Introduction
Multiple sclerosis (MS) is a chronic
inflammatory demyelinating disease of the central nervous system affecting
white and possibly grey matter. Thalamic axons convey information between multiple
subcortical and specific cortical regions in the brain. That is why thalamus is
considered a crucial structure, serving a wide range of neurologic functions.
Extensive involvement of gray matter (GM), and particularly of the thalamus, is
usually associated with a very wide range of clinical features including
cognitive impairment, motor deficits, painful phenomena and fatigue in patients
with MS. Both direct microstructural damage to thalamus
and indirect damage caused by axonal degeneration secondary to white matter MS lesions
could be intimately related to functional disability in MS1.
Diffusion tensor imaging (DTI) describes the properties of water diffusion in
vivo, thus disclosing important details of fiber tract orientation and
providing information regarding microstructural
integrity of the tissue2. Fractional anisotropy
(FA) and apparent diffusion coefficient (ADC) are considered sensitive measures
to different structural tissue characteristics. As Fractional anisotropy (FA)
reflects the organization and directionality of water
diffusion along axons. Therefore, higher FA values may reflect more coherent
axons, or a higher degree of myelination, on the other hand, lower FA may imply
loss of WM integrity and more tissue damage3. Our aim is to detect the thalamic involvement
using diffusion tensor imaging (DTI) and to study its impact on cognitive
impairment, clinical disability and fatigue in MS patients.
Subjects and MethodS
This is a case control
study conducted on 31 patients (20 males and 11females; Mean age: 34.4±8.5 SD)
with a diagnosis of relapsing remitting multiple sclerosis and secondary
progressive multiple sclerosis according to Revised McDonald Criteria4. We
recruited cases from the multiple sclerosis unit, department of Neurology at
Cairo university hospitals during period from January 2014 to September 2014.We
also recruited 18 age, sex and education level-matched healthy individuals as a
control group. We had excluded patients whose age is < 18 and > 45 years,
patients with primary progressive MS, patients with history of neurological
disorder other than MS, patients with known comorbidities as HTN or DM,
left-handed patients, patients with history of alcohol intake or drugs abuse,
patients with severe sensory deficit preventing them from performing cognitive
tests used this study, history of psychiatric disorders or use of antipsychotic
drugs and patients who had a contraindication to undergo a 1.5 Tesla MR
imaging.
Methods
All MS patients were
subjected to: Evaluation of disability using the expanded disability status scale
(EDSS); EDSS has been the most widely used measure of the disability in
multiple sclerosis5, evaluation of fatigue using the fatigue
severity scale (FSS)(6). Patients who obtained
an FSS score of > 4 were considered fatigued, whereas those with an FSS
score ≤ 4 were considered non-fatigued. All individuals in both groups were
subjected to the following battery of neuropsychological and radiological assessment.
Neuropsychological Assessment:
a)
Mental state examination using Mini-Mental State
Examination (MMSE)7.
b)
California Verbal Learning Test- 2nd edition
(CVLT-II): This test was
used to assess the verbal learning and memory8. The following scores were calculated: Total
recall over all learning trials (CVLT-II-TR), Short-term recall after
interference (CVLT-II-SR) and Recall after the delay interval (CVLT-II-DR).
c)
Brief Visuospatial Memory Test–Revised
(BVMT-R): This test was
used to assess the visuospatial memory and learning. The stimulus material was
a matrix of six visual designs, held before the participant for 90 seconds9. The following measures were considered
for each memory test: Total recall over all learning trials
(BVMT--TR) and Recall after the delay interval (BVMT-DR).
d)
Paced Auditory Serial Addition Task
(PASAT): This test
evaluates working memory and information processing. Scores are the number of
correct responses10.
e)
Symbol Digit Modalities Test (SDMT): The SDMT measures concentration and
sustained attention. Subjects are given 90 s to substitute numbers for symbols
as part of a set code11.
f)
Verbal fluency (VF) test: It assessed the phonemic and semantic
fluency. As regard the phonemic fluency, the examinee must produce orally as
many words as possible beginning with a specified letter (Haa (ح
during a one minute. While in semantic fluency, the examinee is asked to
produce as many animal names as possible within a one-minute interval12.
