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Carotid atherosclerosis and progression of brain atrophy The SMART-MR Study.

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ORIGINAL ARTICLE
Carotid Atherosclerosis and Progression
of Brain Atrophy: The SMART-MR Study
Majon Muller, MD, PhD,1,2 Yolanda van der Graaf, MD, PhD,2 Ale Algra, MD, PhD,2,3
Jeroen Hendrikse, MD, PhD,4 Willem P. Mali, MD, PhD,4 and Mirjam I. Geerlings, PhD2;
for the SMART Study Group
Objective: Atherosclerosis has been implicated in the development of brain atrophy. However, support for this
association comes from cross-sectional studies.
Methods: Within the Second Manifestations of ARTerial disease-Magnetic Resonance (SMART-MR) study, a
prospective cohort study among patients with symptomatic atherosclerotic disease (mean age 6 standard deviation,
58 6 10 years; 80% men), magnetic resonance imaging of the brain was performed in 1,232 patients at baseline
(2001–2005) and in 663 patients at follow-up (2006–2009). Brain segmentation was used to quantify total brain
volume, cortical gray matter volume, and ventricular volume as indicators of global, cortical, and subcortical atrophy.
At baseline, measurements of carotid intima–media thickness (CIMT) and carotid stenosis were performed. Carotid
stenosis was classified into groups 0 of 50%, 50 of 70% (moderate), and >70% (severe) and into unilateral or
bilateral stenosis.
Results: Cross-sectional regression analyses showed that both increased CIMT and carotid stenosis were associated
with decreased relative total brain and cortical gray matter volume. Our prospective findings showed that after a
mean follow-up of 3.9 years (range, 3.0–5.8 years), CIMT and moderate stenosis were not related to progression of
brain atrophy. Only severe or bilateral carotid stenosis was related to progression of global atrophy (b [95%
confidence interval (CI)], 0.52% [0.84 to 0.20%], 0.94% [1.45 to 0.43%]), cortical atrophy (b [95% CI],
0.75% [1.37 to 0.13%], 1.34% [2.32 to 0.35%]), and subcortical atrophy (b [95% CI], 0.06% [0.02 to
0.16%], 0.13% [0.01 to 0.28%]).
Interpretation: In a study of patients with atherosclerotic disease with 4 years of follow-up, only severe or bilateral
carotid stenosis, and not moderate carotid stenosis and increased CIMT, were associated with progression of brain
atrophy.
ANN NEUROL 2011;70:237–244
O
ver the past decade, evidence has accumulated that
vascular risk factors and vascular disease play an important role in the etiology of dementia and cognitive
impairment.1 Evidence exists that atherosclerotic processes
underlie the association of vascular risk factors and dementia. Previous studies have shown that carotid atherosclerosis
is associated with dementia and its subclinical markers.2–8
This association may be mediated by cerebrovascular disease, such as embolic stroke or cerebral small-vessel disease.7,9,10 The relation between carotid atherosclerosis and
dementia could also be explained by hemodynamic
changes in the cerebral circulation. Recent studies have
shown that patients with carotid atherosclerosis have an
increased risk of cerebral hypoperfusion,11,12 which subsequently may cause brain atrophy and dementia.13–15
Limited evidence exists on the direct relation between
carotid atherosclerosis and brain atrophy. Cross-sectional
studies have shown that increased carotid intima–media
thickness (CIMT) and carotid stenosis are associated with
decreased total brain volume6,8 as well as with ventricular
and sulcal widening.7 However, only 1 cross-sectional study
used quantitative brain volume measurements,6 and no
studies examined the longitudinal association of carotid atherosclerosis with progression of brain atrophy.
View this article online at wileyonlinelibrary.com. DOI: 10.1002/ana.22392
Received Sep 15, 2010, and in revised form Jan 3, 2011. Accepted for publication Jan 28, 2011.
Address correspondence to Dr Geerlings, University Medical Center Utrecht, Julius Center for Health Sciences and Primary Care, Stratenum 6.131, PO
Box 85500, 3508 GA Utrecht, the Netherlands. E-mail: m.geerlings@umcutrecht.nl
Members of the SMART Study Group are listed in the Appendix on page xxx.
From the 1Department of Internal Medicine, VU University Medical Center, Amsterdam; 2Julius Center for Health Sciences and Primary Care, Utrecht;
Department of Neurology and Neurosurgery, Rudolf Magnus Institute of Neuroscience, Utrecht; and 4Department of Radiology, University Medical Center
Utrecht, Utrecht, the Netherlands.
3
C 2011 American Neurological Association
V
237
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The objective of this study was to investigate
whether presence and severity of carotid atherosclerosis
was related to presence and progression of global, cortical, and subcortical atrophy using quantitative brain volume measurements in individuals with symptomatic
atherosclerotic disease.
