In vivo assessment of cervical cord damage in MS F. Agosta,

doi:10.1093/brain/awm110
Brain (2007), 130, 2211^2219
In vivo assessment of cervical cord damage in MS
patients: a longitudinal diffusion tensor MRI study
F. Agosta,1,2 M. Absinta,1,2 M. P. Sormani,1,3 A. Ghezzi,4 A. Bertolotto,5 E. Montanari,6 G. Comi2 and
M. Filippi1,2
1
Neuroimaging Research Unit, 2Department of Neurology, Scientific Institute and University Ospedale San Raffaele, Milan,
Unit of Biostatistics, DISSAL, University of Genoa, Genoa, 4Multiple Sclerosis Center, Gallarate Hospital, Gallarate,
5
Department of Neurology, Orbassano Hospital, Orbassano and 6Multiple Sclerosis Center, Fidenza Hospital, Fidenza, Italy
3
Correspondence to: Dr Massimo Filippi, Neuroimaging Research Unit, Department of Neurology, Scientific Institute and
University Ospedale San Raffaele, Via Olgettina, 60, 20132 Milan, Italy
E-mail: [email protected]
Keywords: multiple sclerosis; cervical cord; magnetic resonance imaging; diffusion tensor; disability
Abbreviations: DE ¼ dual-echo; DT ¼ diffusion tensor; DW ¼ diffusion-weighted; EDSS ¼ Expanded Disability Status Scale;
EP ¼ echo planar; ETL ¼ echo train length; FA ¼ fractional anisotropy; Fast-STIR ¼ fast-short-tau inversion recovery;
FOV ¼ field of view; FU ¼ follow up; GM ¼ grey matter; LV ¼ lesion volume; MD ¼ mean diffusivity; MP-RAGE
¼ magnetization-prepared rapid acquisition gradient echo; MR ¼ magnetic resonance; MRI ¼ magnetic resonance imaging;
MS ¼ multiple sclerosis; NA ¼ normal appearing; NAWM ¼ normal appearing white matter; PBVC ¼ percentage brain
volume change; PPMS ¼ primary progressive multiple sclerosis; RRMS ¼ relapsing ^ remitting multiple sclerosis;
SD ¼ standard deviation; SE ¼ spin echo; SENSE ¼ sensitivity encoded; SIENA ¼ Structural Imaging Evaluation of Normalised
Atrophy; SPMS ¼ secondary progressive multiple sclerosis; TE ¼ echo time; TR ¼ repetition time; WM ¼ white matter
Received November 29, 2006. Revised April 11, 2007. Accepted April 16, 2007. Advance Access publication May 29, 2007
ß The Author (2007). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: [email protected]
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Cervical cord damage is likely to contribute to the accumulation of disability in multiple sclerosis (MS) and can
be quantified in vivo using MRI.We used conventional and diffusion tensor (DT) MRI to: (a) define the temporal
evolution of intrinsic tissue injury and atrophy in the cervical cord from MS patients, (b) investigate how these
two aspects of cord damage are interrelated and (c) assess the correlation of cord MRI metrics with concomitant brain damage and disability. Conventional and DT MRI of the brain and cervical cord were obtained from
42 MS patients and 9 healthy controls at baseline and after a mean follow-up of 2.4 years. At each time-point, we
measured: cervical cord lesion number, cross-sectional area, mean diffusivity (MD) and fractional anisotropy
(FA). Brain T2 lesion volume, grey matter MD, normal appearing white matter (NAWM) MD and FA, as well
as longitudinal normalized percentage brain volume changes were also measured.
In MS patients, cervical cord cross-sectional area (P _ 0.001) and FA (P ^ 0.01) decreased, and cervical cord MD
increased (P _ 0.001) during follow-up. Cord FA decrease, but not cord cross-sectional area and MD, was significantly higher (P ^ 0.05) in primary progressive MS patients than in those with either relapsing^remitting or
secondary progressive MS. At baseline and follow-up, moderate correlations were found between intrinsic cord
diffusivity abnormalities and cord cross-sectional area (r values ranging from 0.34 to 0.58), but not between their
changes over time. No cross-sectional and longitudinal correlations were found between these MRI metrics and
the number of cord T2-visible lesions. Brain NAWM MD (P ^ 0.03) and brain volume (P _ 0.001) also changed in
patients. There was no significant correlation between cord and brain MRI metrics at both time-points, as well
as between their changes occurred over the follow-up. Baseline cord cross-sectional area (r ^ 0.40, P ^ 0.01)
and FA (r ^ 0.40, P ^ 0.03) correlated with increase in disability at follow-up.
This study shows that both progressive tissue loss and injury to the remaining tissue occur in the cervical cord of
MS patients, and that these two components of cord damage are not strictly interrelated, thus suggesting that
a multiparametric MRI approach is needed to achieve more accurate estimates of such a damage. MS cord
pathology also seems to be independent of concomitant brain changes, to develop at different rates according
to disease phenotype, and to be associated to medium-term disability accrual.