Neuroradiological Assessment:
Diffusion Tensor Imaging
(DTI): It was performed using a 1.5 Tesla unit (Philips Achieva, Netherlands).
DTI consists of axial single shot spin echo echoplanar sequence in 25 encoding
directions with diffusion weighting factor (b value) of 1000 s/mm2, TR= 10951,
TE= 67, matrix= 128 X 128, FOV= 224 X224 mm, number of excitation= 2, slice
thickness = 3 mm without gaps, flip angle= 90o. Analysis of the images was
performed using Philips workstation. Directionally-encoded color DTI maps were
obtained then fused with T2 weighted images or T2 3D fast field echo (3D FFE)
images. Red, green and blue colors represent right-left, anterior-posterior and
superior-inferior directions, respectively. FA and ADC were measured through
drawing regions of interest (ROI) in the thalami of both cerebral hemispheres
in three consecutive levels. FA and ADC were calculated automatically for each
ROI. Mean FA and ADC were calculated for the right and left thalami and used
for statistical analysis.
Statistical Analysis:
Data was analyzed using IBM SPSS
advanced statistics version 20 (SPSS Inc., Chicago, IL).
Numerical data were expressed as mean and standard deviation or median and
range as appropriate. For not normally distributed quantitative data,
comparison between two groups was done using Mann-Whitney test (non-parametric
t-test). Spearman-rho method was used to test correlation between numerical
variables. All tests were two-tailed. A p-value < 0.05 was considered
significant and less than 0.01 were considered highly significant.
ResultS
I. Comparative Analysis
* Clinical
data:
The duration of
illness among MS patients ranged from 2-20 years with mean disease duration
6.9±4.9 SD. Number of attacks ranged from 3-10 attacks with mean number of
attacks 5.8±2.6 SD and total EDSS ranged from 2- 6.5 with mean total EDSS
3.9±1.6 SD. FSS scores in patient group ranged from 1.1 – 5.5 mean score
3.5±1.2 SD. 10 patients were considered fatigued (FSS score > 4) and 21 were
non-fatigued (FSS ≤ 4). In the fatigued group six patients had SPMS and four
patients had RRMS with statistically significant difference between two groups
(SPMS patients are more fatigued than RRMS patients) (P-value = 0.003).
Although no
statistical significant difference was found between patients and control in
MMSE; however, the patients showed significant worse performance than controls
in all neuropsychological assessment tests used (Table 1). On comparing between
RRMS patients to SPMS patients in performance of neuropsychological tests; SPMS
patients showed worse performance in BVMT-R total recall (P-value = 0.034) and
VF-animal (P-value=0.038). Otherwise, no statistically significant difference
was found in other cognitive tests.
* Radiological
data:
Compared to healthy controls, MS patients
had higher thalamic FA and ADC values than controls (p value <0.001) as
shown in table 2. Moreover, the same finding was detected also in RRMS and PPMS
subgroups (P-value = <0.001, <0.001 respectively). On the other hand,
RRMS and SPMS patients showed no statistically significant difference in mean
thalamic FA or ADC values; which means that there is affected diffusivity over
thalamic tissue in patients with MS regardless its type.
II. Correlative Analysis:
* Neuropsychological
Assessment:
Age was negatively
correlated with CVLT-II-SR (r = -0.49, P-value = 0.005), CVLT-II-DR (r= -0.61, P-value
= <0.001), BVMT-TR (r= -0.52, p value =0.003), BVMT-DR (r= -0.54, 0.002),
SDMT (r= -0.57, P-value = 0.001). While all neuropsychological tests were
correlated with the years of education (p value = <0.001).
Cognitive domains measured; with different
neuropsychological tests, were correlated with duration of illness, number of
attacks, degree of disability but not with fatigue severity (p value > 0.05)
(Table 3).
* Radiological
data:
No correlation was found between FA and
ADC in both thalami and age or education; as for clinical data both FA and ADC
were correlated with number of attacks and total EDSS (Rt. Thalami FA) but not
with duration of illness and degree of disability. In addition, no correlation
was found between thalamus diffusivity and different cognitive domains (Table
4).
