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Severity of Dilated Virchow-Robin Spaces Is Associated With Age, Blood Pressure, and MRI Markers of Small Vessel Disease

A Population-Based Study
Originally published 2010;41:2483–2490


Background and Purpose—Little is known about the risk factors of dilated Virchow-Robin spaces (dVRS) and their relation with other markers of brain small vessel disease. We investigated both issues in a large population-based sample of elderly individuals.

Methods—Severity of dVRS was semiquantitatively graded in both white matter and basal ganglia using high-resolution 3-dimensional MRI images taken from 1818 stroke- and dementia-free subjects enrolled in the Three-City Dijon MRI study. Multinomial logistic regression models were used to model the association of cardiovascular risk factors, APOE genotype, brain atrophy, and MRI markers of small vessel disease with the degree of dVRS.

Results—Severity of dVRS was found to be strongly associated with age in both basal ganglia (degree 4 versus 1: OR, 2.1; 95% CI, 1.4 to 3.2) and white matter (OR, 1.5; 95% CI, 1.2 to 1.9). The proportion of hypertensive subjects increased with the degrees of dVRS in both basal ganglia (P=0.02) and white matter (P=0.048). Men presented a higher risk of severe dVRS in basal ganglia than women, particularly degree 4 (OR, 6.0; 95% CI, 1.8 to 19.8). The degree of dVRS was associated with the volume of white matter hyperintensities and the prevalence of lacunes, but not with brain atrophy.

Conclusion—In this large cohort study of elderly subjects, the degree of dVRS appears independently associated with age, hypertension, volume of white matter hyperintensities, and lacunar infarctions. dVRS should be considered as another MRI marker of cerebral small vessel disease in the elderly with regional variations in their severity.

Virchow-Robin spaces are virtual spaces between the cerebral vessel wall and the brain parenchyma that are separated by the leptomeninges.1 They can dilate with accumulation of the interstitial fluid2,3 and become detectable in vivo by MRI and postmortem by autopsy.4

Because the expansion of Virchow-Robin spaces seldom leads to tissue damage in the surrounding parenchyma, dilated Virchow-Robin spaces (dVRS) have been long regarded as benign and normal variants and have been subject to little investigation.5,6 However, there is accumulating evidence that dVRS may be related to cerebral small vessel disease. First, the dilation of Virchow-Robin spaces is a nearly constant feature described in pathological studies of Binswanger encephalopathy or leukoaraiosis, conditions driven mainly by alterations of small cerebral arteries.5,7 Second, in a recent study of patients with lacunar stroke, diffuse blood–brain barrier leakage was detected in the white matter (WM) and was found to be related to the number of dVRS.8 Third, in a postmortem study of patients with Alzheimer disease, dVRS were found to be associated with amyloid angiopathy that is presumably responsible for perivascular deposits of β-amyloid substance decreasing interstitial fluid drainage.9 Fourth, in patients with cerebral autosomal-dominant arteriolopathy with subcortical infarcts and leukoencephalopathy, a monogenic disease responsible for severe ultrastructural changes in the wall of cerebral perforating arteries, dVRS were found to be highly prevalent and characteristic as markers of the disease in specific cerebral areas.10

Although these data strongly support the link between dVRS and cerebral small vessel disease, little is known on the peculiar risk factors of dVRS in the general population. We identified dVRS using high-resolution 3-dimensional MRI in a large population-based elderly sample and investigated their risk factors as well as their association with classical MRI markers of ischemic small vessel disease.

Methods and Materials


The Three-City (3C) study is a cohort study conducted in 3 cities in France (Bordeaux, Dijon, Montpellier) designed to estimate the risk of dementia and cognitive impairment attributable to vascular risk factors. A sample of noninstitutionalized subjects aged ≥65 years was randomly selected from the electoral rolls of each city. Among the 4931 individuals recruited in Dijon, those <80 years of age and enrolled between June 1999 and September 2000 (n=2763) were proposed to undergo a cerebral MRI examination. The detailed description of the study protocol, approved by the Ethical Committee of the University Hospital of Kremlin-Bicêtre, has been previously reported.11 Each participant signed an informed consent statement.

The exclusion criteria for the MRI examination were the following: cardiac pacemaker; valvular prosthesis; other internal electric/magnetic devices; history of neurosurgery/aneurysm; claustrophobia; and presence of metal fragments (in the eyes, brain, or spinal cord). A total of 2285 individuals (83%) agreed to participate, but due to financial limitations, only 1924 brain MRIs were actually performed, of which 48 were discarded due to motion artifacts. Individuals with dementia, brain tumors, or self-reported history of stroke were further excluded (n=58), and thus the final sample was composed of 1818 subjects.

