Cerebral magnetic resonance elastography in supranuclear palsy and idiopathic Parkinson's disease

Abstract

Detection and discrimination of neurodegenerative Parkinson syndromes are challenging clinical tasks and the use of standard T1- and T2-weighted cerebral magnetic resonance (MR) imaging is limited to exclude symptomatic Parkinsonism. We used a quantitative structural MR-based technique, MR-elastography (MRE), to assess viscoelastic properties of the brain, providing insights into altered tissue architecture in neurodegenerative diseases on a macroscopic level. We measured single-slice multifrequency MRE (MMRE) and three-dimensional MRE (3DMRE) in two neurodegenerative disorders with overlapping clinical presentation but different neuropathology - progressive supranuclear palsy (PSP: N = 16) and idiopathic Parkinson's disease (PD: N = 18) as well as in controls (N = 18). In PSP, both MMRE (Δμ = - 28.8%, Δα = - 4.9%) and 3DMRE (Δ|G*|: - 10.6%, Δφ: - 34.6%) were significantly reduced compared to controls, with a pronounced reduction within the lentiform nucleus (Δμ = - 34.6%, Δα = - 8.1%; Δ|G*|: - 7.8%, Δφ: - 44.8%). MRE in PD showed a comparable pattern, but overall reduction in brain elasticity was less severe reaching significance only in the lentiform nucleus (Δμ n.s., Δα = - 7.4%; Δ|G*|: - 6.9%, Δφ: n.s.). Beyond that, patients showed a close negative correlation between MRE constants and clinical severity. Our data indicate that brain viscoelasticity in PSP and PD is differently affected by the underlying neurodegeneration; whereas in PSP all MRE constants are reduced and changes in brain softness (reduced μ and |G*|) predominate those of viscosity (α and φ) in PD.

Full text

Cerebral magnetic resonance elastography in supranuclear palsy and
idiopathic Parkinson's disease
☆
Axel Lipp
a,1
, Radmila Trbojevic
b,1
, Friedemann Paul
b
, Andreas Fehlner
c
, Sebastian Hirsch
c
, Michael Scheel
c
,
Cornelia Noack
a
,JürgenBraun
d
, Ingolf Sack
c,
⁎
a
Department of Neurology, Charité — University Medicine Berlin, Augustenburger Platz 1, 13353 Berlin, Germany
b
NeuroCure Clinical Research Center, Charité — University Medicine Berlin, Max Delbrueck Centre for Molecular Medicine Berlin, Charitéplatz 1, 10117 Berlin, Germany
c
Department of Radiology, Charité — University Medicine Berlin, Charitéplatz 1, 10117 Berlin, Germany
d
Institute of Medical Informatics, Charité — University Medicine Berlin, Charitéplatz 1, 10117 Berlin, Germany
abstractarticle info
Article history:
Received 17 May 2013
Received in revised form 18 July 2013
Accepted 12 September 2013
Available online 20 September 2013
Keywords:
MR-elastography
MRE
Elasticity
Viscosity
Parkinson disease
Progressive supranuclear palsy
Detection and discrimination of neurodegenerative Parkinson syndromes are challenging clinical tasks and the
use of standard T
1
-andT
2
-weighted cerebral magnetic resonance (MR) imaging is limited to exclude symptomatic
Parkinsonism. We used a quantitative structural MR-based technique, MR-elastography (MRE), to assess viscoelastic
properties of th e brain, providing insights into alte red tissuearchitectureinneurodegenerative diseases on a mac-
roscopic level. We measured single-slice multifrequency MRE (MMRE) and three-dimensional MRE (3DMRE) in
two neurodegenerative disorders with overlapping clinical presentation but different neuropathology — progressive
supranuclear palsy (PSP: N = 16) and idiopathic Parkinson's disease (PD: N = 18) as well as in controls (N = 18).
In PSP, both MMRE (Δμ = −28.8%, Δα = −4.9%) and 3DMRE (Δ|G*|: −10.6%, Δφ: −34.6%) were si gni ficantly
reduced compared to controls, with a pronounced reduction within the lentiform nucleus (Δμ = − 34.6%,
Δα = − 8.1%; Δ|G*|: − 7.8%, Δφ: −44.8%). MRE in PD showed a comparable pattern, but overall reduction in
brain elasticity was less se vere reaching significance only in the lentiform nucleus (Δμ n.s., Δα = − 7.4%;
Δ|G*|: − 6.9%, Δφ: n.s.). Beyond that, patients showed a close negative correlation between MRE constants
and clinical severity. Our data indicate that brain viscoelasticity in PSP and PD is differently affected by the under-
lying neurodegeneration; whereas in PSP all MRE constants are reduced and changes in brain softness (reduced μ
and |G*|) predominate those of viscosity (α and φ)inPD.
© 2013 The Authors. Published by Elsevier Inc. All rights reserved.
1. Introduction
Neurodegenerative disorders are defined by a progressive loss of
neuronal function and structure, synaptic alteration and inflammation
(reactive astrocytosis and activated microglia) (Hirsch et al., 2012).