Table 1. Comparison between neuropsychological tests in
MS patients and control.
|
MS Patients (N=31)
N=31))
|
Healthy control (N=18)
N=18))
|
P-value
|
Min
|
Max
|
Mean ± SD
|
Min
|
Max
|
Mean ± SD
|
MMSE
|
22
|
30
|
29.3±1.3
|
26
|
30
|
29.7±1
|
0.333
|
CVLT-II-TR
|
16
|
63
|
39.0±10.2
|
40
|
70
|
51.8±8.7
|
<0.001**
|
CVLT-II-SR
|
2
|
16
|
7.9±2.9
|
8
|
15
|
11.6±1.8
|
<0.001**
|
CVLT-II-DR
|
0
|
14
|
8.5±3.2
|
9
|
15
|
11.4±1.7
|
0.001**
|
BVMT-TR
|
0
|
36
|
20.0±11.0
|
15
|
35
|
28.8±4.6
|
0.008**
|
BVMT-DR
|
0
|
12
|
6.9±4.2
|
6
|
12
|
10.6±1.4
|
0.009**
|
PASAT
|
0
|
39
|
22.1±14.9
|
0
|
3
|
26.7±14.7
|
0.038*
|
SDMT
|
2
|
60
|
27.6 ±15.5
|
22
|
54
|
38.6± 8.2
|
0.003**
|
VF-letter
|
2
|
10
|
5.2 ± 2.1
|
9
|
13
|
10.3± 1.2
|
<0.001**
|
VF-animaL
|
6
|
23
|
12.8
± 4.8
|
17
|
23
|
19.3± 1.5
|
<0.001**
|
BVMT-DR Brief Visuospatial Memory Test–Revised,
Delayed Recall, BVMT-TR Brief Visuospatial Memory Test–Revised, Total
Recall, CVLT-II-DR
California Verbal Learning Test- 2nd edition- Delayed Recall, CVLT-II-SR California
Verbal Learning Test- 2nd edition- Short Term Recall, CVLT-II-TR
California Verbal Learning Test- 2nd edition-Total Recall, MS Multiple sclerosis, MMSE
Mini-Mental State Examination, PASAT Paced Auditory Serial
Addition Task, SDMT Symbol Digit Modalities Test, VF Verbal
Fluency.
*Significant at P<0.05 ** Significant
at P<0.01
Table 2. Comparison between radiological results in MS
patients and control.
|
MS
Patients
(N=31)
|
Healthy
control
(N=18)
|
P
value
|
FA Rt. Thalamus
|
0.45 ± 0.03
|
0.39 ± 0.03
|
<0.001*
|
FA Lt Thalamus
|
0.45 ± 0.03
|
0.40 ± 0.03
|
<0.001*
|
ADC Rt. Thalamus
|
0.79 ± 0.04
|
0.71 ± 0.04
|
<0.001*
|
ADC Lt. Thalamus
|
0.78 ± 0.03
|
0.71± 0.03
|
<0.001*
|
ADC Apparent Diffusion Coefficient, FA Fractional
anisotropy,
MS Multiple sclerosis
*Significant at P<0.01
Table 3. Correlations between clinical data and
neuropsychological tests.