Brain MRI

MRI acquisition was performed on 1.5-Tesla Magnetom (Siemens, Erlangen, Germany). A 3-dimensional high-resolution T1-weighted brain volume was acquired using a 3-dimensional inversion recovery fast spoiled-gradient echo sequence (repetition time=97 ms; echo time=4 ms; inversion time=600 ms; coronal acquisition). The axially reoriented 3-dimensional volume matrix size was 256×192×256 with a 1.0×0.98×0.98-mm3 voxel size. There were 124 slices covering the whole brain. T2- and proton density-weighted brain volumes were acquired using a 2-dimensional dual spin echo sequence with 2 echo times (repetition time=4400 ms; echo time 1=16 ms; echo time 2=98 ms). T2 and proton density acquisitions consisted of 35 axial slices 3.5 mm thick (0.5-mm between-slice spacing) having a 256×256 matrix size and a 0.98×0.98 mm2 in-plane resolution.

Rating of dVRS

High-resolution 3-dimensional MRIs were used for the assessment of dVRS. For each case, MRI analysis was performed with T1-weighted images at 2× magnification on a 27-inch screen. Using multiplanar reformatting, the characteristics of lesions were visualized simultaneously in axial, coronal, and sagittal planes. T2- and proton density-weighted images were analyzed to confirm that the signal of the lesion corresponded to that of cerebrospinal fluid (CSF).

dVRS were defined as CSF-like signal lesions (hypointense on T1 and hyperintense on T2) of round, ovoid, or linear shape with a maximum diameter <3 mm,12 having smooth delineated contours, and located in areas supplied by perforating arteries. For lesions fulfilling the same criteria except for their diameter that was ≥3 mm, further efforts were needed to differentiate them from infarcts using multiplanar reformatting. Only those with a typical vascular shape and following the orientation of perforating vessels (including cystic lesions with an extension of vascular shape) were then regarded as dVRS.1

For each subject, all 124 axially oriented T1-weighted slices were examined to evaluate the global burden of dVRS and to identify the slice containing the greatest number of dVRS in both basal ganglia (BG) and WM. When lesions were difficult to categorize, coregistered T2 and proton density images were used to check that their signal was identical to that of CSF. In BG, dVRS were then rated according to a 4-level severity score in the slice containing the greatest number of dVRS. The degrees of dVRS were defined as follows: degree 1 when there was <5 dVRS; degree 2 when there was between 5 and 10 dVRS; degree 3 when there was >10 dVRS but still numerable; and degree 4 when an innumerable number of dVRS result in a cribriform change in basal ganglia (Figure 1). In the white matter, dVRS were scored degree 1 when there was <10 dVRS in the total white matter; degree 2 when there was >10 dVRS in the total white matter and <10 in the slice containing the greatest number of dVRS; degree 3 when there was between 10 and 20 dVRS in the slice containing the greatest number of dVRS; and degree 4 when there was >20 dVRS in the slice containing the greatest number of dVRS (Figure 2). This rating scheme was adopted after testing different visual rating methods including those reported in the literature on a subset of MRI data from the first 150 subjects of the cohort and after performing step-by-step multiple rectifications. One experienced reader (Y.-C.Z.) blind to all clinical data analyzed all images. The intrarater agreement for the rating of dVRS was assessed on a random sample of 100 individuals with a 1-month interval between the first and second readings. The κ statistics of intrarater agreement was 0.77 for BG and 0.75 for WM, indicating good reliability.

Figure 1. Severity score of dVRS in BG.

Figure 2. Severity scores of dVRS in WM.

Other MRI Parameters

The volume of white matter hyperintensities (WMH) was measured with a validated automated imaging processing method13 and analyzed as a continuous variable. Morphological parameters (center of mass coordinates, Euclidian distance to the ventricular system, principal axes dimension) were computed for each WMH. When their distance from the ventricular system was <10 mm, WMH were labeled as periventricular; otherwise they were labeled as deep.

Gray matter, white matter, and CSF volumes were estimated with voxel-based morphometry methods detailed elsewhere.14 In each subject, these volumes were computed as the integral of the voxel intensities in the corresponding modulated tissue image. The total intracranial volume was computed as the sum of the gray matter, WM, and CSF volumes and brain parenchymal fraction was determined as the ratio of brain tissue volume to total intracranial volume.