2212
Brain (2007), 130, 2211^2219
Introduction
Patients and methods
Patients
We studied 42 patients with MS (Polman et al., 2005) [26 females
and 16 males; mean age (SD) ¼ 44.8 (13.2) years; median disease
duration (range) ¼ 12 (3–40) years]. Thirteen patients had
relapsing–remitting (RRMS), 14 secondary progressive (SPMS)
and 15 primary progressive (PPMS) MS (Lublin and Reingold,
1996). In SPMS patients, the mean time since progression was 6.5
(range ¼ 2–17) years. At study entry, 17 patients (nine RRMS,
seven SPMS, one PPMS) were receiving an immunomodulatory
drug, whereas nine patients (two RRMS, four SPMS, three PPMS)
were in immunosuppressive treatment. Nine healthy controls
[7 females and 2 males; mean age (SD) ¼ 38.9 (13.2) years] with
no history of neurological disorders and a normal neurological
exam served as controls. At the time MRI scans were performed,
patients were assessed neurologically by a single physician,
unaware of the MRI results, and disability was measured using
the Expanded Disability Status Scale (EDSS) (Kurtzke, 1983).
At follow-up, patients were considered clinically worsened if they
had an EDSS score increase 1.0, when baseline EDSS was 56.0 or
an EDSS score increase 0.5, when baseline EDSS was 6.0. The
mean follow-up length was 2.4 years (range ¼ 1.5–3.0 years).
During the study period, the occurrence of relapses was assessed
by the same physician. Local Ethical Committee approval and
written informed consent from all individuals were obtained
before study initiation.
Image acquisition
MRI scans of the brain and cervical cord from all subjects were
obtained at study entry and follow-up, using the same 1.5 Tesla
machine, which did not undergo any upgrade during the study
period and was under a regular program of maintenance.
At follow-up, patients were repositioned following published
guidelines (Miller et al., 1991). During each session, the following
sequences were acquired:
(1) Cervical cord: (a) fast-short-tau inversion recovery (fast-STIR)
[repetition time (TR) ¼ 2288 ms, echo time (TE) ¼ 60 ms,
inversion time ¼ 110 ms, echo train length (ETL) ¼ 11, field
of view (FOV) ¼ 280 280 mm2, matrix size ¼ 264 512,
number of signal averages ¼ 4, 8 sagittal slices with thickness ¼ 3 mm and interslice gap ¼ 0.3 mm); (b) sagittal
T1-weighted 3D magnetization-prepared rapid acquisition
gradient echo (MP-RAGE) (TR ¼ 9.7 ms, TE ¼ 4 ms, flip
angle ¼ 128 ,
FOV ¼ 280 280 mm2,
slab
thickness ¼ 160 mm, number of partitions ¼ 128) and (c) pulsedgradient, diffusion-weighted (DW) sensitivity encoded
(SENSE) single-shot echo planar (EP) (reduction factor ¼ 2,
TR ¼ 7000 ms,
TE ¼ 100 ms,
FOV ¼ 240 90 mm2,
matrix ¼ 128 48, echo train ¼ 40 ms, 5 sagittal slices with
thickness ¼ 4 mm). This sequence collects 16 images per
section, including two images with no diffusion
weighting (b 0 s/mm2) and 14 images with the same
b factor of 900 s/mm2, but with gradients applied in different
directions. The non-diffusion-weighted images are needed to
compute the DT, and the gradient orientations were chosen
according to the algorithm proposed by Jones et al. (1999),
which was designed to optimize DT MRI acquisition. The
measurement was repeated four times to improve the signalto-noise ratio. Three saturation bands were used, positioned
in the anterior part of the neck and transversely at the edges
of the FOV in the superior–inferior direction. A detailed
description of this sequence is given elsewhere (Cercignani
et al., 2003).
(2) Brain: (a) dual-echo (DE) turbo spin echo (SE)
(TR ¼ 3300 ms, TE ¼ 16/98 ms, ETL ¼ 5); (b) T1-weighted
conventional SE (TR ¼ 768 ms, TE ¼ 14 ms) and (c) pulsedgradient DW EP (inter-echo spacing ¼ 0.8 ms, TE ¼ 123 ms,
with diffusion-weighting gradients applied in eight different
directions). As in the cervical cord, only two b factors were
used: b1 0 and b2 ¼ 1044 s/mm2 (Bito et al., 1995). For the
brain DE and T1-weighted sequences, 24 contiguous axial
slices were acquired with 5 mm slice thickness, 256 256
matrix and 250 250 mm2 FOV. The slices were positioned
to run parallel to a line that joins the most infero-anterior
and infero-posterior parts of the corpus callosum. For the
brain DW scans, 10 axial slices with 5 mm slice thickness,
128 128 matrix and 250 250 mm2 FOV were acquired,
with the same orientation as the DE scans, and with the
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The spinal cord is a common site of pathology in multiple
sclerosis (MS) (Ikuta and Zimmermann, 1976) and
conventional MRI can detect cord lesions in up to 90%
of patients with established disease (Lycklama a` Nijeholt
et al., 2003). However, conventional MRI is unable to grade
the extent of tissue injury within macroscopic lesions, as
well as to detect and quantify the ‘occult’ damage known to
occur in the normal-appearing tissues of patients with MS
(Filippi and Grossman, 2002).