>210cm/s.19 We classified carotid stenosis into groups of 0 to
50% (no or limited), 50 to 70% (moderate), and >70%
(severe). In addition, we classified carotid stenosis >50% into
unilateral or bilateral stenosis.
Patients and Methods
At baseline and follow-up, the MR investigations were performed on a 1.5T whole-body system (Gyroscan ACS-NT,
Philips Medical Systems, Best, the Netherlands). The protocol
consisted of transversal T1-weighted (repetition time [TR]/
echo time [TE], 235/2 milliseconds), T2-weighted (TR/TE,
2,200/11 milliseconds and 2,200/100 milliseconds), fast
fluid-attenuated inversion recovery (FLAIR; TR/TE/inversion
time [TI], 6000/100/2,000 milliseconds), and inversion recovery (IR; TR/TE/TI, 2,900/22/410 milliseconds) sequences
(field of view [FOV], 230 230mm; matrix size, 180 256; slice thickness, 4.0mm; no gap; 38 slices).16 Next, on
the basis of a localizer MR angiographic slab in the sagittal
plane, a 2-dimensional (2D) phase-contrast section was positioned at the level of the skull base to measure the volume
flow in the internal carotid arteries (ICAs) and the basilar artery (BA).14 The 2D phase-contrast section was positioned
through the ICAs and the BA (TR/TE, 16/9 milliseconds;
flip angle, 7.5 ; FOV, 250 250mm; matrix size, 256 256; slice thickness, 5.0mm; 8 acquired signals; velocity sensitivity, 100cm/s).
We used the T1-weighted gradient-echo, IR sequence and
FLAIR sequence for brain segmentation. The probabilistic segmentation technique has been described elsewhere, and has
been proven to be very reliable, with similarity indices >0.8 for
all segmented tissue and cerebrospinal fluid (CSF) volumes.20,21
The segmentation program distinguishes cortical gray matter,
white matter, sulcal and ventricular CSF, and lesions. The
results of the segmentation analysis were visually checked for
the presence of infarcts and adapted if necessary to make a distinction between white matter lesion (WML) and infarct volume. Total brain volume was calculated by summing the volumes of gray matter, white matter, WMLs, and infarcts. Total
intracranial volume (ICV) was calculated by summing the total
brain volume and the volumes of the sulcal and ventricular
CSF. In 188 patients, the IR and T1-weighted sequences were
missing due to a temporary change in MRI protocol, and the
brain segmentation in these patients was based on the FLAIR
sequence. Intraclass correlation coefficients between the segmentation using all 3 sequences and FLAIR only based on a subset
of 740 patients were 0.995, 0.996, 0.961, 0.996, and 0.985 for
ICV, total brain volume, CSF, ventricular volume, and WML
volume, respectively.
SMART-MR Study
Data were used from the Second Manifestations of ARTerial
disease-Magnetic Resonance (SMART-MR) study, a prospective
cohort study aimed at investigating brain changes on magnetic
resonance imaging (MRI) in 1,309 independently living
patients with symptomatic atherosclerotic disease. Details of the
design and participants have been described elsewhere.16,17 In
brief, between May 2001 and December 2005, all patients
newly referred to the University Medical Center Utrecht with
manifest coronary artery disease, cerebrovascular disease, peripheral arterial disease, or an abdominal aortic aneurysm, and
without MR contraindications, were invited to participate.
Excluded were patients with a terminal disease, those not independent in daily activities, and those referred back to the referring specialist immediately after 1 visit. During a 1-day visit to
our medical center, an MRI of the brain was performed, in
addition to a physical examination, ultrasonography of the carotid arteries, and blood sampling. Risk factors, medical history,
and functioning were assessed with questionnaires that the
patients completed before their visit to the medical center.
Between January 2006 and May 2009, all participants still alive
(n ¼ 1,238) were invited for follow-up measurements, including MRI of the brain, a physical examination, blood sampling,
risk factors, and medical history. In total, 754 of the surviving
cohort (61%) gave written informed consent and participated.
The SMART-MR study was approved by the ethics committee
of our institution, and written informed consent was obtained
from all participants.
Carotid Atherosclerosis
Presence of atherosclerosis in the carotid arteries was assessed
at baseline by measuring CIMT and carotid artery stenosis.
Ultrasonography was performed with a 10MHz linear-array
transducer (ATL Ultramark 9) by well-trained and certified
ultrasound technicians at the Department of Radiology, University Medical Center Utrecht. Mean CIMT (in millimeters)
was calculated for each patient based on 6 far-wall measurements of the left and right common carotid arteries as previously described.18 The degree of the carotid artery stenosis at
both sides was assessed with color Doppler-assisted duplex
scanning. The severity of carotid artery stenosis was evaluated
on the basis of blood flow velocity patterns.19 The greatest
stenosis observed on the right or the left side of the common
or internal carotid artery was taken to determine the severity
of carotid artery disease. Carotid artery stenosis 50% was
defined as peak systolic velocity >150 cm/s, and a carotid artery stenosis 70% was defined as peak systolic velocity
238
Magnetic Resonance Protocol and Brain
Segmentation
Brain Atrophy
The brain volumes that were used for this analysis were total
brain volume, cortical gray matter volume, and ventricular volume as indicators of global, cortical, and subcortical atrophy.