This loss of neurons and oligodendrocytes results in gross atrophy of
affected brain regions, which can be reliably assessed by volumetric
and morphometric measurements based on magnetic resonance imag-
ing (MRI) (Schrag et al., 2000). In preclinical and early stages of neuro-
degenerative disorders, however, patterns of brain atrophy are subtle
and occult to conventional MRI (Mahlknecht et al., 2010).
This is not surprising given that atrophy due to neuronal cell loss is
the ultimate event in neurodegeneration. Earlier and more subtle alter-
ations in cytoarchitecture and cellular matrix are generally missed by
conventional MRI. In contrast, evaluation of mechanical properties of
the brain such as elasticity and viscosity can provide information on the
constitution of brain tissue at multiple scales (neuronal/non-neuro nal
fibre density, brain oedema and demyelination) (Posnansky et al., 2012;
Riek et al., 2012; Schregel et al., 2012). Given the high sensitivity of
manual palpation, the elastic response of soft tissue to controlled
deformation may provide information on altered tissue architecture in
disease on the macroscopic level (Sarvazyan et al., 1995).
Palpation of the brain, so far limited to neurosurgeons and patholo-
gists to detect central nervous system disorders, has recently emerged
into an imaging modality called MR elastography (MRE) (Muthupillai
et al., 1995) suitable for neuroradiological examinations (Clayton
et al., 2012; Green et al., 2008; Kruse et al., 2008; Pattison et al., 2010;
Sack et al., 2008). In healthy volunteers, we have shown that cerebral
MRE is sensitive to ageing, providing a higher sensitivity than tests
using morphology-based markers (Sack et al., 2009, 2011). Further-
more, we studied the effect of multiple sclerosis (Streitberger et al.,
2012; Wuerfel et al., 2010) and hydrocephalus (Freimann et al., 2012;
Streitberger et al., 2011) on the viscoelastic properties of the brain and
identified a disease-related loss of elasticity. Murphy et al. (2011)
found a significant decrease in elasticity in seven Alzheimer patients
NeuroImage: Clinical 3 (2013) 381–387
☆
This is an open-access article distributed under the terms of the Creative Commons
Attribution License, which permits unrestricted use, distribution, and reproduction in
any medium, provided the original author and source are credited.
⁎ Corresponding author. Tel.: +49 30 450 539058.
E-mail address: ingolf.sack@charite.de (I. Sack).
1
These authors contributed equally to this work.
2213-1582/$ – see front matter © 2013 The Authors. Published by Elsevier Inc. All rights reserved.
http://dx.doi.org/10.1016/j.nicl.2013.09.006
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compared to an age- and gender-matched control group without cogni-
tive decline.
From these pilot studies we have learnt that different physiological
events and various neurological disorders are accompanied by wide-
spread softening of cerebral parenchyma, suggesting that the brain's
viscoelastic properties may reflect principal patterns of neuronal integ-
rity. To further unravel the underlying mechanisms of ‘brain softening’
in disease, recent MRE studies in the mouse investigated demyelination
(Schregel et al., 2012)andinflammation (Riek et al., 2012) and identi-
fied a loss of cerebral elasticity in response to these events.
Motivated by these results, researchers are currently developing
cerebral MRE into an image-based marker of neurodegeneration.
However, the limited number of clinical trials still impedes conclusions
on how neurodegeneration affects the brain's viscoelasticity. In particu-
lar, no comparison exists between the MRE data obtained in neuro-
degenerative disorders of different aetiology, clinical dynamic and
cerebral distribution of the underlying neurodegeneration. Therefore,
it is not possible to unambiguously correlate ‘brain softening’ with the
occurrence of neuronal degradation.
For this study, we therefore chose two neurodegenerative disorders
that substantially overlap in clinical presentation but differ considerably
with regard to their neuropathology — progressive supranuclear palsy
(PSP) and idiopathic Parkinson's disease (PD).
PD is a rather slowly progressive neurodegenerative disease with
alpha-synuclein deposits in neuronal Lewy bodies and Lewy neurites
as its pathological hallmark. Propagation of Lewy-related pathology
(LRP) in the brainstem occurs in a caudal to rostral direction with even-
tual involvement of diencephalon, basal forebrain, medial temporal lobe
structures and finally the cortex. Neuronal populations most vulnerable
to neuronal loss in PD include the substantia nigra, locus coeruleus,
raphe nuclei, pedunculopontine nucleus, basal nucleus of Meynert and
dorsal motor nucleus of the vagus (Dickson et al., 2009).
In PSP, microtubule-associated protein tau is the major constituent
of neurofibrillary tangles (NFTs) that accumulate in affected neurons
and glial cells. Although the anatomical distribution of tau pathology de-
termines the clinical syndrome [Williams, 2009 521/id], most PSP cases
show marked atrophy of the midbrain, superior cerebellar peduncle
and cerebellar dentate nucleus. Nuclei most severely affected by NFTs
are the globus pallidus, subthalamic nucleus and substantia nigra. Tau
pathology usually spares the cerebral cortex except for the precentral
gyrus (Dickson et al., 2010).
The more rapid and widespread neurodegeneration in PSP might
cause a stronger reduction in brain elasticity compared with the rather
limited neuronal loss within the substantia nigra in patients with early
to moderate PD.