In an attempt to overcome these limitations and to
define new MR markers more closely linked to the most
disabling pathological features of MS (i.e. irreversible
demyelination and neuroaxonal injury), diffusion tensor
(DT) MRI has received considerable attention (Rovaris
et al., 2005a). The development of a novel DT MRI
sequence (Cercignani et al., 2003) has recently made
possible to achieve an accurate estimate of the extent of
cervical cord damage (Agosta et al., 2005; Valsasina et al.,
2005, 2007; Benedetti et al., 2006), which have been shown
by cross-sectional studies to correlate with the level of
disability associated to demyelinating (Valsasina et al., 2005;
Benedetti et al., 2006) and degenerative (Valsasina et al.,
2007) conditions. Whereas a few longitudinal DT MRI
studies of the brain have been performed in patients with
MS (Caramia et al., 2002; Cassol et al., 2004; Schmierer
et al., 2004; Oreja-Guevara et al., 2005; Rovaris et al.,
2005b), the temporal evolution of cervical cord diffusivity
changes has not been investigated yet in these patients.
Against this background, we performed a longitudinal,
conventional and DT MRI study of the cervical cord in MS
patients to: (a) define the temporal evolution of intrinsic
tissue injury and atrophy in the cervical cord from MS
patients, (b) investigate how these two aspects of cord
damage are interrelated and (c) assess the correlation of
cord MRI metrics with concomitant brain damage and
disability.
F. Agosta et al.
Longitudinal cord DT MRI changes in MS
Brain (2007), 130, 2211^2219
2213
Table 1 Main demographic and clinical characteristics of patients at baseline and follow-up
Number of patients
Males/females
Mean age (SD) (years)
Median disease duration (range) (years)
Median EDSS at baseline (range)
Median EDSS at FU (range)
All patients
RRMS
SPMS
PPMS
42
16/26
44.8 (13.2)
12 (3^ 40)
4.0 (1.0 ^7.5)
5.0 (1.0 ^ 8.5)
13
5/8
33.4 (5.5)
9 (3^16)
2.0 (1.0 ^ 4.0)
1.5 (1.0 ^ 4.0)
14
3/11
44.1 (10.6)
16 (11^ 40)
5.5 (3.0 ^7.5)
6.0 (3.0 ^ 8.5)
15
8/7
55.4 (12.0)
11 (3^35)
5.5 (3.0 ^7.0)
6.0 (3.0 ^ 8.0)
Abbreviations: RRMS ¼ relapsing ^ remitting multiple sclerosis; SPMS ¼ secondary progressive multiple sclerosis; PPMS ¼ primary
progressive multiple sclerosis; SD ¼ standard deviation; EDSS ¼ Expanded Disability Status Scale; FU ¼ follow-up.
second-last caudal slice positioned to match exactly the
central slices of the DE set. This brain portion was chosen
since these central slices are less affected by the distortions
due to B0 field inhomogeneity, which can affect image coregistration.
Image analysis
Statistical analysis
The baseline and follow-up values of conventional and DT MRIderived metrics were compared using a repeated measures analysis
Results
No abnormalities were seen on the conventional brain and
cervical cord MR images obtained from healthy controls.
During the study period, all MRI metrics from healthy
controls remained stable (data not shown).
In the whole cohort of patients, median EDSS
scores were 4.0 (range ¼ 1.0–7.5) at baseline and 5.0
(range ¼ 1.0–8.5) at follow-up. During the follow-up,
7 RRMS patients experienced 14 relapses. All relapses
were treated with intravenous methylprednisolone (1 g/d for
3–5 days without tapering). In these patients, follow-up
MRI scans were always obtained at least 3 months after the
attack. During the study period, in one SPMS and in three
RRMS patients the treatment was changed from an
immunomodulatory to an immunosuppressive drug. In
one PPMS patient the immunosuppressive treatment was
stopped because of intolerance. At follow-up 14 patients
(six SPMS and eight PPMS) were considered clinically
worsened. The main demographic and clinical characteristics of the three groups of patients at study entry and
follow-up are presented in Table 1.
At baseline, 84 cervical cord lesions were found in 33
patients (79%, median number of lesions/patient ¼ 2,
range ¼ 0–5). At follow-up, eight patients (three RRMS,
three SPMS and two PPMS) had at least one new cord
lesion (six patients had one new cord lesions and two
patients had two new cord lesions). Table 2 reports cervical
cord cross-sectional area and DT MRI histogram-derived
quantities for MS patients at baseline and follow-up.
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All MRI post-processing was performed by two experienced
observers by consensus, unaware to whom the scans belonged.