All brain volumes were normalized for ICV.22
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Brain Infarcts, WMLs, Cerebral Blood Flow
At baseline and follow-up, the whole brain was visually searched
for infarcts by an investigator and a neuroradiologist. Discrepancies in rating were re-evaluated in a consensus meeting. Raters
were blinded regarding the history and diagnosis of the patient.
Infarcts were defined as focal hyperintensities on T2-weighted
images of at least 3mm in diameter. Hyperintensities located in
the white matter also had to be hypointense on T1-weighted and
FLAIR images to distinguish them from WMLs. Dilated perivascular spaces were distinguished from infarcts on the basis of their
location, form, and the absence of gliosis. The location, affected
flow territory, and type were scored for every infarct. Brain
infarcts were categorized as cortical infarcts, large subcortical
infarcts, infarcts in the cerebellum and brainstem, and lacunar
infarcts. We defined lacunar infarcts as infarcts sized 3 to 15mm
in diameter and located in the subcortical white matter, thalamus, or basal ganglia. Large subcortical infarcts had the same
characteristics as lacunar infarcts, but were sized >15mm and
were located exclusively in subcortical areas.
Volumes of WMLs obtained with the segmentation program consisted of deep and periventricular WML volumes and
were summed to obtain the total volume of WMLs. WML volumes were normalized for ICV.22
Postprocessing of the flow measurements was performed
by 1 investigator.14,23 The flow through the left and right ICAs
and BA were summed to calculate the total cerebral blood flow
(tCBF; ml/min). We expressed tCBF per 100ml brain parenchymal volume to obtain a measure of cerebral perfusion (pCBF).23
Vascular Risk Factors
During the patient’s baseline visit to the medical center, height
and weight were measured without shoes and heavy clothing,
and the body mass index (BMI) was calculated (kg/m2). Smoking habits and alcohol intake were assessed with questionnaires.
Pack years of smoking were calculated, and alcohol intake was
categorized as never, former, or current. Systolic blood pressure
(SBP; mmHg) and diastolic blood pressure (DBP) were measured twice with a sphygmomanometer, and the average of the 2
measures was calculated. Hypertension was defined as mean
SBP 160mmHg, mean DBP 95mmHg, or self-reported use
of antihypertensive drugs. An overnight fasting venous blood
sample was taken to determine glucose and lipid levels. Diabetes mellitus was defined as use of glucose-lowering agents, a
known history of diabetes or a fasting plasma glucose level
7.0. Hyperlipidemia was defined as total cholesterol
>5.0mmol/l, low-density lipoprotein cholesterol >3.2mmol/l,
or use of lipid-lowering drugs.
Study Sample
Of the 1,309 patients, 19 had no MRI, and 14 had no FLAIR
sequence. In addition, in 44 patients, brain volume data were
missing due to motion or artifacts. As a result, baseline MRI
data were available in 1,232 patients. Of the 1,232 patients,
718 patients participated in the follow-up exam. Of these, 38
had no MRI, and in 17 patients brain volume data were miss-
August 2011
ing due to motion or artifacts. As a result, the analyses for the
prospective analysis were performed in 663 patients.
Data Analysis
Missing data rarely occur completely at random, and a complete case analysis (deletion of all participants with 1 or more
missing values) leads to loss of statistical power and to biased
results.24,25 We therefore used multiple imputation (10 datasets) to address the missing values,26 using the statistical program R (aregImpute; version 2.10.0). Data were analyzed
using SPSS version 17.0 (SPSS Inc., Chicago, IL), by pooling
the 10 inputted datasets. Subject characteristics were calculated
for the baseline SMART-MR cohort (n ¼ 1,232) and for the
SMART-MR sample with follow-up measurements (n ¼ 663).
Linear regression analysis was used to investigate the cross-sectional association of CIMT and carotid stenosis with baseline
relative total brain, cortical gray matter, and ventricular volume. In addition, linear regression analysis and analysis of covariance were used to investigate the prospective association of
baseline carotid atherosclerosis with change in measures of
brain volume by using brain volume measurements at followup as dependent variable and brain volume measurements at
baseline as independent variable. Cross-sectional and prospective analyses were adjusted for age, sex, and follow-up time
(model 1). To examine if the relation between carotid atherosclerosis and brain volume was explained by vascular risk factors, we further adjusted for smoking, alcohol consumption,
BMI, hypertension, diabetes, and hyperlipidemia (model 2).