Lacunar infarcts were rated on T1, T2- and proton density-weighted images by the same examiner (Y.-C.Z.). Lacunar infarcts were defined as focal lesions from 3 to 15 mm in size having the same signal characteristics as CSF on all sequences situated in BG or WM and were discriminated from dilated Virchow-Robin spaces using the previously mentioned criteria.

Risk Factor Assessment

Sociodemographic and medical data were collected at the subject’s residence during face-to-face interviews by trained psychologists. Subjects were considered to have a history of ischemic heart disease if a history of myocardial infarction, bypass cardiac surgery, or angioplasty was reported. Diabetes mellitus was considered present when antidiabetic drugs were taken or when fasting blood glucose was ≥7 mmol/L. Hypercholesterolemia was defined as total cholesterol ≥6.2 mmol/L or lipid-lowering drugs were taken. Systolic and diastolic blood pressures were measured twice, each taken at least 5 minutes apart with an interval for rest in a seated position. The mean of both measures was used. Hypertension was defined by high blood pressure (systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg) or by the use of antihypertensive drugs. Smoking status was categorized as never, former, and current. Polymorphism of the APOE gene was assessed using a procedure described elsewhere and the presence of allele 4 of APOE was considered.15 Medications taken regularly during the month preceding the interview were recorded from prescription forms and coded according to the French translation of the Anatomic Therapeutical Chemical Classification of the World Health Organization.

Statistical Analyses

The descriptive statistics on the baseline potential risk factors are presented as well as their crude distribution according to dVRS degrees. For multivariate cross-sectional analyses, multinomial logistic regression models were computed with dVRS rated with a 4-degree score as the dependent variable and with degree 1 as the reference category. Each response category (the probability of having dVRS of degree 2, 3, or 4) was contrasted against the reference category. Separate analyses were performed to model the dVRS load in BG and in WM with control for age, gender, and total intracranial volume. The same approach was used to examine the relationships between the severity of dVRS and the other MRI markers; in this case, multivariate models also included hypertension. Because there were only 24 individuals with degree 4 of dVRS in the BG, crude analyses were also performed and compared with multivariate analyses to evaluate the risk of overfitting. Because they gave similar results (data not shown), only multivariate models are presented. All probability values were 2-tailed; P≤0.05 was considered to be statistically significant. All analyses were performed using SAS Version 9.1 (SAS Institute, Inc, Cary, NC).


Baseline characteristics of the study sample are shown in Table 1. The mean age was 72.5 years (SD=4.1) and 706 (38.8%) participants were male. Eighty-eight percent of participants had a dVRS of degree 1 or 2 in BG and, in this brain area, degree 4 was observed in 24 (1.3%) subjects. Within the WM, 77% of the individuals had dVRS of degrees 1 or 2, and 94 subjects (5.2%) had the highest degree.

Table 1. Baseline Characteristics of the Study Participants (N=1818)

CharacteristicsMean (SD) or Percent (no.)
*Systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg or use antihypertensive medication.
†Glycemia ≥7 mmol/L or use of antidiabetic treatment.
‡Total cholesterol ≥6.2 mmol/L or use of lipid-lowering drugs.
§History of myocardial infarction, bypass cardiac surgery, or angioplasty.
Age, years72.5 (4.1)
Male gender38.8 (706)
Current smoker5.9 (108)
Hypertension*76.8 (1396)
Diabetes mellitus8.3 (150)
Hypercholesterolemia56.8 (1025)
Ischemic heart disease§8.2 (149)
Antihypertensive drug use42.7 (777)
Apolipoprotein E 4 allele carrier22.0 (396)
dVRS in BG
    Degree 153.6 (976)
    Degree 235.3 (641)
    Degree 39.7 (177)
    Degree 41.3 (24)
dVRS in WM
    Degree 123.6 (429)
    Degree 253.4 (970)
    Degree 317.9 (325)
    Degree 45.2 (94)

Risk Factors Associated With the Severity of dVRS

The crude distribution of potential risk factors according to dVRS degree and their associations with dVRS in BG and WM are shown in Tables 2 and 3, respectively. Mean age increased with dVRS degree in both brain locations (Table 2); each SD increase in age was associated with a higher odds of having higher degrees of dVRS, in particular degree 4 (odds for degree 4 dVRS in BG: OR, 2.1; 95% CI, 1.4 to 3.2; in WM: OR, 1.5; 95% CI, 1.2 to 1.9) as compared with degree 1. Gender was not associated with the severity of dVRS in WM (P=0.53; Table 3), but in BG, men had a higher risk of presenting severe dVRS, particularly degree 4 (OR, 6.0; 95% CI, 1.8 to 19.8; Table 3).