Cervical cord MS lesions were first identified on the hardcopies of
fast-STIR scans. Then, fast-STIR scans were reviewed in a
chronological order and the new lesions seen on follow-up
images counted. After off-line reconstruction of cervical cord DT
MRI data, cervical cord mean diffusivity (MD) and fractional
anisotropy (FA) maps were derived and MD and FA histograms
produced, as previously described (Valsasina et al., 2005). For each
histogram, only the average MD and FA were a priori chosen to
enter the analysis, to minimize the number of comparisons and
hence reduce the risk of type I error. Cervical cord cross-sectional
area was measured using a semi-automated technique developed
by Losseff et al. (1996).
Following the identification of brain T2-hyperintense lesions on
DE scans, T2 lesion volume (LV) was measured using a computerassisted technique (Rovaris et al., 1997). Brain MD and FA maps
were derived for every pixel, as for the cord. Using SPM2 and
maximum image in-homogeneity correction (Ashburner and
Friston, 1997), brain grey matter (GM), white matter (WM) and
CSF were automatically segmented from the DE images. Each
pixel was classified as GM, WM or CSF, dependent on which
mask had the greatest probability at that location. This generated
mutually exclusive masks for each tissue, which were superimposed onto the MD and FA maps (on which hyperintense
lesions were masked out previously), and the corresponding MD
histograms of the NAWM and GM and FA histogram of NAWM
produced (Rovaris et al., 2005b). FA histograms were derived only
for the NAWM, since no preferential direction of water molecular
motion is expected to occur in GM, due to the absence of a
microstructural anisotropic organization of this compartment. As
for the cord, only the average MD and FA entered the analysis.
Longitudinal percentage brain volume change (PBVC) was
calculated using brain T1-weighted images and the Structural
Imaging Evaluation of Normalised Atrophy (SIENA) software
(Smith et al., 2002).
of variance (ANOVA) model, adjusted for age and, in case of
patients, clinical phenotype. Cross-sectional area of the cervical
cord was also used as a covariate in the comparison between
baseline and follow-up DT MRI quantities of the cervical
cord. The percentage changes over time of MRI quantities were
adjusted for age and cord cross-sectional area whenever needed.
A ‘time group’ interaction analysis was performed to assess the
heterogeneity of MRI changes over time among clinical phenotypes; the results were displayed using forest plots. Univariate
correlations were assessed using the Spearman Rank Correlation
Coefficient. An univariate logistic regression model, adjusted for
follow-up duration, was used to investigate the role of clinical and
MRI quantities as independent predictors of the probability to
have an EDSS worsening at follow-up.
2214
Brain (2007), 130, 2211^2219
F. Agosta et al.
Table 2 Cervical cord conventional and DT MRI findings at baseline and follow-up in MS patients
Cross-sectional areaçbaseline (mm3)
Cross-sectional areaçFU (mm3)
Average MDçbaseline (103 mm2/s)
Average MDçFU (103 mm2/s)
Average FAçbaseline
Average FAçFU
Mean (SD)
Range
Mean (SD)
Range
P
Mean (SD)
Range
Mean (SD)
Range
P
Mean (SD)
Range
Mean (SD)
Range
Pa
All patients
RRMS
SPMS
76.5 (11.6)
49.8 ^101.7
72.9 (10.8)
46.7^96.2
50.001
1.26 (0.13)
0.95^1.57
1.37 (0.12)
1.08 ^1.73
50.001
0.37 (0.06)
0.27^ 0.50
0.36 (0.05)
0.21^ 0.46
0.01
83.1 (11.9)
71.6 (11.6)
57.9^101.7
49.8 ^95.7
77.7 (9.7)
69.4 (12.5)
54.8 ^96.2
46.7^90.0
P for ‘time group’ interaction ¼ 0.44
1.22 (0.11)
1.30 (0.17)
1.04 ^1.38
0.95^1.57
1.34 (0.16)
1.38 (0.11)
1.08 ^1.73
1.19^1.50
P for ‘time group’ interaction ¼ 0.80
0.40 (0.05)
0.34 (0.05)
0.27^ 0.50
0.27^ 0.46
0.39 (0.03)
0.34 (0.06)
0.33^ 0.45
0.21^ 0.46
P for ‘time group’ interaction ¼ 0.05
PPMS
75.1 (9.1)
54.8 ^91.2
72.0 (9.1)
56.2^ 83.7
1.26 (0.11)
1.09^1.47
1.38 (0.09)
1.23^1.54
0.37 (0.06)
0.29^ 0.48
0.35 (0.04)
0.28 ^ 0.42
a
Adjusted for age (see text for further details).
Abbreviations: RRMS ¼ relapsing ^ remitting multiple sclerosis; SPMS ¼ secondary progressive multiple sclerosis; PPMS ¼ primary progressive
multiple sclerosis; SD ¼ standard deviation; FU ¼ follow-up; MD ¼ mean diffusivity; FA ¼ fractional anisotropy.