As presence of large brain infarcts is a strong confounder in
the association of carotid atherosclerosis and brain volume, the
abovementioned analyses were repeated after exclusion of
patients with a history of cerebrovascular disease or with 1 or
more nonlacunar infarcts on MRI. Finally, to investigate
whether reduced pCBF and presence of WMLs and lacunar
infarcts mediate the association of carotid atherosclerosis with
change in brain volume, we additionally adjusted the analyses
for pCBF or for WMLs and lacunar infarcts.
Results
Mean (standard deviation [SD]) age of the total
SMART-MR population (N ¼ 1,232) was 58 (10) years.
Compared with the total SMART-MR population,
patients with follow-up measurements (n ¼ 663) were
younger at baseline, had hypertension and diabetes less
often, had smaller CIMT, and less often had severe carotid stenosis (Table 1). The percentages of missing variables varied between 0 and 15%. Mean (SD) baseline
total brain, cortical gray matter, and ventricular volumes
for the total SMART-MR population were 79 (3), 36
(3), and 2.1 (1.0) %ICV and for the patients with follow-up were 79 (3), 36 (3), and 2.0 (0.8) %ICV.
Cross-sectional linear regression analyses, adjusting
for age and sex, showed that an increase in CIMT of 1
SD (0.31mm) and presence of moderate, severe, or
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TABLE 1: Baseline Patient Characteristics of the Total SMART-MR Population and of the SMART-MR Sample
with Follow-up Measurements
Characteristic
Total SMART-MR
Sample, N 5 1,232
SMART-MR Sample with
Follow-up, n 5 663
Age, yra
58 (10, 25–82)
57 (9, 28–79)
Sex, No. (%) men
983 (80%)
541 (81%)
Coronary heart disease
735 (60%)
412 (62%)
Peripheral arterial disease
268 (22%)
120 (18%)
Cerebrovascular disease
284 (23%)
153 (23%)
Abdominal aortic aneurysm
108 (9%)
39 (6%)
Smoking (pack years)b
19 (0–50)
20 (0–50)
Alcohol use, No. (%) current
924 (75%)
515 (77%)
27 (4, 15–43)
27 (4, 18–39)
Hypertension, No. (%)
640 (52%)
312 (47%)
Diabetes, No. (%)
253 (21%)
106 (16%)
Hyperlipidemia, No. (%)
968 (78%)
522 (79%)
Intima–media thickness, mma
0.94 (0.31, 0.42–4.52)
0.92 (0.29, 0.47–4.02)
Carotid stenosis 50 to 70%, No. (%)
45 (4%)
24 (4%)
Carotid stenosis >70 to 99%, No. (%)
83 (7%)
31 (5%)
Carotid stenosis 100%, No. (%)
52 (4%)
32 (5%)
Bilateral carotid stenosis >50%, No. (%)
52 (4%)
23 (3%)
0.11 (0.03–0.53)
0.09 (0.03–0.40)
Cortical infarcts 1, No. (%)
144 (12%)
74 (11%)
Subcortical infarcts 1, No. (%)
11 (1%)
6 (1%)
Cerebellar infarcts 1, No. (%)
48 (4%)
26 (4%)
Brain stem infarcts 1, No. (%)
35 (3%)
17 (3%)
232 (19%)
114 (17%)
51 (11, 9–92)
52 (10, 19–91)
General characteristics
Vascular disease category, No. (%)
Vascular risk factors
BMI, kg/m
2a
Carotid atherosclerosis
Cerebrovascular pathology
White matter lesion volume, %ICV
b
Lacunar infarcts 1, No. (%)
Parenchymal CBF, ml/min/100ml
a
a
Mean (standard deviation, range).
b
Median (10th–90th percentile).
BMI ¼ body mass index; CBF ¼ cerebral blood flow.
bilateral carotid stenosis were associated with smaller
total brain and cortical gray matter volume (Table 2).
CIMT was also associated with larger ventricular volume.
These associations were independent of cardiovascular
risk factors. When repeating the cross-sectional analyses
in the 663 patients with follow-up data, the results presented in Table 2 were similar (data not shown).
240
After a mean (SD; range) follow-up of 3.9 (0.4; 3.0–
5.8) years, CIMT, moderate carotid stenosis, and unilateral
stenosis were not related to change in brain volume (Fig).