Table 2. Crude Distribution of Potential Risk Factors Across the Degrees of dVRS

dVRS in BGdVRS in WM
Degree 1 (N=976)Degree 2 (N=641)Degree 3 (N=177)Degree 4 (N=24)Degree 1 (N=429)Degree 2 (N=970)Degree 3 (N=325)Degree 4 (N=94)
All data are presented as percentage (no.) unless otherwise indicated.
*Systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg or use of antihypertensive medication.
†Glycemia ≥7 mmol/L or use of antidiabetic treatment.
‡Total cholesterol ≥6.2 mmol/L or use of lipid-lowering drugs.
§History of myocardial infarction, bypass cardiac surgery, or angioplasty.
Age, mean years (SD)71.7 (4.0)73.0 (4.2)74.2 (4.0)75.0 (3.4)72.2 (4.2)72.4 (4.1)72.7 (4.2)73.8 (4.1)
Male gender36.5 (356)37.8 (242)50.3 (89)79.2 (19)33.6 (144)39.5 (383)42.2 (137)44.7 (42)
Current smoker5.0 (49)7.0 (45)6.8 (12)8.3 (2)5.8 (25)5.7 (55)7.4 (24)4.3 (4)
Hypertension*72.6 (709)81.0 (519)83.1 (147)87.5 (21)74.8 (321)75.2 (729)82.5 (268)83.0 (78)
Diabetes mellitus7.5 (73)9.1 (58)10.9 (19)0.0 (0)9.5 (40)7.6 (73)8.6 (28)9.6 (9)
Hypercholesterolemia58.6 (568)55.0 (350)53.4 (94)54.2 (13)64.2 (272)54.4 (525)53.6 (173)58.5 (55)
Ischemic heart diseases§7.2 (70)9.2 (59)8.5 (15)20.8 (5)8.4 (36)7.9 (77)8.6 (28)8.5 (8)
Antihypertensive drug use36.5 (356)48.5 (311)53.1 (94)66.7 (16)39.9 (171)41.0 (398)48.3 (157)54.3 (51)
APOE 4 carrier22.2 (215)21.9 (139)20.5 (36)25.0 (6)23.9 (101)21.5 (207)20.7 (67)22.3 (21)

Table 3. Associations Between Potential Risk Factors and the Degrees of dVRS

dVRS in BGdVRS in WM
OR (95% CI)*OR (95% CI)*
Degree 2 Versus 1Degree 3 Versus 1Degree 4 Versus 1P*Degree 2 Versus 1Degree 3 Versus 1Degree 4 Versus 1P*
P values correspond to the overall relationship between each variable and the different degrees of dVRS.
*Models of multinomial logistic regression adjusted on age, gender, and total intracranial volume. In each model, dVRS in BG or dVRS in WM was considered as the dependent variable categorized in 4 degrees (the reference being the first degree).
†For continuous variables, the OR estimates the association related to an increase of 1 SD.
Age1.4 (1.3–1.6)1.9 (1.6–2.2)2.1 (1.4–3.2)<0.00011.1 (0.9–1.2)1.1 (1.0–1.3)1.5 (1.2–1.9)0.005
Male gender0.9 (0.7–1.2)2.0 (1.3–3.0)6.0 (1.8–19.8)0.00021.2 (0.9–1.7)1.3 (0.9–1.9)1.2 (0.7–2.1)0.53
Current smoker1.4 (0.9–2.2)1.5 (0.7–3.0)1.4 (0.3–7.2)0.640.8 (0.5–1.4)1.1 (0.6–2.1)0.7 (0.2–2.3)0.27
Hypertension1.4 (1.1–1.9)1.4 (0.9–2.2)2.4 (0.6–10.5)0.021.0 (0.7–1.3)1.5 (1.0–2.2)1.4 (0.8–2.5)0.048
Diabetes mellitus1.2 (0.8–1.8)1.4 (0.8–2.5)NE0.590.8 (0.5–1.3)0.9 (0.6–1.6)1.0 (0.5–2.3)0.80
Hypercholesterolemia0.9 (0.8–1.2)0.9 (0.7–1.3)1.5 (0.6–3.6)0.680.7 (0.6–0.9)0.7 (0.5–0.9)0.9 (0.6–1.4)0.04
Ischemic heart disease1.2 (0.8–1.7)0.9 (0.5–1.6)2.3 (0.8–6.7)0.350.9 (0.6–1.4)0.9 (0.5–1.6)0.7 (0.3–1.7)0.91
Antihypertensive drug use1.5 (1.2–1.9)1.7 (1.2–2.4)3.5 (1.4–8.7)<0.00011.1 (0.9–1.4)1.5 (1.1–2.0)1.7 (1.1–2.7)0.02
APOE 4 carrier1.0 (0.8–1.3)0.9 (0.6–1.3)1.0 (0.4–2.7)0.930.8 (0.6–1.1)0.8 (0.6–1.1)0.9 (0.5–1.6)0.52