In Fig. 1, the forest plot of the same quantities is presented
for the overall sample of patients and for each of the three
disease phenotypes. Cord area decreased at follow-up
(P50.001) at a similar rate in all the three patient groups
(P for ‘time group’ interaction ¼ 0.44). An increase of
cord average MD (P50.001) and a decrease of average
cervical cord FA (P ¼ 0.01) were also observed in the
patient cohort; the MD increase was again independent of
clinical phenotype (P for ‘time group’ interaction ¼ 0.80),
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Fig. 1 Forest plot of the ‘time group’ interaction analysis of
cervical cord cross-sectional area and diffusivity changes over time,
for the overall sample of multiple sclerosis patients and for each of
the three disease phenotypes. The x-axis reports magnetic
resonance imaging metrics percentage changes. The bars represent
the 95% confidence intervals of measurements. Note that the
forest plot for FA does not necessarily show the same trend as the
statistics presented in Table 2, because the forest plot displays the
estimated magnetic resonance imaging results for the average age
of each group of patients and average FA decrease was found to be
associated to patient age. See the text for further details.
Abbreviations: RRMS ¼ relapsing ^ remitting multiple sclerosis;
SPMS ¼ secondary progressive multiple sclerosis; PPMS ¼ primary
progressive multiple sclerosis; MD ¼ mean diffusivity;
FA ¼ fractional anisotropy.
whereas the FA decrease was associated to patient age (P for
‘time age’ interaction ¼ 0.02, being higher for younger
patients) and clinical phenotype (P for ‘time group’
interaction ¼ 0.05), being higher in PPMS patients than in
the other two groups. As shown in Fig. 1, the mean FA
change (estimated at the average age for each patient
group) was 4.2% (standard error ¼ 2.9%) for PPMS,
þ1.1% (standard error ¼ 4.2) for SPMS and 0.2%
(standard error ¼ 2.8%) for RRMS patients. This did not
change after adjusting for disease duration (data not
shown). Also, none of the conventional and DT MRI
changes differed significantly between patients with and
without relapses during follow-up or between patients
receiving or not receiving disease-modifying treatment
(data not shown).
Brain T2 LV did not change significantly over the study
period [mean T2 LV (SD) was 17.7 (16.6) ml at baseline
and 18.3 (16.2) ml at follow-up]. The mean PBVC was
1.40 (SD ¼ 1.15). Table 3 reports brain DT MRI
histogram-derived quantities for MS patients at baseline
and follow-up. In Fig. 2, the forest plot of the same
quantities is presented for the overall sample of patients
and for each of the three disease phenotypes. An increase of
average NAWM MD (P ¼ 0.03), which was independent of
clinical phenotype (P for ‘time group’ interaction ¼ 0.35),
was found. Brain NAWM FA significantly decreased only in
SPMS patients (P for ‘time group’ interaction ¼ 0.02).
At baseline and follow-up, average MD and FA of the
cervical cord did not correlate with the number of cord
lesions seen at the two time-points and their changes over
time did not differ significantly between patients with and
without new cord lesions at follow up (r values ranged
from 0.15 to 0.23). Baseline average MD and FA of the
cervical cord correlated with cervical cord area at baseline
(MD: r ¼ 0.34, P ¼ 0.03; FA: r ¼ 0.58, P50.001)
Longitudinal cord DT MRI changes in MS
Brain (2007), 130, 2211^2219
2215
Table 3 Brain DT MRI findings at baseline and follow-up in MS patients
NAWM average MDçbaseline (103 mm2/s)
NAWM average MDçFU (103 mm2/s)
GM average MDçbaseline (103 mm2/s)
GM average MDçFU (103 mm2/s)
NAWM average FAçbaseline
NAWM average FAçFU
Mean (SD)
Range
Mean (SD)
Range
P
Mean (SD)
Range
Mean (SD)
Range
P
Mean (SD)
Range
Mean (SD)
Range
P
All patients
RRMS
SPMS
PPMS
0.86 (0.06)
0.79^1.08
0.88 (0.11)
0.80 ^1.36
0.03
1.11 (0.11)
0.98 ^1.43
1.10 (0.11)
0.97^1.49
0.10
0.27 (0.03)
0.19^ 0.31
0.26 (0.03)
0.14 ^ 0.30
0.07
0.85 (0.05)
0.87 (0.09)
0.87 (0.05)
0.81^ 0.96
0.79^1.08
0.83^ 0.98
0.85 (0.05)
0.92 (0.16)
0.89 (0.09)
0.80 ^ 0.96
0.80 ^1.36
0.81^1.14
P for ‘time group’ interaction ¼ 0.35
1.09 (0.10)
1.13 (0.15)
1.13 (0.10)
1.00 ^1.35
0.98 ^1.43
1.05^1.34
1.08 (0.09)
1.13 (0.16)
1.08 (0.04)
0.98 ^1.30
0.97^1.49
1.02^1.16
P for ‘time group’ interaction ¼ 0.26
0.28 (0.02)
0.26 (0.04)
0.26 (0.02)
0.24 ^ 0.30
0.19^ 0.31
0.21^ 0.29
0.28 (0.02)
0.25 (0.05)
0.26 (0.02)
0.25^ 0.30
0.14 ^ 0.30
0.21^ 0.29
P for ‘time group’ interaction ¼ 0.02
Abbreviations: RRMS ¼ relapsing ^ remitting multiple sclerosis; SPMS ¼ secondary progressive multiple sclerosis; PPMS ¼ primary
progressive multiple sclerosis; NAWM ¼ normal-appearing white matter; MD ¼ mean diffusivity; SD ¼ standard deviation; FU ¼ follow-up;
GM ¼ grey matter; FA ¼ fractional anisotropy.