Only severe or bilateral carotid stenosis were related to a
decrease in total brain and cortical gray matter volume and
an increase in ventricular volume. Compared with patients
with no or limited carotid stenosis, the differences (b, 95%
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Muller et al: Brain Atrophy
TABLE 2: Cross-Sectional Relation between Baseline Carotid Atherosclerosis Measures and Baseline Brain
Volume in 1,232 Patients
Modela
Total Brain
Volume, % ICV
Cortical Gray Matter
Volume, % ICV
Ventricular
Volume, % ICV
bb
95% CI
bb
95% CI
bb
95% CI
1
0.29
0.42 to 0.17d
0.33
0.52 to 0.14d
0.07
0.02 to 0.12e
2
0.20
0.33 to 0.08d
0.22
0.42 to 0.03e
0.06
0.01 to 0.11e
1
0.00
—
0.00
—
Moderate,
50 to 70%
0.51
1.15 to 0.14
Severe, >70%
0.89
CIMT, per SD
increasec
Carotid stenosis
0 to 50%, reference
0.00
—
1.15
2.12 to 0.17
e
0.11
0.15 to 0.37
1.27 to 0.51d
1.42
1.99 to 0.84d
0.15
0.00 to 0.30
0.00
—
0.00
—
0.00
—
Moderate, 50
to 70%
0.29
0.93 to 0.34
0.90
1.87 to 0.07
0.07
0.19 to 0.33
Severe, >70%
0.70
1.08 to 0.32d
1.22
1.79 to 0.64d
0.11
0.04 to 0.26
0.00
—
Unilateral >50%
0.75
Bilateral >50%
0 to 50%, reference
2
Carotid stenosis
0 to 50%, reference
0.00
—
1.13 to 0.35
d
1.33
0.92
1.52 to 0.32
d
0.00
—
Unilateral >50%
0.55
Bilateral >50%
0.71
0 to 50%, reference
1
2
0.00
—
1.93 to 0.73
d
0.15
0.01 to 0.30
1.42
2.33 to 0.52
d
0.12
0.13 to 0.36
0.00
—
0.94 to 0.17
e
0.00
—
1.72 to 0.52
d
1.12
1.30 to 0.12
e
0.11
0.05 to 0.26
2.09 to 0.28
e
1.19
0.10
0.15 to 0.34
a
Model 1: adjusted for age and sex; model 2: additionally adjusted for smoking, alcohol consumption, body mass index,
hypertension, diabetes, and hyperlipidemia.
b
b ¼ coefficient of linear regression; an increase of the independent variable by 1 unit is associated with a b increase of brain
volume.
c
SD ¼ 0.31mm.
d
p < 0.005.
e
p < 0.05.
ICV ¼ intracranial volume; CI ¼ confidence interval; CIMT ¼ carotid intima–media thickness; SD ¼ standard deviation.
confidence interval [CI]) in change in total brain, cortical
gray matter, and ventricular volume adjusted for age, sex,
smoking, alcohol consumption, BMI, hypertension, diabetes, hyperlipidemia, and follow-up period were 0.52
(0.84 to 0.20), 0.75 (1.37 to 0.13), and 0.06
(0.02 to 0.16) %ICV for patients with severe stenosis
and 0.94 (1.45 to 0.43), 1.34 (2.32 to 0.35),
and 0.13 (0.01 to 0.28) %ICV for patients with bilateral
stenosis. Exclusion of patients with total occlusion of the
carotid artery (n ¼ 32) did not change our findings (data
not shown). After exclusion of patients with nonlacunar
infarcts on MRI (n ¼ 80) or patients with cerebrovascular
disease (n ¼ 153), the associations of carotid stenosis with
brain volumes did not change (data not shown).
August 2011
To examine if reduced pCBF mediated the association of severe or bilateral carotid stenosis with progression of brain atrophy, we additionally adjusted the regression analyses for pCBF. The association of severe or
bilateral stenosis with a decrease in total brain and cortical gray matter volume and an increase in ventricular volume were partly explained by reduced pCBF; bs (95%
CI) for severe carotid stenosis were 0.47 (0.72 to
0.21), 0.46 (1.05 to 0.12), and 0.06 (0.00 to 0.13)
%ICV and for bilateral stenosis were 0.92 (1.33 to
0.50), 0.78 (1.80 to 0.23), and 0.15 (0.03 to 0.27)
%ICV. Adjustment for WMLs and lacunar infarcts further attenuated the association of severe or bilateral carotid stenosis with change in brain volumes; bs (95%
241
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Discussion
FIGURE: Longitudinal relation between measures of carotid
atherosclerosis and change in total brain volume (A), cortical
gray matter volume (B), and ventricular volume (C). Bars
represent the mean (standard error) change in brain volume
after 3.9 years of follow-up. Carotid intima–media thickness
(CIMT) tertile 1, 0.47 to 0.78mm; tertile 2, 0.78 to 0.97mm;
tertile 3, 0.97 to 4.02mm. *p < 0.05; **p < 0.005. ICV 5 intracranial volume.
CI) for severe carotid stenosis were 0.42 (0.67 to
0.16), 0.36 (0.95 to 0.22), and 0.05 (0.02 to
0.12) %ICV and for bilateral stenosis were 0.84
(1.26 to 0.41), 0.67 (1.68 to 0.35), and 0.14
(0.01 to 0.26) %ICV.