To prove this hypothesis we measured and analysed externally in-
duced shear vibrations in the brain using 2D- and 3D-MRE. We used
fast 2DMRE to capture the shear modulus at multiple drive frequencies,
coining the term multifrequency MRE or MMRE, and 3D-MRE to mea-
sure the full vector field of the vibration at single frequency (3DMRE).
Each method represents a trade-off between acquisition time and com-
pleteness of elastodynamic information. 3DMRE offers an opportunity
to perform a detailed mapping of viscoelastic parameters while MMRE
enables us, for regions of interest (ROI's), to extend the analysis in
terms of modelling. Under the assumption of scale-free viscoelastic net-
work topology in the brain, MMRE offers greater interpretative power
(Sack et al., 2013) while under different assumptions (e.g. dominating
elastic properties) MMRE provides equivalent measures to 3DMRE at
single vibration frequency. We therefore aimed to use both methods
for a detailed analysis of the effect of neurodegenerative diseases in
MRE.
Several clinical studies of brain MRE are based on MMRE in combina-
tion with the so-called springpot model (Freimann et al., 2012;
Streitberger et al., 2011, 2012; Wuerfel et al., 2010). The springpot pro-
vides two constants, μ and α. μ
corresponds to our haptic sensation of a
material's constitution (related to the terms ‘soft’ and ‘firm’), while α is
the viscoelastic power law exponent and relates to the density and
topology of the mechanical lattice (Posnansky et al., 2012). Other stud-
ies report 3DMRE of the brain measured at single frequency (Green
et al., 2008; Murphy et al., 2011). Consistent with recent studies in the
mouse, we will state for this type of data the magnitude (|G*|) and the
phase angle (φ) of the complex shear modulus (Schregel et al., 2012).
Due to its capability to efficiently suppress pressure waves, 3DMRE
can provide higher spatial resolution than MMRE, however, viscoelastic
modelling (and drawing conclusions about the underlying mechanical
network) requires multiple vibration frequencies as used in MMRE.
We therefore apply both experiments with a view to using MRE for
the staging of neurodegeneration.
2. Methods
2.1. Patients
The study was approved by the Institutional Review Board and all
subjects gave written informed consent before participation.
The study cohort included 52 subjects, among them 18 patients
(6 female; mean age = 63 years) diagnosed with mild to moderate
Parkinson's disease according to the UK Brain Bank consensus criteria
(Hughes et al., 1992), 16 patients (8 female; mean age = 70 years)
diagnosed with probable PSP according to current consensus criteria
(Litvan et al., 1996, 2003) and 18 predominantly sedentary control
subjects of similar age (8 female; mean age = 64 years) (Table 1). As
clinical heterogeneity of PSP weakens diagnostic certainty, recruitment
of PSP patients was limited to the clinical phenotype of Richardson's
syndrome (PSP-RS) and PSP-Parkinsonism (PSP-P) (Williams and
Lees, 2009). Subjects were recruited from the Outpatient Movement
Disorder Unit of the Charité, Berlin, and the NeuroCure Clinical Research
Center. Subjects with implanted deep brain stimulators (STN-DBS) or
carrying other ferromagnetic implants were not included. The presence
of structural brain abnormalities in T1- and T2-weighted MRI unrelated
to PSP/PD such as birth defects, head trauma and cerebrovascular disor-
ders excluded subjects from further participation. Clinical severity of
underlying neurodegeneration was rated using appropriate test instru-
ments. In PD, the motor part of the Unified Parkinson's Disease Rating
Scale (UPDRS part III) was obtained during a phase of best medical
treatment (ON state). In PSP, disease severity was assessed by the
Golbe scale (PSPRS) (Golbe and Ohman-Strickland, 2007).
2.2. MRE measurements
Mechanical vibrations were transmitted into the head by a custom-
made head cradle connected via a carbon-fibre piston to a remote vibra-
tion generator as described in (Sack et al., 2008). Measurements were
performed on a standard 1.5 T clinical MRI scanner (Sonata, Siemens,
Erlangen, Germany) equipped with a single-element head-coil. For
both MMRE and 3DMRE, a single-shot spin echo echo-planar imaging
sequence was employed, which was sensitized to motion by a sinusoi-
dal motion-encoding gradient (MEG) during the first half of the echo
period.
Table 1
Patient characteristics.
Parameter Controls PD PSP P
N181816
Gender [f: m] 8: 11 6: 12 8: 8
Age [years] 64 ± 10.8 63 ± 10.8 70 ± 5.8 0.07
a
Disease duration [months] n.a. 111 ± 81.0 69 ± 32.4 0.14
b
Clinical severity
c
[points] n.a. 16.7 ± 9.8 41.9 ± 12.5
Values are means ± SD.
a
Kruskal–Wallis test.
b
Mann–Whitney test.
c
Clinical severity in PD and PSP cases assessed by motor part of UPDRS and Golbe scale.