|
Duration
of illness
|
Number
of attacks
|
EDSS
|
r
|
p
|
r
|
p
|
r
|
p
|
CVLT-II-TR
|
-0.33
|
0.07
|
-0.23
|
0.21
|
-0.44
|
0.01**
|
CVLT-II-SR
|
-0.28
|
0.13
|
-0.17
|
0.35
|
-0.49
|
0.005**
|
CVLT-II-DR
|
-0.465
|
0.008**
|
-0.37
|
0.04*
|
-0.55
|
0.001**
|
BVMT-TR
|
-0.43
|
0.017*
|
-0.39
|
0.03*
|
-0.6
|
<0.001**
|
BVMT-DR
|
-0.44
|
0.013*
|
-0.38
|
0.034*
|
-0.5
|
0.004**
|
PASAT
|
-0.3
|
0.1
|
-0.31
|
0.1
|
-0.4
|
0.028*
|
SDMT
|
-0.41
|
0.021*
|
-0.22
|
0.23
|
-0.47
|
0.007**
|
VF-Letter
|
-0.2
|
0.29
|
-0.2
|
0.3
|
-0.43
|
0.02*
|
VF-animal
|
-0.29
|
0.12
|
-0.22
|
0.23
|
-0.46
|
0.01**
|
BVMT-DR Brief Visuospatial Memory Test–Revised,
Delayed Recall, BVMT-TR Brief Visuospatial Memory Test–Revised, Total
Recall, CVLT-II-DR
California Verbal Learning Test- 2nd edition- Delayed Recall, CVLT-II-SR
California Verbal Learning Test- 2nd edition- Short Term Recall, CVLT-II-TR
California Verbal Learning Test- 2nd edition-Total Recall, EDSS
Expanded Disability Status Scale, PASAT Paced Auditory Serial Addition Task, SDMT Symbol
Digit Modalities Test, VF Verbal Fluency
*Significant at P<0.05 ** Significant
at P<0.01
Table 4. Correlations of radiological data.
|
Rt.
FA
|
Lt.
FA
|
Rt.
ADC
|
Lt.
ADC
|
r
|
p
|
r
|
p
|
r
|
p
|
r
|
P
|
Age
|
0.03
|
0.11
|
0.22
|
0.3
|
0.19
|
0.55
|
-0.11
|
0.58
|
Educational
level
|
-0.02
|
0.91
|
0.04*
|
0.85
|
0.002
|
0.31
|
0.22
|
0.23
|
Duration
of illness
|
0.78
|
0.001
|
0.62
|
0.001
|
0.29
|
0.11
|
0.13
|
0.5
|
Number
of attacks
|
0.59
|
<.001**
|
0.61
|
<.001**
|
0.43
|
0.02*
|
0.32
|
0.08
|
Total
EDSS
|
0.4
|
0.03*
|
0.36
|
0.05
|
0.16
|
0.4
|
0.2
|
0.28
|
FSS
|
0.35
|
0.05
|
0.25
|
0.17
|
0.34
|
0.06
|
0.30
|
0.10
|
MMSE
|
-0.12
|
0.54
|
-0.19
|
0.30
|
-0.05
|
0.78
|
0.00
|
0.99
|
CVLT-II-TR
|
-0.29
|
0.12
|
-0.18
|
0.35
|
0.00
|
0.99
|
0.02
|
0.91
|
CVLT-II-SR
|
0.01
|
0.96
|
0.02
|
0.90
|
0.23
|
0.20
|
0.38
|
0.04*
|
CVLT-II-DR
|
-0.18
|
0.32
|
-0.26
|
0.16
|
0.05
|
0.78
|
0.26
|
0.15
|
BVMT-TR
|
-0.30
|
0.10
|
-0.32
|
0.08
|
-0.13
|
0.49
|
-0.06
|
0.76
|
BVMT-DR
|
-0.28
|
0.12
|
-0.32
|
0.08
|
-0.10
|
0.61
|
0.04
|
0.84
|
PASAT
|
-0.19
|
0.31
|
-0.23
|
0.22
|
-0.13
|
0.48
|
-0.08
|
0.68
|
SDMT
|
-0.29
|
0.12
|
-0.21
|
0.25
|
-0.03
|
0.89
|
0.00
|
0.98
|
VF-Letter
|
-0.12
|
0.53
|
-0.21
|
0.26
|
-0.14
|
0.45
|
0.00
|
0.99
|
VF-animal
|
-0.26
|
0.17
|
-0.16
|
0.38
|
-0.20
|
0.27
|
-0.04
|
0.82
|
ADC Apparent Diffusion Coefficient, BVMT-DR Brief
Visuospatial Memory Test–Revised, Delayed Recall,BVMT-TR Brief
Visuospatial Memory Test–Revised, Total Recall, CVLT-II-DR
California Verbal Learning Test- 2nd edition- Delayed Recall, CVLT-II-SR
California Verbal Learning Test- 2nd edition- Short Term Recall, CVLT-II-TR
California Verbal Learning Test- 2nd edition-Total Recall, EDSS Expanded
Disability Status Scale, FA Fractional anisotropy, FSS
Fatigue Severity Scale, Lt Left, MMSE= Mini-Mental State Examination, PASAT Paced
Auditory Serial Addition Task, Rt Right, SDMT Symbol
Digit Modalities Test, VF Verbal Fluency
*Significant at P<0.05
DISCUSSION
Cortical and subcortical
demyelination are observed during the course of MS, several grey matter
structures including the thalamus, hippocampus, caudate, putamen and globus
pallidus were involved in MS13,14. Our results showed that there was
a significant thalamic involvement in MS patients (even in normally appearing
thalamic tissue on conventional MRI) as demonstrated using DTI. In concordance
with our results, other studies found significantly increased anisotropy in the
normal appearing basal ganglia including the thalamus15,16.