Finally, post hoc analysis excluding patients with suspected cognitive impairment (Mini Mental State Examination <24) did not change the results (data not shown).
242
In a population with symptomatic atherosclerotic disease,
we observed that increased CIMT and carotid stenosis
were significantly associated with decreased relative total
brain and cortical gray matter volume. However, our
prospective findings showed that only severe or bilateral
carotid stenosis, but not increased CIMT or moderate
stenosis, were related to progression of global, cortical,
and subcortical atrophy over a 4-year period of patient
follow-up. This relation was independent of age, sex, and
vascular risk factors, such as hypertension, hyperlipidemia, and diabetes, and was partly explained by reduced
cerebral perfusion and cerebral small-vessel disease.
Our cross-sectional findings are in agreement with
previous studies such as the Cardiovascular Health Study
and the Framingham Study.6,7 These large-scale population-based studies reported that increased CIMT as well
as moderate and severe carotid stenosis were associated
with sulcal and ventricular widening7 and with smaller
total brain volume.6 To our knowledge, this is the first
study that also examined the prospective relation of
measures of carotid atherosclerosis with progression of
brain atrophy. An explanation of the disparity between
the cross-sectional and prospective findings could be that
carotid stenosis and CIMT reflect different stages and severity of the atherosclerotic process.18,19 Carotid stenosis
and plaques are irreversible focal manifestations of atherosclerosis, whereas increased CIMT represents mainly hypertensive medial hypertrophy.27 In fact, studies have
shown that CIMT could be reduced by antihypertensive
and lipid-lowering treatment.28,29 However, because
CIMT has proven to be a strong predictor of future cardiovascular events,30 it is unlikely that treatment could
have explained the discrepancies between the cross-sectional and prospective findings. It is, however, conceivable that compared with severe or bilateral carotid stenosis, increased CIMT or moderate stenosis may require a
longer follow-up time than 4 years to achieve similar
effects on progression of brain atrophy. The disparity
between the cross-sectional and prospective findings
could not be explained by a healthy survivor effect,
because the cross-sectional results were similar within the
663 patients with complete follow-up. Another explanation for the cross-sectional results could be that carotid
atherosclerosis and brain atrophy are independent processes with common elements in the causal pathway,
because many of the contributory factors in atherosclerosis have emerged as potential contributors in dementia.31
Common pathophysiological elements could include
hypertension, hyperlipidemia, inflammation, or genetic
factors.31 Although adjustment for cardiovascular risk
Volume 70, No. 2
Muller et al: Brain Atrophy
factors did not change the observed associations between
carotid atherosclerosis and brain atrophy, this explanation
cannot be excluded.
Several mechanisms may explain an association
between severe or bilateral carotid stenosis and progression of brain atrophy. Cerebrovascular disease may mediate the association between atherosclerosis and atrophy.
Because excluding individuals with large brain infarcts on
MRI did not affect the estimate, it is not likely that the
association with brain atrophy is explained by cortical or
large subcortical infarcts. However, adjusting the analyses
for presence of cerebral small-vessel disease, such as
WMLs and lacunar infarcts, partly mediated the association between atherosclerosis and progression of brain atrophy. Also, severe or bilateral stenosis may induce cerebral hypoperfusion leading to cerebral hypoxia especially
in individuals with reduced or impaired collateral circulation.32 A good collateral circulation can generate normal
cerebral hemodynamics in patients with carotid stenosis.
When collaterals are not adequate, the perfusion pressure
distal to the lesion begins to fall, which might trigger regional brain microcirculatory disturbances that can evolve
into a neurodegenerative process, eventually leading to
brain atrophy.13,32 The cortical gray matter is especially
vulnerable to hypoperfusion, because the gray matter has
higher oxygen and glucose requirements than the white
matter.33 This is confirmed by our findings that adjusting for pCBF, as an indicator of cerebral perfusion, only
attenuated the association of carotid stenosis with progression of cortical atrophy. Future studies are needed,
using measures of flow in the circle of Willis and cerebral
perfusion at brain tissue level, to further elucidate the
relation between carotid artery disease, collateral circulation, cerebral hypoperfusion, and neurodegeneration.34
Strengths of our study are the large number of
patients investigated and the volumetric assessment of
measures of brain atrophy, which made it possible to
obtain precise estimates of progression of brain atrophy,
and resulted in a large power to detect associations. Volumetric segmentation methods have several advantages
compared with visual rating and 2D assessment of brain
atrophy. Contrary to visual rating scales, volumetric assessments are not impeded by ceiling effects. Furthermore,
volumetric segmentation methods are more precise, and
therefore more likely to detect small differences in brain
volumes that cannot be detected by visual rating and 2D
techniques. In addition, the segmentation of different
brain tissue types and CSF spaces allowed us to differentiate between cortical and subcortical brain atrophy. Finally,
the extensive information on markers of cerebrovascular
pathology and cardiovascular risk factors allowed us to
investigate whether the association between carotid atheroAugust 2011
sclerosis and brain atrophy was independent of these possible confounders or modifiers. Our interpretation of the
results may be limited by a few factors. First, individuals
who participated in the follow-up examination represent a
relatively healthy group. If anything, however, this may
have led to an underestimation of the true association.