382 A. Lipp et al. / NeuroImage: Clinical 3 (2013) 381–387

2.2.1. Single-slice multifrequency MRE (MMRE)
The vibration waveform was synthesised by superposition of four
harmonic oscillations of f = 25, 37.5, 50 and 62.5 Hz frequency with
identical phases and a total duration of 400 ms (Klatt et al., 2007). A sin-
gle burst of this signal was fed into the wave generator prior to the start
of each image acquisition. The motion was encoded by an MEG in
through-plane direction composed of four sinusoids of 60-Hz frequency
and 35 mT/m amplitude. The polarity of the MEG was toggled in each
second experiment for subtracting the inverse phase contrast and leav-
ing the difference wave phase in the image. The experiment was repeat-
ed in order to capture the dynamics of wave propagation. Therefore, the
delay between the onset of vibration and the start of motion encoding
was varied 32 times from 320.0 ms to 397.5 ms by an increment of
2.5 ms. The resulting phase shift corresponds to a first harmonic fre-
quency of 12.5 Hz, which determines the resolution in our vibration
spectrum. One 6-mm transverse image slice through the central part
of the ventricles parallel to the internal base of the skull was selected.
Further image acquisition parameters were: repetition time TR, 3 s;
echo time TE, 149 ms; field of view, FoV, 192 × 192 mm
2
;matrixsize,
128 × 128; no accumulation.
2.2.2. Three-dimensional MRE (3DMRE)
3DMRE refers to full wave field acquisition within a volumetric slab
of 6 cm thickness through the central brain. Continuous harmonic
vibrations of 50 Hz frequency were used for head stimulation in this
experiment. The strain wave field was consecutively encoded by an
MEG in through-plane direction, phase-encoding direction and read-
out direction, each composed of three cosine-cycles of 60-Hz frequency
(zeroth- and first-moment-nulled MEG (Murphy et al., 2011)). The
cosine-shaped gradient waveform was approximated by trapezoidal
gradients of 30 mT/m amplitude. Four instances of one vibration cycle
were captured by a trigger-shift increment of 5 ms. Thirty transverse
slices of 2-mm thickness without gap were acquired in the central crani-
um parallel to the g enu splenium axis of the corpus callosum. Further im-
aging parameters were: TR, 272 ms; TE, 116 ms; FoV, 256 × 224 mm
2
;
matrix size, 128 × 122; two accumulations for increasing the signal-
to-noise ratio.
2.3. Data processing
Phase images were unwrapped and Fourier-transformed in time,
yielding complex displacement fields at drive frequency. The wave
field maps were filtered either by applying the curl operator followed
by a 3D Gaussian noise filter to a 5-pixel neighbourhood (for 3D data)
or by a 2D Butterworth band-pass with frequency-dependent filter
threshold given in Klatt et al. (2007) (for multifrequency 2D data).
While the preprocessing of 2D data corresponds to our previously
published method, 3D processing benefits from the capability of the
curl operator to suppress compression waves which is not applicable
to 2D data. Modulus recovery was based on a pixel-wise inversion of
the Helmholtz equation as analysed in Papazoglou et al. (2008) as-
suming a uniform density of brain tissue of 1000 kg/m
3
.
2.3.1. MMRE
For 2D data of MMRE, the real part and the imaginary part of G* were
averaged over the parenchyma visible in the image slice (excluding the
ventricles), yielding four global frequency-dependent complex modulus
values G*(f) with f being the drive frequency. These shear moduli were
fitted by the springpot model,
G

¼ κ i·2π·fðÞ
α
; ð1Þ
where κ = μ
1−α
η
α
,andκ and α were the frequency-independent free
variables in our least-squares fit procedure. The parameter μ is the global
shear elasticity; η is the viscous damping and α is a measure of the elas-
tic lossy relation (Sack et al., 2009). For example, α = 0 corresponds to
lossless elastic behaviour with shear elasticity, μ and α = 1 to lossy vis-
cous damping with viscosity, η. For relating κ to a shear elasticity μ,we
assumed η = 3.7 Pa·s. This value of η was previously determined as
an approximated value of viscosity in human brain tissue (Klattetal.,
2007).
2.3.2. 3DMRE
For 3D data, each field component was separately inverted, yielding
three complex shear modulus maps, which were combined to generate
one complex shear modulus map G* represented as
G

jj
¼ abs G

ðÞ
φ ¼ arctan imag G

ðÞ=real G

ðÞðÞ:
ð2Þ
This representation of G* was chosen for comparing the phase angle
φ to the springpot-related constant α which will be discussed later. Ad-
ditionally, negative G″-values due to reversely running waves could be
eliminated in this way. For completeness, the global values of real(G*),
imag(G*), |G*| and φ in the parenchyma excluding the ventricles are
tabulated. For comparison of |G*|- and φ-parameter maps, one central
image slice through the genu and splenium of the corpus callosum
was manually selected for each subject and registered to a template
generated from the MRE magnitude images of all subjects using the
ANTs open source software library (Avants et al., 2011). The transforma-
tion model used in our registration was normalised symmetric (Greey
SyN) probability mapping.