In
our study there was also significant difference between the subgroup of
patients with RRMS and controls, indicating that subtle thalamic damage can be
present in early in the course of the disease. This goes with the results in
previous studies that showed early thalamic involvement16-19. In
contrary to our results, another study found that there was no change in
diffusivity (ADC) between MS patients and controls20,21.
Cognitive
impairment in MS patient is well proven in several previous studies yet pattern
of cognitive affection was variable; not only between different studies but
also varying considerably among MS patients in same studies22-25. Different
studies were directed to find the anatomical associations with different
cognitive profiles. Thalamic damage can potentially trigger a cognitive
dysfunction in patients with MS26. In our study, we used a battery
of neuropsychological tests that focused mainly on memory (verbal and
visuospatial), learning, attention, planning, information processing and verbal
fluency. These cognitive domains are related greatly to thalamic role in
cognitive process. Our results showed that there was a significant worse
performance in MS patients when compared to healthy controls in all of the
neuropsychological tests. Surprisingly, there was no correlation between
cognitive domains and diffusivity over the thalamus, despite other studies
which support the role of thalamus in cognitive impairment in MS27-31.
This could be due to different imaging modalities used in these studies and the
use of 1.5 T DTI in our study instead of 3T DTI, which can more sensitive to diffusivity
changes. The most likely cause of the increased sensitivity of 3.0 T is
improved detection of small lesions missed by the conventional MRI and also
affection of cognitive functions could be more complex and related more to
cortical–subcortical circuits disconnection32.
Multiple factors could
contribute to the differences in learning, memory and executive functions
profiles among the different MS types, including age, level of education,
disease duration, number of attacks, coexisting clinical disability and
affective disorders22,24,33,34. This supports our results that
showed the presence of significant correlations between age, level of
education, duration of the disease, number of attacks, EDSS and performance in
neuropsychological tests.
We also found
significant correlations between the duration of disease, number of attacks and
the mean FA values over the right and left thalami; which means that the more
the thalamic involvement, the more the clinical disability in patients with MS.
Total EDSS was also correlated with changes of FA over right thalami. Our
results regarding affection of the thalamus and its contribution to disability
in MS, are matching with Tover-Moll et al. (2009), who found that there was
correlation between motor EDSS and diffusivity over the thalamus16.
On the contrary, to our results, they found no correlation between disease
duration and changes in FA or MD in patients with MS, except in the SPMS group.
Fatigue is another
common symptom of MS and affects up to 90% of patients with the disease35.
There was no correlation between fatigue severity and diffusivity changes over
the thalamus. This goes with the results of Codella and colleagues (2002), who
found no significant difference in FA especially over WM between fatigued and
non-fatigued individuals36.
Our
results support the concept of thalamic involvement in MS. It is not only the
white matter that is affected; also we have affection of subcortical grey
matter that contributes to pathophysiology of MS. This thalamic involvement
contributes greatly to cognitive impairment and clinical disability in patients
with MS. The use of 1.5 T DTI helps us to detect microstructural lesions that
could affect anisotropy and diffusivity of tissues and are not visible in
conventional MRI.
[Disclosure: Authors report no conflict
of interest]
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