal individuals over a wide age range. The significant correlation between the viscoelastic properties of the brain and glymphatic function suggests that a more organized or preserved microenvironment of the brain parenchyma is associated with a more unimpeded glymphatic fluid flow.

**Keywords:** Brain; Magnetic resonance elastography; Glymphatic system; Neurodegenerative disease; Viscoelastic property

## INTRODUCTION

According to the glymphatic system hypothesis,

cerebrospinal fluid (CSF) enters the brain interstitial space via the aquaporin-4 channel on astrocyte endfeet within the perivascular space, mixes with the interstitial fluid (ISF)

**Received:** December 16, 2022 **Revised:** March 11, 2023 **Accepted:** March 27, 2023

**Corresponding author:** Seung-Koo Lee, MD, PhD, Department of Radiology and Research Institute of Radiological Science and Center for Clinical Image Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea.

• E-mail: slee@yuhs.ac

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

<footnote n="1">¹Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea</footnote>

<footnote n="2">²Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea</footnote>

<footnote n="3">³School of Biomedical Imaging and Imaging Sciences, King's College London, London, UK</footnote>

<footnote n="4">⁴INSERM U1148, Laboratory for Vascular Translational Science, University Paris Diderot, Paris, France</footnote>

<footnote n="5">⁵Department of Radiology and Research Institute of Radiological Science and Center for Clinical Image Data Science, Yonsei University College of Medicine, Seoul, Korea</footnote>
and waste solutes, and then exits through the perivorous
space, thereby clearing interstitial metabolic waste products
[1-3]. Glymphatic system dysfunction is associated with
various neurodegenerative disorders [1,4]. Therefore,
various attempts have been made to evaluate the function
of the glymphatic system in vivo, such as direct visualization
of CSF movement using an intrathecal injection of a tracer or
indirect assessment using the Diffusion Tensor Image Analysis
Along the Perivascular Space (DTI-ALPS) method [5,6].

However, much remains to be elucidated regarding the
glymphatic system. Given that the central function of the
glymphatic system is the transport of fluids and solutes
through the brain parenchymal microenvironment, a
relevant research topic is a relationship between glymphatic
function and the structural integrity or complexity of the
brain parenchyma [7]. In this context, magnetic resonance
elastography (MRE) is a promising new approach because
of its ability to assess tissue viscoelastic properties in vivo,
thus providing biomechanical information about the tissue
microenvironment [8,9].

MRE is a phase-contrast magnetic resonance imaging (MRI) technique that can non-invasively measure in vivo tissue viscoelastic properties by measuring the three-dimensional (3D) shear wave displacement field produced during the propagation of acoustic waves generated by an external mechanical vibration source [10,11]. Although its application has been studied extensively in the liver, MRE has also been applied to the brain, suggesting that numerous neurological conditions associated with glymphatic dysfunction (e.g., Alzheimer's disease, Parkinson's disease, normal pressure hydrocephalus, multiple sclerosis, and brain aging) exhibit significant findings on MRE [11-18].

However, various aspects of MRE systems, such as driver
systems for vibration delivery, image acquisition sequences,
inversion algorithms, and terminology, have not yet been
standardized [8]. Particularly regarding driver systems, a
variety of approaches have been used for brain MRE [11].
Recently, a novel MRE vibration transducer based on a
rotational eccentric mass was introduced and successfully
tested in a pre-clinical phantom study and in vivo human
liver MRE, producing highly accurate vibrational waves
without second-harmonic vibrations and thus high-fidelity
data [19,20]. Nevertheless, the application of the MRE
system to the brain warrants further research.

We hypothesized that 1) the application of the MRE
system to the brain using the novel transducer is feasible,
and its normative data may be useful for future applications

of the MRE system in patients with neurological diseases,
and 2) a comprehensive evaluation of glymphatic function
and viscoelastic properties of the brain may reveal
significant correlations, ultimately offering valuable insights
into age-related neurodegeneration.

Therefore, this study aimed to investigate the feasibility
of assessing the viscoelastic properties of the brain using
MRE and a novel MRE transducer and to determine the
relationship between the viscoelastic properties of the brain
measured by MRE and glymphatic function assessed using
the DTI-ALPS method in neurologically normal individuals
with a wide age range.