2.4. Statistical analysis
All data are expressed as means ± SD. Parameters of brain viscoelas-
ticity (|G*|, φ) were calculated for both, the full brain and the area of the
basal ganglia (lentiform nucleus: putamen, internal and external globus
pallidus), and compared by ANOVA. Groups (subjects vs. patients) were
compared using unpaired t-test (parametric data) or Mann–
Whitney
test (nonparametric data). As age is an important determinant of brain
elasticity, ANOVA was performed with age as a covariate. Correlation
analysis between clinical data (age, disease duration, disease severity)
and parameters of brain elasticity was calculated by Pearson's correla-
tion coefficient. P b .05 was considered statistically significant. All calcu-
lations were performed using GraphPad Prism Version 5.01 (GraphPad,
Inc., La Jolla, CA, USA). Owing to the exploratory nature of this pilot
study, no comparisons for multiple testing were made.
3. Results
3.1. Clinical characteristics
Clinical characteristics of cases and controls are summarised in
Table 1. Among PD cases, eight had an akinetic-rigid phenotype, three
were tremor dominant and seven had an equal symptom presentation.
Among PSP cases, eight met criteria for Richardson subtype and eight
for Parkinson subtype of PSP (PSP-P). Disease duration was slightly
shorter (P = 0.28) in PSP, reflecting the faster progression of PSP,
and there was a trend (P = 0.07, ANOVA) towards an older age in PSP
patients (+6 years compared to controls).
3.2. Brain viscoelasticity in neurodegeneration
Age has been reported to be a determinant of brain viscoelasticity, ac-
counting for a linear decline in whole brain elasticity (μ)of−0.75%/year
(Sack et al., 2011), whereas tissue's microstructure (α) remains
unchanged. To separate these age-related changes from the impact
of neurodegeneration on brain viscoelasticity, statistical comparisons
of MRE parameters included age as covariate. For group-wise com-
parisons, 3DMRE parameters obtained in PSP cases were corrected by
−0.75%/year.
383A. Lipp et al. / NeuroImage: Clinical 3 (2013) 381–387

When compared to control subjects, no significant change in whole
brain MMRE parameters μ and α was found for PD. In contrast, PSP was
associated with a significant reduction of both μ and α of −28.8%
(vs. controls: P b 0.001) and − 4.9% (vs. controls: P b 0.01), respective-
ly. This effect was pronounced in the lentiform nucleus (vs. controls:
Δμ = −34.6%, P = 0.001; Δα = − 8.1%, P b 0.01). Considering this re-
gion in PD patients, only a weak reduction of α of − 7.4% (vs. controls:
P b 0.05) was discernible, while μ remained unchanged (Fig. 1).
3DMRE reproduced our primary findings of stronger reduction of
viscoelastic constants in PSP compared to PD (Δ|G*|: − 10.6%, P b 0.01
[PSP vs. controls]; − 4.8%, not significant [PD vs. controls]; Δφ: − 34.6%,
P b 0.001 [PSP vs. controls]; −15.4%, P = 0.07 [PD vs. controls]) and pro-
nou n ce d reduction of MRE parameters in the lentiform nucleus (Δ|G*|:
−7.8%, P = 0.037 [PSP vs. controls]; − 6.9%, P b 0.05 [PD vs. controls];
Δφ: − 44.8%, P b 0.001 [PSP vs. controls]; − 20.7%, P
=0.06[PDvs.con-
trols]) (Fig. 3).
Contrary to MMRE, where Δμ N Δα,in3DMREΔ|G*| b Δφ,i.e.thedi-
mensionless phase-based parameter, displayed a higher disease-related
change than the shear-modulus parameter, highlighting that the me-
chanical constants measured by MMRE and 3DMRE provide indepen-
dent information on brain constitution. Although μ and φ display
similarly high rates of change with disease, φ has a much higher intra-
group variability and is thus less reliable than μ. The high variability of
φ is also reflected in the normalised parameter maps shown in Fig. 2
for |G*| and φ in a central slice of each of our groups. Fig. 2 addresses
the local variation of 3DMRE parameters. Since φ reflects the duality
of fluid–solid properties of tissue it is highly affected by the heteroge-
neous distribution of fluid-filled spaces in the brain. In contrast, |G*| ap-
pears to be smoother in the normalised group maps with less in-plane
variation than φ, which is consistent with the relative magnitude of
the standard deviations given in Table 2. Both |G*|- and φ-image inten-
sities decrease from the healthy state to PD and PSP. Again, pronounced
signal deterioration is seen in the lentiform nucleus, which are demar-
cated by dashed red lines in the |G*| maps in Fig. 2. Mean intensities
and SD values in these regions are 1913 ± 196 Pa, 1757 ± 117 Pa,
1551 ± 140 Pa for controls, PD and PSP patients, respectively. From
2D-MMRE no normalised parameter maps were attainable. All group
mean values and standard deviations are summarised in Table 2.
3.3. Correlation of brain viscoelastic properties with clinical data
The impact of neurodegeneration on brain viscoelastic properties
also becomes apparent when disease severity and elasticity parameters
are correlated (Table 3, Fig. 4). In the present study, patients had mild to
moderate PD with a mean UPDRS
III-ON
of 16.7 pts., ranging from 4 to 36
pts. There was a strong correlation between UPDRS
III-ON
and 3DMRE
parameters obtained both in the full brain and in the lentiform nucleus
(all r b − 0.5, all P b 0.05, Fig. 4). In PSP, 3DMRE parameters correlated
with disease stage (PSP staging system, full brain and lentiform nucleus,
all r b − 0.5, all P b 0.05 [except imagG]) and less robustly with the clin-
ical symptom score (Golbe score vs. φ
full brain
: r = − 0.51, P =0.04).