Second, because the majority of our study sample consisted of male patients with atherosclerotic disease, we do
not know to what extent our results also apply to women
or can be generalized to the general population. Although
we adjusted for vascular risk and disease, our population
consisted of patients with manifest arterial disease, and it
is thus still possible that other factors than atherosclerosis
may explain our findings, such as heart failure or hypoxia,
which may have occurred during myocardial infarction or
cardiovascular interventions. Nonetheless, our cross-sectional findings were similar to those found in populationbased samples.6,7
In summary, in this prospective study in patients
with symptomatic atherosclerotic disease, only high grade
or bilateral carotid artery narrowing led to progression of
brain atrophy.
Acknowledgment
Supported by a program grant from the Netherlands
Organization for Scientific Research-Medical Sciences
(NWO-MW: project No. 904-65-095) and a grant from
the Netherlands Organization for Scientific Research
(NWO: project No. 917-66-311; M.I.G.).
Potential Conflicts of Interest
A.A.: grants, Netherlands Heart Foundation, Netherlands
Brain Foundation, Thrombosis Foundation Holland,
Netherlands Organization for Scientific Research, and
Netherlands Organization for Health Research and Development; consulting fee/honorarium, Boehringer Ingelheim; other, a principal investigator of ESPRIT, the
European/Australian Stroke Prevention in Reversible
Ischemia Trial, a trial that was run independently of any
pharmaceutical company; after completion and full
analysis of ESPRIT, the study group accepted financial
support from Boehringer Ingelheim for post hoc exploratory analyses of the ESPRIT trial data; for this purpose a
contract was signed ensuring complete scientific freedom.
Appendix
We thank the members of the SMART Study Group of
University Medical Center Utrecht: A. Algra, MD, PhD,
Julius Center for Health Sciences and Primary Care,
Rudolf Magnus Institute for Neurosciences, Department
243
ANNALS
of Neurology
of Neurology; P. A. Doevendans, MD, PhD, Department
of Cardiology; Y. van der Graaf, MD, PhD, D. E.
Grobbee, MD, PhD, and G. E. H. M. Rutten, MD, PhD,
Julius Center for Health Sciences and Primary Care; L. J.
Kappelle, MD, PhD, Department of Neurology; W. P. T.
M. Mali, MD, PhD, Department of Radiology; F. L. Moll,
MD, PhD, Department of Vascular Surgery; and F. L. J.
Visseren, MD, PhD, Department of Vascular Medicine.
References
1.
Viswanathan A, Rocca WA, Tzourio C. Vascular risk factors and dementia: how to move forward? Neurology 2009;72:368–374.
2.
Johnston SC, O’Meara ES, Manolio TA, et al. Cognitive impairment and decline are associated with carotid artery disease in
patients without clinically evident cerebrovascular disease. Ann Intern Med 2004;140:237–247.
3.
Muller M, Grobbee DE, Aleman A, et al. Cardiovascular disease
and cognitive performance in middle-aged and elderly men. Atherosclerosis 2007;190:143–149.
4.
Rice Wendell C, Zonderman AB, Metter EJ, et al. Carotid intimal
medial thickness predicts cognitive decline among adults without
clinical vascular disease. Stroke 2009;40:3180–3185.
5.
van Oijen M, de Jong FJ, Witteman JC, et al. Atherosclerosis and
risk for dementia. Ann Neurol 2007;61:403–410.
6.
Romero JR, Beiser A, Seshadri S, et al. Carotid artery atherosclerosis, MRI indices of brain ischemia, aging, and cognitive impairment: the Framingham study. Stroke 2009;40:1590–1596.
7.
Manolio TA, Burke GL, O’Leary DH, et al. Relationships of
cerebral MRI findings to ultrasonographic carotid atherosclerosis
in older adults: the Cardiovascular Health Study. CHS Collaborative Research Group. Arterioscler Thromb Vasc Biol 1999;19:
356–365.
16.
Geerlings MI, Appelman AP, Vincken KL, et al. Brain volumes and
cerebrovascular lesions on MRI in patients with atherosclerotic disease. The SMART-MR study. Atherosclerosis 2010;210:130–136.
17.
Simons PC, Algra A, van de Laak MF, et al. Second manifestations
of ARTerial disease (SMART) study: rationale and design. Eur J
Epidemiol 1999;15:773–781.
18.
Simons PC, Algra A, Bots ML, et al. Common carotid intimamedia thickness and arterial stiffness: indicators of cardiovascular
risk in high-risk patients. The SMART study (Second Manifestations
of ARTerial disease). Circulation 1999;100:951–957.