MATERIALS AND METHODS

Study Participants

This prospective study was approved by Severance
Hospital Institutional Review Board (4-2019-0874) and was
conducted in accordance with the Declaration of Helsinki.
Informed consent was obtained from all the participants.

We screened 63 volunteers aged 20-79 years between
October 2019 and January 2022. The recruitment process
ensured that the number of participants in each age group
was similar. The eligibility criteria were as follows: 1) age
20-79 years, 2) normal cognitive status, and 3) no history
of neurological or psychiatric disorders. The exclusion
criteria were 1) Mini-Mental State Examination score ≤ 25;
2) history of neurological disease; 3) diseases or findings
that may increase bleeding risk (such as an intracranial
aneurysm); 4) significantly abnormal findings on brain
MRI (such as brain tumor); 5) scalp or skull lesions that
hamper transducer placement; 6) general contraindications
for MRI such as an implanted pacemaker); and 7) severe
image artifacts or incomplete image acquisition. Although
it has been proven that vibrations from the MRE transducer
are safe for brain evaluation, abnormalities with bleeding
tendencies were excluded from this study to eliminate the
potential risk of vibration-induced adverse effects, such as
aneurysm rupture [21]. Of the 63 participants, two were
excluded due to overt intracranial aneurysm, six due to
infundibulum indistinguishable from the aneurysm, one
due to incidental meningioma, one due to old intracerebral
hemorrhage, one due to capillary telangiectasia, and five
due to severe artifacts. Finally, 47 participants (median age,
49 years [interquartile range, 34-62 years]; range, 23-74
years; male:female ratio, 21:26) were enrolled (Table 1).
Figure 1 shows a flowchart of the recruitment process.
## Image Acquisition

All scans were conducted between 10:00 a.m. and 2:00 p.m., following sufficient sleep to eliminate the possibility of diurnal variation, using a 3-Tesla system (Ingenia, Philips Medical Systems) with a 32-channel receiver head coil. Each scan comprised both brain MRI and MRE and was obtained in a single session. Brain MRI included 3D T1-weighted imaging (T1WI), 3D fluid-attenuated inversion recovery imaging (FLAIR), 3D time-of-flight MR angiography (TOF MRA), DTI, and susceptibility-weighted imaging (SWI). MRE was performed only after an on-site neuroradiologist confirmed that the exclusion criteria were not met based on the brain MRI findings. Detailed imaging parameters of brain MRI are summarized in the Supplementary Methods.

MRE was acquired using a gradient-recalled echo sequence with a Hadamard encoding scheme using a gravitational

<table><caption>**Table 1.** Demographic Characteristics of Study Participants (n = 47)</caption><thead><tr><th>Parameters</th><th>Values</th></tr></thead><tbody><tr><td>Sex</td><td></td></tr><tr><td>Male</td><td>21 (44.7)</td></tr><tr><td>Female</td><td>26 (55.3)</td></tr><tr><td>Median age (range; IQR), yr</td><td>49 (23–74; 34–62)</td></tr><tr><td>Number of participants by age group</td><td></td></tr><tr><td>20–29 yr</td><td>7 (14.9)</td></tr><tr><td>30–39 yr</td><td>12 (25.5)</td></tr><tr><td>40–49 yr</td><td>5 (10.6)</td></tr><tr><td>50–59 yr</td><td>8 (17.0)</td></tr><tr><td>60–69 yr</td><td>11 (23.4)</td></tr><tr><td>70–79 yr</td><td>4 (8.5)</td></tr></tbody></table>

Data are the number of patients with percentage in parentheses unless specified otherwise. As the Shapiro-Wilk test rejected normality for age, values were reported as median values and interquartile ranges. IQR = interquartile range

<figure><img src="image_1.png" /><figcaption>**Fig. 1.** Flow chart of volunteer recruitment.</figcaption></figure>

transducer based on a rotational eccentric mass as the driver system [19,20]. The motor and controller units of the driver system are located in the MRI control room, and a flexible rotating shaft connects the motor unit to a gravitational transducer. The transducer was firmly fastened to the volunteer's head with a hair band and randomly assigned to either the right or left temporal region. A 1-cm thick gel pad ergonomically shaped according to the contour of the head was attached to the transducer to enhance comfort. The MRE scan covered the centrum semiovale region of the brain with the uppermost point on the upper boundary of the corpus callosum at the lowest slice level. Detailed imaging parameters of the brain MRE are summarized in the Supplementary Methods. Figure 2 shows the MRE driver system and the image acquisition.