Direct comparison of MMRE parameters between cases shows a
significant reduction of μ in PSP patients (PD vs. PSP: full brain Δμ =
−35.6%, P b 0.001; lentiform nucleus Δμ = − 36.7%, P b 0.001), re-
flecting the more rapid and widespread neurodegeneration. Group-
wise comparison of 3DMRE parameters (PD vs. PSP), however, did not
reach statistical significance (PD vs. PSP: full brain Δφ = − 22.0%,
P = 0.058; lentiform nucleus Δφ = − 30.0%, P =0.08).
As previously discussed, age is a known determinant of brain visco-
elasticity (Sack et al., 2009, 2011). Accordingly, there was a strong neg-
ative correlation between age and all 3DMRE parameters in PD (full
brain and lentiform nucleus, r = − 0.49 to − 0.76, all P b 0.05 [except
φ
full brain
]). In contrast, age dependency was less distinct in controls
(imagG
full brain
r = − 0.47, P = 0.048) and non-significant in PSP
cases, probably due to the smaller age range in these groups (PD: 32
to 77 [Δ45] years, controls: 49 to 86 [Δ37] years, PSP: 58 to 83
[Δ25] years). Contrary to 3DMRE, correlation of MMRE parameters
with any of the clinical data (age, severity, or stage) was poor. Neither
of the two groups showed a correlation between disease duration or
gender and MRE parameters.
4. Discussion and conclusion
4.1. Group wise comparison
Our study addressed the alteration of brain viscoelastic constants in
two clinically similar but neuropathologically distinct neurodegenera-
tive conditions.
The main results of our study are as follows: (1) brain viscoelasticity
is reduced in PSP, with a greater reduction within the lentiform nuclei;
(2) reduction of brain viscoelasticity is highly correlated with measures
of clinical severity in both, PSP and PD; and (3) reduction of viscoelastic-
ity in PD is limited to measures of softness (μ, |G*|), while in PSP mea-
sures of viscosity (α, φ) are affected as well.
To date, standard T
1
-andT
2
-weighted cerebral MRI (1.5 T) is insuf-
ficient in detecting PD, especially at early stages (Seppi and Schocke,
2005), and thus is primarily used to exclude potential cases of symp-
tomatic PD. Midbrain and tegmental atrophy as well as frontal and tem-
poral lobe atrophy have been proven to reliably discriminate PSP from
PD and control subjects; however, specificity against atypical Parkinson
syndromes (multiple system atrophy, corticobasal syndrome) is poor
(Lee et al., 2005).
Advanced quantitative structural MR-based techniques such as MRE
and diffusion tensor imaging (DTI) provide more specificmeasuresof
the cellular matrix of the brain parenchyma and thus improve the clas-
sification sensitivity/specificity for neurodegenerative disorders (Menke
et al., 2009).Asshowninthepresentstudyandinourpreviouswork
(Sack et al., 2011), normal ageing is accompanied by a linear decline in
whole brain elasticity as shown by a decrease in μ and |G*|. This is sup-
ported by DTI, where fractional anisotropy (FA), a measure of white
matter connectivity, decreases linearly after the second decade of life
(Lebel et al., 2012; Sullivan et al., 2010).
In neurodegenerative disorders such as PSP, both measures (FA
Whitwell et al., 2011 and MRE) are significantly decreased compared
to healthy age-matched controls, indicating progressive degradation of
the brain cellular matrix. Unlike reduced FA in DTI, the MRE results of
the present study indicate that neurodegeneration in PSP involves at
least two distinct processes — progressive loss of brain elasticity (re-
duced μ and |G*|) and reduction of the viscous damping properties of
the brain (reduced α and φ). The physical quantity underlying DTI is
the water diffusion coefficient. This coefficient is correlated with the
displacement of diffusing water, which is indirectly related to the direc-
tionality and integrity of the underlying tissue structure. Due to the scal-
ing properties of viscoelastic constants in hierarchically ordered tissue
(Kelly and McGough, 2009), MRE provides a more direct measure of
Fig. 1. Group-wise comparison of MMRE parameters μ and α within the lentiform nuclei;
values are group means [SD], *P b 0.05, unpaired t-test.
384 A. Lipp et al. / NeuroImage: Clinical 3 (2013) 381–387

the inherent constitution and the microstructure of the tissue under
investigation (Guo et al., 2012; Posnansky et al., 2012).
4.2. Comparison of 2D and 3D-MRE
Before discussing our results with respect to the underlying patho-
physiology we wish to comment on the viscoelastic notation used in
this study. The classic measure in MRE is the complex shear modulus,
which has a real and an imaginary part, also known as storage modulus
(G′) and loss modulus (G″), respectively. Both parameters are translated
to frequency-independent, i.e. generalised, constants by the springpot
model (Eq. (1)), which is well-established in the MMRE literature
(Asbach et al., 2010; Klatt et al., 2010; Sack et al., 2009). The springpot
implies a constant ratio of G″/G′ and constant slopes of G″ and G′ in
logarithmical coordinates. The ratio is related to our parameter α by
Fig. 2. Normalised parameter maps obtained by 3DMRE. The grayscale in the |G*| maps is from 0 to 3 kPa, the colorscale of phi is from 0 to 0.2. (For interpretation of the references to colour
in this figure, the reader is referred to the web version of this article.)