The proportion of hypertensive individuals increased with the degree of dVRS; compared with normotensive subjects, hypertensive subjects had higher odds of having dVRS of higher degrees both in BG (P=0.02; Table 3) and in WM (P=0.048; Table 3). Antihypertensive drug use was also found to be associated with the severity of dVRS regardless of the brain location, although the odds of having dVRS of degree 4 was apparently twice as great in BG (OR, 3.5; 95% CI, 1.4 to 8.7; Table 3) than in WM (OR, 1.7; 95% CI, 1.1 to 2.7; Table 3). When hypertension and antihypertensive medications were considered separately and entered in the same regression model, only antihypertensive medications remained associated with the severity of dVRS both in BG (P=0.0001) and WM (P=0.03). We also observed that hypercholesterolemia was inversely associated with dVRS degrees in WM (P=0.04; Table 3), but no significant relationship was observed in BG (P=0.68; Table 3). Finally, smoking status, diabetes, history of ischemic heart disease, or APOE genotype was not associated with the severity of dVRS.

Relationships Between the Severity of dVRS and the Other MRI Markers

Mean (SD) total volume of WMH was 5.5 (5.0) cm3, of which 4.0 (4.2) cm3 was in the periventricular region and 1.5 (1.3) cm3 in the deep region. The mean brain parenchymal fraction (SD) was 0.72 (0.03). Lacunar infarctions were present in 121 (6.8%) participants.

Tables 4 and 5 show the distribution of these MRI markers across the different dVRS degrees and their associations with dVRS in BG and in WM. The mean WMH volume was found to significantly increase with dVRS degrees (Table 3). For each SD increase in WMH volume, the odds of having dVRS of degree 2, 3, or 4 (versus degree 1) was 2 to 3 times higher for BG than for WM (eg, odds of having dVRS of degree 4 in BG: OR, 3.2; 95% CI, 2.5 to 4.1; in WM: OR, 1.2; 95% CI, 1.0 to 1.4). In the analyses by type of WMH, we observed that higher deep WMH volumes were associated with higher degrees of dVRS regardless of the location, whereas periventricular WMH volumes were only related to dVRS in BG (P<0.0001).

Table 4. Crude Distribution of MRI Markers Across the Degrees of dVRS

dVRS in BGdVRS in WM
Degree 1 (N=976)Degree 2 (N=641)Degree 3 (N=177)Degree 4 (N=24)Degree 1 (N=429)Degree 2 (N=970)Degree 3 (N=325)Degree 4 (N=94)
All data are presented as mean (SD) unless otherwise indicated.
PWMH indicates periventricular WMH; DWMH, deep WMH; BPF, brain parenchymal fraction (ratio of brain tissue volume to intracranial volume).
Total WMH volume, cm34.4 (3.8)6.0 (5.3)8.9 (6.6)14.4 (7.9)5.5 (6.3)5.3 (4.4)5.8 (4.4)7.5 (6.2)
PWMH volume, cm33.1 (3.1)4.4 (4.5)6.8 (5.7)11.9 (7.2)4.2 (5.3)3.9 (3.7)4.1 (3.8)5.1 (5.0)
DWMH volume, cm31.3 (1.1)1.6 (1.3)2.1 (1.6)2.5 (1.1)1.3 (1.5)1.4 (1.2)1.8 (1.1)2.4 (1.7)
Lacunar (≥1), % (no.)3.1 (30)7.1 (44)22.4 (38)42.9 (9)3.1 (13)6.6 (62)11.1 (35)12.1 (11)
BPF0.72 (0.03)0.72 (0.03)0.71 (0.03)0.71 (0.03)0.72 (0.03)0.72 (0.03)0.72 (0.03)0.72 (0.03)