Fig. 2 Forest plot of the ‘time group’ interaction analysis of
brain diffusivity changes over time, for the overall sample of
multiple sclerosis patients and for each of the three disease
phenotypes. The x-axis reports magnetic resonance imaging
metrics percentage changes. The bars represent the 95%
confidence intervals of measurements. Note that when the
‘time group’ interaction effect was not significant, we cannot
exclude that the diffusivity differences between groups are just
a chance finding. Abbreviations: RRMS ¼ relapsing ^ remitting
multiple sclerosis; SPMS ¼ secondary progressive multiple
sclerosis; PPMS ¼ primary progressive multiple sclerosis;
NAWM ¼ normal appearing white matter; MD ¼ mean diffusivity;
FA ¼ fractional anisotropy; GM ¼ grey matter.
and follow-up (MD: r ¼ 0.42, P ¼ 0.003; FA: r ¼ 0.56,
P50.001). No significant correlation was found between
the longitudinal change of cord atrophy with the concomitant changes of cord MD and FA. Also, there were no
significant correlations either between baseline cord and
brain MRI metrics (r values ranged from 0.11 to 0.27)
and between their percentage changes over time (r values
Discussion
Despite post-mortem studies have convincingly shown
that cord atrophy does not reflect the actual extent of
irreversible tissue damage of this structure (Ganter et al.,
1999; Bergers et al., 2002; Bot et al., 2004; DeLuca et al.,
2004, 2006), possibly because of the ‘counterbalancing’
effect of inflammatory and gliotic changes in the vicinity of
axonal pathology (Lycklama a` Nijeholt et al., 2001;
Mottershead et al., 2003), most of the available in vivo
MRI studies of MS-related cord injury are still based only
on measures of cord atrophy (Filippi et al., 1996; Losseff
et al., 1996; Lycklama a` Nijeholt et al., 1998; Stevenson
et al., 1998a, b, 2000; Rovaris et al., 2001; Ingle et al., 2003;
Lin et al., 2003; Sastre-Garriga et al., 2005). Only a few MRI
studies have attempted to assess the extent of intrinsic cord
damage, using either MT (Bozzali et al., 1999; Filippi et al.,
2000; Rovaris et al., 2000) or DT (Agosta et al., 2005;
Valsasina et al., 2005; Benedetti et al., 2006; Hesseltine
et al., 2006) MRI. None of these latter studies was,
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ranged from 0.21 to 0.22). At baseline, EDSS
significantly correlated with brain T2 LV (r ¼ 0.31,
P ¼ 0.05), brain NAWM MD (r ¼ 0.34, P ¼ 0.05),
brain NAWM FA (r ¼ 0.38, P ¼ 0.02), cervical cord
area (r ¼ 0.39, P ¼ 0.01) and cervical cord average FA
(r ¼ 0.51, P ¼ 0.001). Baseline cervical cord area
(r ¼ 0.40, P ¼ 0.01) and cervical cord average
FA (r ¼ 0.40, P ¼ 0.03) were the only two MRI quantities
associated to EDSS changes observed during the follow-up.
None of the changes of conventional and DT MRI-derived
metrics differed significantly between patients with and
without clinical worsening (data not shown), nor there was
a significant correlation between MRI and EDSS score
changes (r values ranged from 0.21 to 0.19).
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Brain (2007), 130, 2211^2219
might reflect a net loss of structural barriers to water
molecular motion and fibre bundle coherence, which in
turn are likely to be the result of axonal pathology. This
notion is also supported by a high-field study of postmortem MS spinal cords (Mottershead et al., 2003), which
demonstrated that axonal density correlated with decreased
diffusion anisotropy and, although weakly, increased
apparent diffusion coefficient.
Although the development of cord atrophy, which
occurred in our sample during the follow-up, would
increase the likelihood of partial volume effect from the
CSF and hence result in increased diffusivity changes at
follow-up compared to baseline, we do not believe that the
observed progressive alteration of DT MRI metrics is
influenced a great deal by contamination of pixels at the
edge of the cord. This is because of at least four reasons.
First, cord diffusivity changes over follow-up were not
significantly associated to the concomitant decrease of cord
area. Second, since atrophy developed at a similar rate in all
the three patient groups, one would have expected, in case
of a significant partial volume effect, to see a similar rate of
diffusivity changes in all three groups, but this was not the
case at least for FA. Third, we ran the analysis of DT MRI
changes over time with correction for cord area changes.
Finally, contamination from the CSF was further minimized
by considering in the analysis only pixels away from the
edge of the cord (Valsasina et al., 2005).