Fig. 3. Group-wise comparison of 3DMRE parameters |G*| and φ within the lentiform
nuclei; values are group means [SD], *P b 0.05, unpaired t-test.
Table 2
Brain viscoelastic parameters.
Viscoelasticity
parameters
Controls PD PSP P
+
MMRE — full brain
μ [Pa] 2788 ± 302 3038 ± 814 1984 ± 489
⁎,⁎⁎
b 0.001
α 0.303 ± 0.014 0.295 ± 0.018 0.288 ± 0.012
⁎
0.02
MMRE — lentiform nucleus
μ [Pa] 3961 ± 997 3907 ± 1211 2475 ± 1036
⁎,⁎⁎
b 0.001
α 0.349 ± 0.03 0.322 ± 0.03
⁎
0.319 ± 0.029
⁎
0.01
3DMRE — full brain
realG* [Pa] 1814 ± 155 1737 ± 211 1574 ± 145
⁎
b 0.01
imagG* [Pa] 588 ± 94 525 ± 143 423 ± 92
⁎
b 0.01
|G*| [Pa] 1970 ± 176 1876 ± 255 1682 ± 170
⁎
b 0.01
φ 0.26 ± 0.04 0.22 ± 0.07 0.17 ± 0.07
⁎
0.01
3DMRE — lentiform nucleus
realG* [Pa] 1942 ± 182 1804 ± 180
+
1745 ± 213
+
0.05
imagG* [Pa] 620 ± 129 530 ± 158 437 ± 128
+
b 0.01
|G*| [Pa] 2101 ± 199 1955 ± 213
+
1850 ± 233
+
0.01
φ 0.29 ± 0.08 0.23 ± 0.11 0.16 ± 0.11
+
b 0.01
Values are means ± SD;
+
1-way ANOVA (age as covariate); post hoc between-group
analysis (unpaired t-test).
⁎
P b 0.05 vs. controls.
⁎⁎
P b 0.05 vs. PD.
385A. Lipp et al. / NeuroImage: Clinical 3 (2013) 381–387

α =2/π arctan(G″/G′). Furthermore, α is identi fied as the slope of
logG′(logω)andlogG″(logω)(Klattetal.,2010). Thus, our 3DMRE pa-
rameter φ = arctan(G″/G′)(seeEq.(2))shouldequalπ/2 · α,provided
that the simple two-parameter springpot model is valid within our fre-
quency range (from 25 to 62.5 Hz). As this is not fully true (see e.g. Fig. 3
in Sack et al., 2009), we cannot compare φ with α. A further obstacle to
comparing the two phase-based parameters φ and α is their numerical-
ly different treatment. The calculation of α invoked spatially averaged
G′- and G″-values followed by model-fitting. In contrast, φ was de-
rived from G′- and G″-maps and registered to normalised images as
shown in Fig. 2.Consequently,α is less prone to noise than φ,rendering
α more reliable for the assessment of global viscoelastic effects. The
relationship between μ and |G*| depends on α andisthusmorecomplex.
μ and |G*| can be considered equivalent only in materials with dominat-
ing elastic properties. Although brain tissue is more elastic than viscous
(Klatt et al., 2007), |G*| is influenced by viscosity, which may explain its
lower rate of ch ange upon disease. At any rate, a decline of μ (and of |G*|
in elastic solids) indicates ‘softening’, whereas the decay of α or φ
sug-
gests transition to a more elastic material (Guo et al., 2012; Posnansky
et al., 2012).
Softening with unchanged α would imply that the architecture of the
tissue remains preserved while its mechanical scaffold becomes weaker.
Recent studies on isolated cells (Lu et al., 2006) and in vivo murine brain
(Schregel et al., 2012) indicate that axons represent important constitu-
tive elements of the mechanical sca ffold of the brain. Schregel et al.
(2012) observed a drop in |G*| in the presence of extra-axonal re-
organisation, i.e. demyelination and degradation of the extracellular
matrix similar to observations made by Riek et al. (2012) in a mouse
model of neuroinflammation. Since these processes do not affect the
topology of axonal fibres, its influence on α is presumably low, which
is consistent with our previous findings in mild (remitting-relapsing)
MS (Wuerfel et al., 2010) and in the maturating brain (Sack et al.,
2009). Interestingly, for progressive MS (primary and secondary pro-
gressive, pp&sp) and normal pressure hydrocephalus (NPH), an MMRE
parameter decrement on the same order as in our PSP group was report-
ed (MS [pp&sp]: Δμ = − 20.5%, Δα = − 6.1% (Streitberger et al.,
2012); NPH: Δμ = −25.1%, Δα = −9.5% (Streitberger et al., 2011)).
In the light of these results, a drop in |G*| and μ without an
unchanged parameter α suggests the presence of processes like inflam-
mation or disruption of extra-axonal integrity whereas progressive deg-
radation towards neuronal loss would ultimately cause a decline in α as
has been observed in progressive MS, NPH (Streitberger et al., 2011,
2012) and in the PSP group of our current study.