## Postprocessing

The post-processing pipeline is described in detail in the Supplementary Methods, and its graphical representation is shown in Supplementary Figure 1. After processing of MRE data using a finite element method-based inversion algorithm [22], maps of the following viscoelastic parameters were obtained: storage modulus G', loss modulus G", the magnitude of the complex shear modulus |G*|, and phase angle φ, where $|G*| = \sqrt{G^{12} + G^{12}}$ and $φ = \arctan(\frac{G''}{G'})$. Of the four viscoelastic parameters, the magnitude of the complex shear modulus |G*| and phase angle φ were used for further analysis.

After automated segmentation of the brain parenchyma and white matter hyperintensity (WMH) using Statistical Parametric Mapping software (SPM12) and the LST toolbox, brain parenchymal volume and normalized WMH volume (ratio of the WMH volume to the total brain parenchymal volume) were calculated for subsequent analyses [23]. Next, the brain parenchymal mask was divided into right and left sides with respect to the brain midline to evaluate the influence of the transducer position on the measurement of viscoelastic parameters.

The ALPS index was estimated as described in a previous publication [6]. Three regions of interest (ROIs) were manually placed in the areas of projection, association, and subcortical neural fibers at the level of the lateral ventricle on color fractional anisotropy DTI maps by referring to SWI images. All the individuals were right-handed; hence, the ROIs were placed in the dominant left hemisphere. ROI placement was conducted by a neuroradiologist who was unaware of the MRE findings.
<figure><img src="image_2.png" /><figcaption>**Fig. 2.** Schematic diagram of the driver system and magnetic resonance elastography (MRE) acquisition. **A:** The transducer is connected to the motor and controller unit in the magnetic resonance imaging (MRI) control room through a rotating shaft. **B:** An example of the positioning of the transducer. The transducer was firmly fastened to either the right or left temporal region of the volunteer's head. **C:** Scan coverage of the MRE. The MRE scan covered the centrum semiovale region of the brain.</figcaption></figure>

## Statistical Analysis

Descriptive statistics for each viscoelastic parameter were reported. Univariable analyses with variables including age, sex, brain parenchymal volume, normalized WMH volume, and ALPS index were conducted to identify candidate factors to be included in the multivariable analysis of the association with the viscoelastic parameters (|G*| and φ) as the dependent variable. Multivariable linear regression analyses were conducted with variables (*P* < 0.2 in the univariable analyses) to assess independent relationships. The variance inflation factor (VIF) was calculated to determine the degree of multicollinearity. Finally, to investigate possible discrepancies in the measurement of viscoelastic parameters between the ipsilateral and contralateral sides with respect to the transducer position, the respective mean values of both sides were compared for each viscoelastic parameter using a paired *t*-test. Statistical significance was set at *P* < 0.05. Statistical analyses were performed using MedCalc Software (version 9.3.6.0; MedCalc).

## RESULTS

Brain MRE data were successfully acquired for all enrolled volunteers. Vibrations were well tolerated by all individuals, with no reports of illness or pain. The mean ± standard deviation of the magnitude of the complex shear modulus |G*| and phase angle φ for all participants were 1.604 ± 0.165 kPa and 0.301 ± 0.032 rad, respectively. Table 2 summarizes the measurement statistics for all the participants by age group.