Another important issue to be addressed is how much of
the axonal pathology in the cervical cord of MS patients is
due to local damage and how much is due to retrograde
and anterograde degeneration of neurons secondary to the
injury of fibres traversing WM lesions of the brain
(Evangelou et al., 2000). Although this study can only
give a partial answer to this question, it is likely that
‘distant’ pathology (i.e. axonal damage followed by anterograde/retrograde degeneration) is not a major contributor
of the observed cord diffusivity changes. This notion is
supported by the lack of a correlation between cord and
brain MRI metrics found in the present study, which agrees
with previous pathological (DeLuca et al., 2004, 2006) and
cross-sectional MRI (Lycklama a` Nijeholt et al., 1998;
Rovaris et al., 2000; Agosta et al., 2005; Valsasina et al.
2005) reports. We also did not find a significant correlation
between the extent of cervical cord T2 lesions and
diffusivity alterations in these patients. This agrees with
the results of post-mortem studies, showing that axonal
damage and cord atrophy occur largely independent of
local areas of inflammatory demyelination (Bjartmar et al.,
2000; Bergers et al., 2002; DeLuca et al., 2006). Therefore,
our data support the notion that inflammatory demyelination (local and distant) may not be the only causative factor
of intrinsic diffusivity changes of the cervical cord seen in
patients with MS and that the nature of the process may be
one of neurodegeneration wherein an underlying diffuse
axonopathy, independent of inflammatory demyelination,
contributes significantly to axonal loss in the cord and
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however, longitudinal and thus did not provide any clue on
the dynamics of intrinsic cord damage associated to MS
and how this relates to the development of cord atrophy
and disability. This study shows that MS patients not only
experience a progressive cord atrophy, a finding which is
consistent with those of previous longitudinal studies
(Stevenson et al., 1998b, 2000; Lin et al., 2003; Ingle
et al., 2003; Sastre-Garriga et al., 2005), but also progressive
structural changes in the residual cervical cord tissue. It also
shows that such changes can be monitored by the use of
serial DT MRI scans and that their assessment may be
important to achieve a more complete picture of the
mechanisms associated to the development of irreversible
tissue loss and disability in patients with MS.
With this in mind, a major issue to be addressed is to
attempt to define the possible pathological substrates of
the observed progressive change of cervical cord water
diffusivity in MS. There is now compelling evidence, based
on post-mortem studies, that in addition to demyelination
(Lycklama a` Nijeholt et al., 2001; Bergers et al., 2002;
Mottershead et al., 2003; Bot et al., 2004; De Luca et al.,
2006), axonal loss is a major feature of cord T2-visible
lesions and normal-appearing tissue (Ganter et al., 1999;
Bjartmar et al., 2000; Lovas et al., 2000; Bergers et al., 2002;
De Luca et al., 2004; Evangelou et al., 2005; De Luca et al.,
2006). Post-mortem assessment also showed that axonal loss
in patients with MS is more pronounced in the cervical
than in other portions of the cord (De Luca et al., 2004)
and that small diameter nerve fibres are more severely
injured by the pathological process, with large fibres being
relatively preserved (Ganter et al., 1999; DeLuca et al.,
2004). Demyelination and axonal loss may result in an
increased extracellular space between surviving fibres,
which, however, can harbour cell debris, inflammatory
infiltrates, fibrillary gliosis and astrocytic proliferation
(Lycklama a` Nijeholt et al., 2001). Finally, although only
a few post-mortem studies assessed cord GM damage in MS
(Lycklama a` Nijeholt et al., 2001; Bot et al., 2004; Gilmore
et al., 2005, 2006), it is conceivable, as it has been shown
for the brain (Kidd et al., 1999; Evangelou et al., 2000;
Peterson et al., 2001; Geurts et al., 2005), that loss of
neurons, secondary to GM discrete lesions or to axonal
transection in the WM, may also occur. All these
pathological changes have the potential to alter the
diffusivity properties of the cervical cord. Increased
extracellular spaces (due to axonal and neuronal loss), as
well as an increased proportion of large diameter fibres can
indeed encourage water diffusion and lead to an increased
average MD. Intracellular abnormalities of the surviving
axons with a consequent reduced anisotropy of intracellular
diffusion (Pierpaoli et al., 1996), and the formation of ‘new’
barriers, due to cell debris, inflammatory infiltrates and
gliosis, which restrict water molecular motion isotropically,
can result in a reduced average FA. Our findings, therefore,
suggest that the progressive increase of MD and decrease of
FA in the cervical cord of MS patients during follow-up
F. Agosta et al.
Longitudinal cord DT MRI changes in MS
2217
MS course to accrual similar levels of disability (Confavreux
and Vukusic, 2006).