19.
Elgersma OE, van LM, Buijs PC, et al. Changes over time in optimal duplex threshold for the identification of patients eligible for
carotid endarterectomy. Stroke 1998;29:2352–2356.
20.
Anbeek P, Vincken KL, van Bochove GS, et al. Probabilistic segmentation of brain tissue in MR imaging. Neuroimage 2005;27:
795–804.
21.
Muller M, Appelman AP, van der Graaf Y, et al. Brain atrophy and
cognition: interaction with cerebrovascular pathology? Neurobiol
Aging 2009; June 9 [Epub ahead of print].
22.
Hachinski V, Iadecola C, Petersen RC, et al. National Institute of
Neurological Disorders and Stroke-Canadian Stroke Network vascular cognitive impairment harmonization standards. Stroke 2006;
37:2220–2241.
23.
Appelman AP, van der Graaf Y, Vincken KL, et al. Total cerebral
blood flow, white matter lesions and brain atrophy: the SMARTMR study. J Cereb Blood Flow Metab 2008;28:633–639.
24.
van der Heijden GJ, Donders AR, Stijnen T, et al. Imputation of
missing values is superior to complete case analysis and the missing-indicator method in multivariable diagnostic research: a clinical example. J Clin Epidemiol 2006;59:1102–1109.
25.
Donders AR, van der Heijden GJ, Stijnen T, et al. Review: a gentle
introduction to imputation of missing values. J Clin Epidemiol
2006;59:1087–1091.
26.
Rubin DB, Schenker N. Multiple imputation in health-care databases: an overview and some applications. Stat Med 1991;10:
585–598.
8.
Kin T, Yamano S, Sakurai R, et al. Carotid atherosclerosis is
associated with brain atrophy in Japanese elders. Gerontology
2007;53:1–6.
27.
Spence JD. Measurement of intima-media thickness vs. carotid
plaque: uses in patient care, genetic research and evaluation of
new therapies. Int J Stroke 2006;1:216–221.
9.
Barnett HJ, Gunton RW, Eliasziw M, et al. Causes and severity of
ischemic stroke in patients with internal carotid artery stenosis.
JAMA 2000;283:1429–1436.
28.
Kang S, Wu Y, Li X. Effects of statin therapy on the progression of
carotid atherosclerosis: a systematic review and meta-analysis.
Atherosclerosis 2004;177:433–442.
10.
Pico F, Dufouil C, Levy C, et al. Longitudinal study of carotid atherosclerosis and white matter hyperintensities: the EVA-MRI
cohort. Cerebrovasc Dis 2002;14:109–115.
29.
Wang JG, Staessen JA, Li Y, et al. Carotid intima-media thickness
and antihypertensive treatment: a meta-analysis of randomized
controlled trials. Stroke 2006;37:1933–1940.
11.
Sojkova J, Najjar SS, Beason-Held LL, et al. Intima-media thickness
and regional cerebral blood flow in older adults. Stroke 2010;41:
273–279.
30.
12.
Bokkers RP, van der Worp HB, Mali WP, et al. Noninvasive MR
imaging of cerebral perfusion in patients with a carotid artery stenosis. Neurology 2009;73:869–875.
Lorenz MW, Markus HS, Bots ML, et al. Prediction of clinical cardiovascular events with carotid intima-media thickness: a systematic
review and meta-analysis. Circulation 2007;115:459–467.
31.
de la Torre JC. Critically attained threshold of cerebral hypoperfusion: the CATCH hypothesis of Alzheimer’s pathogenesis. Neurobiol Aging 2000;21:331–342.
Casserly I, Topol E. Convergence of atherosclerosis and Alzheimer’s disease: inflammation, cholesterol, and misfolded proteins.
Lancet 2004;363:1139–1146.
32.
Muller M, van der Graaf Y, Visseren FL, et al. Blood pressure, cerebral blood flow, and brain volumes. The SMART-MR study.
J Hypertens 2010;28:1498–1505.
Vernieri F, Pasqualetti P, Matteis M, et al. Effect of collateral
blood flow and cerebral vasomotor reactivity on the outcome of
carotid artery occlusion. Stroke 2001;32:1552–1558.
33.
Kirkness CJ. Cerebral blood flow monitoring in clinical practice.
AACN Clin Issues 2005;16:476–487.
34.
van Laar PJ, van der Grond J, Mali WP, et al. Magnetic resonance
evaluation of the cerebral circulation in obstructive arterial disease. Cerebrovasc Dis 2006;21:297–306.
13.
14.
15.
244
Poels MM, Ikram MA, Vernooij MW, et al. Total cerebral blood
flow in relation to cognitive function: the Rotterdam Scan Study.
J Cereb Blood Flow Metab 2008;28:1652–1655.
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