### Univariable and Multivariable Analysis for the Magnitude of the Complex Shear Modulus |G*|

Regarding the univariable analysis for |G*|, age (β = -0.004, *P* = 0.005), brain parenchymal volume (β < 0.001, *P* = 0.152), normalized WMH volume (β = -13.80, *P* = 0.011), and ALPS index (β = 0.385, *P* = 0.005) were identified as candidates with *P* < 0.2. However, on multivariable analysis with those covariables, only the ALPS index was
<table><caption>**Table 2.** Summary Statistics of Measurements of All Participants and Participants by Age Group</caption><thead><tr><th>Participants</th><th>|G*|, kPa</th><th>φ, rad</th><th>Brain Parenchymal Volume, mL</th><th>Normalized WMH Volume</th><th>ALPS Index</th></tr></thead><tbody><tr><td>All participants</td><td>1.604 ± 0.165</td><td>0.301 ± 0.032</td><td>1.195.59 ± 132.99</td><td>4.571*10<sup>-4</sup> (1.007*10<sup>-4</sup>-1.690*10<sup>-3</sup>)</td><td>1.544 ± 0.174</td></tr><tr><td>20-29 yr</td><td>1.711 (1.508-1.751)</td><td>0.317 (0.293-0.330)</td><td>1200 (1157-1256)</td><td>0.000 (0.000-1.592*10<sup>-4</sup>)</td><td>1.649 (1.500-1.680)</td></tr><tr><td>30-39 yr</td><td>1.657 (1.523-1.767)</td><td>0.303 (0.291-0.322)</td><td>1329 (1175-1367)</td><td>8.500*10<sup>-5</sup> (2.535*10<sup>-5</sup>-4.734*10<sup>-4</sup>)</td><td>1.564 (1.498-1.651)</td></tr><tr><td>40-49 yr</td><td>1.617 (1.481-1.736)</td><td>0.305 (0.274-0.305)</td><td>1222 (1199-1311)</td><td>2.146*10<sup>-4</sup> (1.216*10<sup>-4</sup>-2.322*10<sup>-4</sup>)</td><td>1.400 (1.310-1.480)</td></tr><tr><td>50-59 yr</td><td>1.591 (1.511-1.700)</td><td>0.311 (0.308-0.327)</td><td>1112.8 (1076.8-1135.7)</td><td>6.191*10<sup>-4</sup> (2.716*10<sup>-4</sup>-1.999*10<sup>-3</sup>)</td><td>1.667 (1.543-1.754)</td></tr><tr><td>60-69 yr</td><td>1.543 (1.434-1.615)</td><td>0.308 (0.282-0.317)</td><td>1177.1 (1084.2-1239.4)</td><td>1.153*10<sup>-3</sup> (9.160*10<sup>-4</sup>-2.564*10<sup>-3</sup>)</td><td>1.557 (1.489-1.627)</td></tr><tr><td>70-79 yr</td><td>1.440 (1.379-1.521)</td><td>0.274 (0.254-0.287)</td><td>1015.1 (994.2-1072.9)</td><td>1.154*10<sup>-2</sup> (9.909*10<sup>-3</sup>-1.483*10<sup>-2</sup>)</td><td>1.281 (1.254-1.332)</td></tr></tbody></table>

Data are mean ± standard deviation or median (interquartile range). WMH = white matter hyperintensity, ALPS = analysis along the perivascular space

independently associated with |G*|, showing a positive relationship (β = 0.300, P = 0.029). All VIF values were less than 2 (Table 3, Fig. 3).

## Univariable and Multivariable Analysis for the Phase Angle φ

For φ, normalized WMH volume (β = -1.624, P = 0.128) and ALPS index (β = 0.064, P = 0.015) were identified as candidates for multivariable analysis. However, only the ALPS index was independently associated with the phase angle φ on the multivariable analysis (β = 0.057, P = 0.039) (Table 4, Fig. 3).

## The Influence of Transducer Position on the Measurement of Viscoelastic Parameters

Transducers were placed on the right and left sides of 24 and 23 participants, respectively. There was no significant difference between the ipsilateral and contralateral sides regarding transducer position for any viscoelastic parameter (|G*|: P = 0.954; φ: P = 0.698) (Supplementary Table 1). Representative cases are shown in Figure 4.