This study also showed that cross-sectional area and FA
of the cervical cord at baseline were associated not only to
the baseline EDSS score, but also to the accrual of disability
over the follow-up. Interestingly, this was not found to be
the case for any of the brain MRI-derived quantities
measured in the present study. The role of cord area in
predicting the accumulation of disability in MS patients
has been already highlighted by previous cross-sectional
(Filippi et al., 1996; Losseff et al., 1996; Lycklama a` Nijeholt
et al., 1998; Stevenson et al., 1998a; Rovaris et al., 2001)
and longitudinal (Ingle et al., 2003; Lin et al., 2003; SastreGarriga et al., 2005) MRI studies. This study adds to this by
showing that the assessment of intrinsic cord pathology
may be a rewarding exercise to improve our ability to
predict medium-term evolution of disability. This is
particularly true when considering that the magnitude of
the correlation between cord cross-sectional area and FA is
moderate, thus suggesting that these two metrics convey
pieces of information that only partially overlap. The fact
that cord FA and not cord MD is associated to the
subsequent clinical evolution of the disease may be due to
the fact that all possible MS pathological substrates of cord
damage (i.e. inflammatory infiltrates and oedema, cell
debris, demyelination, axonal loss and injury, neuronal loss
and astrocytic proliferation) do concur to FA reduction,
whereas their impact on MD is likely to be variable,
with some of them leading to decreased MD values
(i.e. inflammatory oedema, demyelination, axonal loss and
injury and neuronal loss) and others leading to MD
‘pseudonormalization’ (i.e. inflammatory infiltrates, cell
debris, astrocytic proliferation, fibrillary gliosis and shrinkage of the tissue).
The absence of a significant correlation between cord
MRI and disability changes over time, as well as the finding
that patients with and without a significant EDSS score
increase during the follow-up did not differ in terms of
concomitant changes of cord DT MRI metrics, albeit
possibly disappointing, were not unexpected for a number
of reasons. First, at least in the less-disabled patients, an
increase in the EDSS score might just reflect a worsening of
clinical signs, which may not be associated to an
accumulation of ‘fixed’ disability. Second, EDSS score has
several limitations, including a relatively poor sensitivity to
disease-related changes (Hobart et al., 2004). Third, some
of our patients (e.g. two patients with SPMS and a
relatively low EDSS at study entry) might not have been
fully representative of the ‘classical’ course of the disease.
Finally and most importantly, it is conceivable that
pathological changes occurring at one stage of the disease
may give rise to an immediate change of the MR properties
of the injured tissues, but result in a measurable clinical
impact at a later stage. These considerations would call
for future longitudinal studies with a longer follow-up
duration on patients with a more homogeneous
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hence to diffusivity changes. Clearly, since post-mortem
studies showed variable degrees of correlation between
plaque load and axonal loss in different brain and cord
tracts (Evangelou et al., 2000; DeLuca et al., 2006) and since
it is at present not possible to obtain reliable in vivo
MRI estimates of specific tract pathology in the cord, we
cannot exclude that both processes (i.e. inflammatory
demyelination and diffuse axonopathy) may operate to
varying extent in different patients and in different tracts.
Another novel finding of this study was the demonstration that intrinsic cord diffusivity abnormalities at baseline
correlate moderately with the severity of cord atrophy at
follow-up. This suggests that intrinsic cord abnormalities
precede the development of cord atrophy. Demyelinated
and partially degenerated axons, as well as sublethally
injured and functionally impaired neurons may cause
diffusivity changes that would not necessarily result in
cord atrophy. This is also supported by the observation
that, during the follow-up, DT MRI changes over time did
not correlate with the concomitant changes of cord
atrophy, which indicates that a relatively long period of
time may be needed for intrinsic cord changes to result in
irreversible tissue loss or, alternatively but not mutually
exclusively, for irreversible tissue loss to develop at a
magnitude enough to overcome the ‘masking’ effect of
inflammatory infiltrates and gliosis on MRI measures of
cord atrophy. Although additional longitudinal multiparametric MRI studies of early RRMS patients with longer
follow-up periods are needed to better elucidate the
dynamics of cord atrophy evolution in MS, the possibility
of detecting with DT MRI the presence of incipient and
potentially reversible intrinsic cord changes opens up new
venues for treatment monitoring in MS.
We also investigated whether the dynamics of cord
damage vary among the three major clinical phenotypes of
the disease. We found that, whereas cord cross-sectional
area and average MD evolve at similar rates in all patient
groups, average cord FA declines more rapidly in patients
with PPMS than in those with RRMS and SPMS, thus
suggesting a more pronounced loss of cord fibres integrity
in the former group. PPMS patients are typically characterized by severe locomotor disability despite the paucity
of brain abnormalities (Thompson et al., 2000). As a
consequence, our findings strengthen the notion that the
‘preferential’ involvement of the cervical cord in PPMS
patients (Lycklama a` Nijeholt et al., 1998; Filippi et al.,
2000) may, at least partially, explain the discrepancy
between brain MRI and clinical findings and the disproportion between the severity of locomotor disability and the
less-pronounced impairment of other functional systems
(Thompson et al., 2000). The observed faster rate of
cervical cord damage development in PPMS patients may
also contribute to explain why progressive patients from
onset reach disability milestones in a fraction of the time
needed to patients with an exacerbating-remitting initial
Brain (2007), 130, 2211^2219
2218
Brain (2007), 130, 2211^2219
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