With our current knowledge, we can only tentatively interpret the
different patterns of brain viscoelastic changes in PD and PSP. The neu-
ropathology of PD involves presynaptic accumulation of α-synuclein
(Cheng et al., 2010; Schulz-Schaeffer, 2010), which starts focally and
affects axonal integrity only later in the process of degeneration. In
PSP, hyperphosphorylated tau dissociates from microtubules, causing
disruption of microtubular transport and eventually axonal degradation
(Armstrong and Cairns, 2013). Thus, early loss of axons that are eminent
to the mechanical scaffold of the brain (Freimann et al., in press)might
explain the pronounced loss of |G*|, μ and
α in our group of PSP patients,
while unchanged MRE parameters indicate that axonal degradation is
probably not the primary pathological mechanism in PD. Varying
degrees of extraneuronal involvement (glial, astrocytes) in PSP and PD
might contribute to the pronounced reduction of MRE parameters in
our PSP cases. Although there is neuropathological evidence of limited
glial α-synuclein aggregates also in PD (Fellner et al., 2011), tau pathol-
ogy is dominant in oligodendroglia and astrocytes in PSP (Armstrong
and Cairns, 2013), altering the mechanical scaffold of the brain even
further.
4.3. Limitations
The link of MRE parameters to histological properties of brain tissue
is still controversial and needs further verification. Precision of the
phase angle of the complex modulus (φ) is limited, which prevents us
from drawing further conclusions about the sensitivity of cerebral
MRE to neuronal network structures.
Some technical matters concerning the combination of MMRE and
3DMRE remain to be addressed. In our study, MMRE and 3DMRE had
to be applied separately due to time constraints. A combined method
of 3DMMRE appears feasible with the aid of 3 T MRI and parallel imag-
ing. 3DMMRE would combine the sensitivity of μ with the capability of
3DMRE to provide spatially resolved parameter maps. New develop-
ments in MRE reconstruction methods would largely benefitfrom
3D wave data at multiple drive frequencies (Baghani et al., 2011;
Papazoglou et al., 2012; Van Houten et al., 2011).
Our study has several limitations. First of all, brain viscoelasticity is
known to be inversely related to age. Therefore, the non-significant
trend towards a younger age among our PD patients might overestimate
the differences in MRE between both groups. The effect of age on MRE
parameters, however, was non-significant in our PSP patients and only
limited (imagG
full brain
) in our control group. Second, MRE results in our
PD patients varied widely. This is explained in part by a large age range
(32–77 years) and wide differences in clinical severity (UPDRS
III-ON
:
4–36 pts.), parameters that showed the highest impact on the brain's
viscoelastic properties. Future studies assessing MRE longitudinally
in neurodegenerative disorders such as Parkinson's disease, multiple
system atrophy and PSP will help to define diagnostic thresholds for
an image-based differentiation of neurodegenerative diseases.
Table 3
Correlation of MRE parameters and clinical severity (PD: UPDRS motor part during ON;
PSP: PSP staging system according to Golbe scale (Golbe and Ohman-Strickland, 2007)).
PD
r
PD
P
PSP
r
PSP
P
MMRE — full brain
μ 0.030 0.907 −0.285 0.285
α −0.376 0.124 −0.431 0.095
MMRE — lentiform nucleus
μ 0.487 0.041 − 0.259 0.334
α −0.068 0.790 −0.153 0.570
3DMRE — full brain
realG* − 0.592 0.010 − 0.536 0.032
imagG* − 0.582 0.011 −0.503 0.047
|G*| −0.589 0.010 −0.540 0.031
φ −0.533 0.023 −0.500 0.048
3DMRE — lentiform nucleus
realG* − 0.593 0.012 − 0.511 0.043
imagG* − 0.486 0.048 −0.420 0.105
|G*| −0.607 0.010 −0.506 0.046
φ −0.478 0.053 −0.548 0.028
Fig. 4. Correlation of 3DMRE (|G*|) and severity of clinical symptoms (UPDRS
III-ON
)inPD
patients.
386 A. Lipp et al. / NeuroImage: Clinical 3 (2013) 381–387

In summary, 3DMRE for spatially resolved mechanical parameter
mapping and MMRE for viscoelastic modelling were applied to the
brains of patients with PD and PS and compared to controls. Both MRE
methods revealed a reduction of whole-brain elasticity and viscosity
in PSP due to widespread neurodegenerative processes but showed no
alteration of global viscoelasticity in PD. However, regional analysis by
3DMMRE showed that PD affects the basal ganglia region causing soft-
ening of the tissue. Overall, MMRE was sensitive enough to discriminate
PSP from PD based on the global shear modulus while the enhanced
regional sensitivity of 3DMRE provided the highest correlation with
clinical scores in PD. In the future, a combination of MMRE and
3DMRE may provide a highly sensitive imaging marker for the quantifi-
cation of regional neurodegeneration and the distinction of different
types of neurodegenerative disorders.
Acknowledgements
This work was supported by the German Research Foundation (DFG
Sa901/10 to I.S. and Exc 257 to F.P.).
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