## DISCUSSION

In the current study, viscoelastic properties of the brain—the magnitude of the complex shear modulus |G*| and phase angle φ—were measured by the MRE system using a gravitational transducer as a driver system. Our study showed that glymphatic function, measured using the ALPS index, was independently associated with |G*| and φ when adjusted for other cofactors including age, WMH volume, and brain parenchymal volume. Moreover, the measurement of brain viscoelastic properties was independent of the transducer placement (ipsilateral or contralateral).

Currently, a driver system with a pneumatic actuator and head pillow is widely used in brain MRE because it is the only available commercial driver system [8]. However, potential errors in the reconstruction of biomechanical properties have been raised regarding the system, such as a decrease in the vibration amplitude or upper harmonic-related inaccuracies [19]. In this context, a novel MRE driver system based on a rotational eccentric mass, termed a gravitational transducer, was recently introduced and proven to produce highly accurate vibrational waves without second-harmonic vibrations and to be accurately phase-locked with an MRE sequence [19]. A recent study showed that the system was robust in terms of repeatability
<table><caption>**Table 3.** Univariable and Multivariable Linear Regression Analyses for Magnitude of the Complex Shear Modulus |G*| in kPa</caption><thead><tr><th rowspan="2">Variable</th><th colspan="2">Univariable</th><th colspan="3">Multivariable</th></tr><tr><th>β</th><th>P</th><th>β</th><th>P</th><th>VIF</th></tr></thead><tbody><tr><td>Sex</td><td>0.018</td><td>0.722</td><td></td><td></td><td></td></tr><tr><td>Age, yr</td><td>-0.004</td><td>0.005</td><td>-0.002</td><td>0.230</td><td>1.814</td></tr><tr><td>Brain parenchymal volume, mL</td><td>&lt; 0.001</td><td>0.152</td><td>&lt; 0.001</td><td>0.537</td><td>1.313</td></tr><tr><td>Normalized WMH</td><td>-13.80</td><td>0.011</td><td>-4.751</td><td>0.440</td><td>1.532</td></tr><tr><td>ALPS index</td><td>0.385</td><td>0.005</td><td>0.300</td><td>0.029</td><td>1.147</td></tr></tbody></table>

VIF = variance inflation factor, WMH = white matter hyperintensity, ALPS = analysis along the perivascular space

<figure><img src="image_3.png" /><figcaption>**Fig. 3.** Scatter diagrams and univariable analyses of the magnitude of the complex shear modulus |G*| (upper row) and phase angle φ (lower row) with age, sex, brain parenchymal volume, normalized white matter hyperintensity (WMH) volume, and analysis along the perivascular space (ALPS) index.</figcaption></figure>

<table><caption>**Table 4.** Univariable and Multivariable Linear Regression Analyses for the Phase Angle φ in rad</caption><thead><tr><th rowspan="2">Variable</th><th colspan="2">Univariable</th><th colspan="3">Multivariable</th></tr><tr><th>β</th><th>P</th><th>β</th><th>P</th><th>VIF</th></tr></thead><tbody><tr><td>Sex</td><td>0.006</td><td>0.535</td><td></td><td></td><td></td></tr><tr><td>Age, yr</td><td>-0.000</td><td>0.202</td><td></td><td></td><td></td></tr><tr><td>Brain parenchymal volume, mL</td><td>&lt; 0.001</td><td>0.718</td><td></td><td></td><td></td></tr><tr><td>Normalized WMH</td><td>-1.624</td><td>0.128</td><td>-0.898</td><td>0.404</td><td>1.115</td></tr><tr><td>ALPS index</td><td>0.064</td><td>0.015</td><td>0.057</td><td>0.039</td><td>1.115</td></tr></tbody></table>

VIF = variance inflation factor, WMH = white matter hyperintensity, ALPS = analysis along the perivascular space

and reliability [24]; however, only 15 volunteers with a narrow age range (21–33 years) were included. This study is the first to use the MRE driver system in individuals across a broad age range for brain MRE. We demonstrated that the transducer position had no significant effect on the assessment of the viscoelastic properties of the brain. These findings provide valuable information about normative age-related changes for future applications of the transducer in brain MRE in patients with neurological diseases.

Our study reported slightly lower values for viscoelastic parameters, in contrast to previous brain MRE studies. According to a systematic review, where the viscoelastic parameters were converted to shear stiffness μ [μ = 2

|G*|²/(G'+|G*|)] and loss tangent (tangent of the phase angle φ) to standardize results between different research groups, the mean shear stiffness and loss tangent of brain MRE at 50 Hz were 2.07 ± 0.42 kPa and 0.41 ± 0.06 rad, respectively [11]. In our study, the corresponding values were 1.708 ± 0.187 kPa and 0.310 ± 0.032 rad, respectively. This discrepancy may be attributed to differences in the brain regions imaged or MRE acquisition techniques. Further studies, including various MRE techniques, are warranted to set a reference range of viscoelastic parameters for the brain and, ultimately, to establish a standard brain MRE protocol.

The magnitude of the complex shear modulus |G*| is
<figure><img src="image_4.png" /></figure>

<figure><img src="image_5.png" /><figcaption>**Fig. 4.** Representative axial T1-weighted imaging (T1WI), fluid-attenuated inversion recovery imaging (FLAIR), and viscoelastic maps of a 34-year-old male (A), a 70-year-old male (B), and a 62-year-old female participant (C). The mean values of |G*|, φ, brain parenchymal volume, normalized white matter hyperintensity volume, and analysis along the perivascular space (ALPS) index were as follows: A: 1.783 kPa, 0.307 rad, 1378.51 mL, 2.3221 x 10⁻⁴, and 1.8883, respectively; B: 1.516 kPa, 0.327 rad, 1231.5 mL, 1.8269 x 10⁻³, and 1.2926, respectively; C: 1.718 kPa, 0.277 rad, 1007.81 mL, 1.638 x 10⁻³, and 1.8006, respectively. The participant in (A) showed a higher |G*| and ALPS index than the participant in (B). Note that although the participant in (C) was relatively old, she demonstrated a relatively high |G*| and ALPS index. The bright material on the participants' right side on T1WI is the gel pad attached to the transducer.</figcaption></figure>

regarded as a primarily tissue stiffness-related metric, whereas the phase angle φ is regarded as a primarily tissue viscosity-related metric [25]. We found in the univariable analysis that only |G*| was associated with age, whereas φ was not. This result is in concordance with previous reports, where only primarily tissue stiffness-related metrics, such as springpot-parameter μ or shear stiffness, showed a significant association with age, whereas primarily viscosity-related metrics, such as springpot-parameter α or damping ratio, did not [14,15,17]. The precise molecular and cellular conditions underlying changes in viscoelastic properties measured by MRE remain unclear. Based on previous studies, it is believed that primarily tissue stiffness-related metrics relate more to the mechanical backbone, which is largely dependent on tissue composition and/or myelination in the brain, whereas primarily viscosity-related metrics relate more to the complexity of the tissue architecture, which is attributed to the arrangement of axonal fibers and/or interneuronal connections [11,14,25-32]. In this context, our findings can be interpreted as preclinical tissue composition change (such as glia/neuron ratio) during normal aging but without severe degradation of the tissue geometry or architecture, which was also not apparent with structural MRI.

This is the first study to investigate the relationship between brain viscoelastic parameters and glymphatic function. The ALPS index is a measure of transependymal perivascular space water movement relative to that along

projection and association fibers and has been considered a promising biomarker of glymphatic function in various neurological conditions [5,6,33-36]. We found that a lower ALPS index was associated with lower values of both |G*| and φ, even after adjusting for age and age-related cofactors. Therefore, we can infer that glymphatic function is associated with the biomechanical properties of the brain parenchymal microenvironment, not only in terms of tissue composition but also tissue organization. Although direct evidence regarding this association at the molecular or histological levels is limited, one possible explanation is brain tissue deformability. Kedarasetti et al. [37] reported the deformability of brain tissue in response to arteriolar pulsations in the perivascular space. If the brain tissue deforms significantly due to a loss of tissue stiffness, kinetic energy may be removed from the CSF, resulting in decreased fluid flow and a lower ALPS index [7]. Another possible explanation is myelination in the parenchymal microenvironment of the brain. A recent study suggested a relationship between the integrity of myelination and the regulation of ISF drainage and substance transport in the extracellular space of the brain [38]. Given that |G*| decreases demyelination and global extracellular matrix destruction [29], this may explain the link between glymphatic function and changes in the brain's viscoelastic properties, which may not be solely due to aging. In addition, early stage brain microenvironmental alterations in cerebral small vessel disease that are not
discernible on other MRI sequences can be detected by MRE, thus explaining the association between |G*| and the ALPS index, even after adjusting for WMH volume. In this respect, this study provides useful insights into bridging the gap between numerous neurological conditions and the glymphatic hypothesis by directly demonstrating the relationship between glymphatic dysfunction and changes in brain viscoelastic properties. However, additional molecular and histological studies are required to fully understand the relationship between the viscoelastic properties of the brain and glymphatic function.

MRE is associated with numerous neurological conditions such as brain tumors, neurodegeneration, demyelination, trauma, brain aging, and even memory function [11,31]. In particular, the strong relationship between the viscoelastic properties of the hippocampus and relational memory performance is thought to be closely related to our findings, given that cognitive performance is significantly associated with the glymphatic function [1,31]. In this context, brain MRE may be a clinically useful imaging marker not only for neurodegeneration but also for functional assessment following neurological rehabilitation [9].

This study had several limitations. First, we obtained MRE images only for the centrum semiovale region with approximately 15-mm thick coverage. Although the applied vibration with a scan time of 2 min 20 s was tolerable in all volunteers, possible discomfort regarding the vibration was considered and minimized, resulting in a limited coverage size. Moreover, the spatial resolution of 2.75 x 2.75 x 3.14 mm³ of the MRE imaging may have been relatively low for the complete evaluation of differences in viscoelastic properties between the gray and white matter. Further investigation with whole-brain coverage, higher spatial resolution, and reduced scan time is required for clinical practice. The levels of MRE acquisition and ALPS index analysis were different. The MRE scan was obtained at the centrum semiovale, whereas the ALPS index was analyzed at the level of the lateral ventricle, which was slightly lower than the MRE acquisition level. However, the ALPS index has been suggested as an imaging marker that can reflect the glymphatic function of the entire brain and not only the periventricular region. Therefore, we believe that the difference in the image analysis level does not diminish the significance of our findings. Finally, the reproducibility of the MRE system was not tested. However, a recent study found that brain MRE using the same transducer showed robust repeatability and reliability [24]. However, future studies using various imaging systems and

manufacturers are required to validate their reliability and reproducibility.

In conclusion, brain MRE using a gravitational transducer as a source of vibration is feasible in neurologically normal individuals over a wide age range. The significant correlation between the viscoelastic properties of the brain and glymphatic function suggests that a more organized or preserved microenvironment of the brain parenchyma is associated with a more unimpeded glymphatic fluid flow.

## Supplement

The Supplement is available with this article at https://doi.org/10.3348/kjr.2022.0992.

## Availability of Data and Material

The datasets generated or analyzed during the study are available from the corresponding author on reasonable request.

## Conflicts of Interest

The authors have no potential conflicts of interest to disclose.

## Author Contributions

Conceptualization: Seung-Koo Lee. Data curation: Bio Joo, So Yeon Won. Formal analysis: Bio Joo. Investigation: Seung-Koo Lee. Methodology: Ralph Sinkus. Resources: Ralph Sinkus. Software: Ralph Sinkus. Supervision: Seung-Koo Lee. Validation: Bio Joo. Visualization: Bio Joo. Writing—original draft: Bio Joo. Writing—review & editing: Seung-Koo Lee.

## ORCID iDs

Bio Joo
https://orcid.org/0000-0001-7460-1421

So Yeon Won
https://orcid.org/0000-0003-0570-3365

Ralph Sinkus
https://orcid.org/0000-0002-6093-1654

Seung-Koo Lee
https://orcid.org/0000-0001-5646-4072

## Funding Statement

None
## Acknowledgments

The authors thank Medical Illustration & Design, part of the Medical Research Support Services of Yonsei University College of Medicine, for all artistic support related to this work.

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