Table 5. Association Between MRI Markers and the Degrees of dVRS

dVRS in BG OR (95% CI)*dVRS in WM OR (95% CI)*
Degree 2 Versus 1Degree 3 Versus 1Degree 4 Versus 1P*Degree 2 Versus 1Degree 3 Versus 1Degree 4 Versus 1P*
P values correspond to the overall relationship between each variable and the different degrees of dVRS.
*Models of multinomial logistic regression adjusted on age, gender, total intracranial volume, and hypertension. In each model, dVRS in BG or dVRS in WM was considered as the dependent variable categorized in 4 degrees (the reference being the first degree).
†For continuous variables, the OR estimates the association related to an increase of 1 SD.
PWMH indicates periventricular WMH; DWMH, deep WMH; BPF, brain parenchymal fraction (ratio of brain tissue volume to intracranial volume).
Total WMH volume, cm31.7 (1.5–2.0)2.5 (2.1–2.9)3.2 (2.5–4.1)<0.00010.9 (0.8–1.1)1.0 (0.9–1.2)1.2 (1.0–1.4)0.02
PWMH volume, cm31.7 (1.5 (2.0)2.4 (2.0–2.9)3.1 (2.4–4.0)<0.00010.9 (0.8–1.0)0.9 (0.8–1.1)1.1 (0.9–1.3)0.18
DWMH volume, cm31.5 (1.3–1.7)1.9 (1.6–2.2)2.1 (1.6–2.7)<0.00011.1 (0.9–1.3)1.4 (1.2–1.7)1.8 (1.5–2.2)<0.0001
Lacunar (≥1)1.8 (1.1–3.0)6.8 (4.0–11.7)16.6 (6.0–45.9)<0.00011.9 (1.0–3.6)3.3 (1.7–6.4)3.4 (1.4–7.9)0.002
BPF0.9 (0.8–1.0)0.9 (0.7–1.1)1.1 (0.7–1.8)0.481.1 (0.9–1.3)1.2 (0.9–1.4)1.5 (1.1–1.9)0.27

Higher degree of dVRS was also associated with a higher frequency of lacunes (Table 3). Compared with subjects with no lacunes, those with at least 1 lacune had an increased odd of having dVRS of a higher degree. These risks were 2 to 5 times higher for BG than for WM (Table 5). Finally, global atrophy, determined by the brain parenchymal fraction (ratio of brain tissue volume to total intracranial volume), was not associated with dVRS degrees (Table 5).

Sensitivity analyses were also performed on participants reporting a history of stroke (N=43). The results remained unchanged and were identical to those presented in this article (data not shown).


This study, performed in a large population-based sample of 1818 elderly individuals, showed that the severity of dVRS was strongly associated with age and hypertension. The association with hypertension was found to be significant for dVRS located both in WM and in BG, although it was stronger for the latter. We also found that the severity of dVRS was associated with both WMH volume and the presence of lacunar infarctions, which are mainly driven by structural alterations of small cerebral penetrating arteries. Finally, no association was detected between the severity of dVRS and cerebral atrophy.

The association between hypertension or antihypertensive treatment and dVRS is in line with postmortem data showing that dVRS are highly prevalent within the brains of hypertensive patients.5,7 This result is, however, in contrast with an MRI study of 816 outpatients that reported no significant association between hypertension and dVRS after adjustment for age, gender, and dementia.16 This discrepancy may be related to the different scoring method used in this last study because only dVRS of diameter >2 mm were considered in the final analysis. Such a selection may inadequately estimate the global burden of dVRS because most of them are <2 mm of diameter.12

A striking difference between genders was observed for the severity of dVRS in BG because men had a 6-fold increased risk of degree 4 of dVRS compared with women. Such a gender difference has not been reported so far and remains unexplained. A weak but significant inverse association was detected between hypercholesterolemia and the severity of dVRS. Interestingly, a protective effect of hypercholesterolemia on the frequency of microbleeds, another MRI marker of small vessel disease, has been observed.17 It has been hypothesized that cholesterol could modulate the age- and hypertension-related ultrastructural changes of the microvasculature, but these results need to be confirmed.

Previous postmortem studies7 have suggested that perivascular spaces enlarge in parallel with the shrinking of the cerebrum. Our data do not confirm this hypothesis because we observed no association between the degree of dVRS and the brain parenchymal fraction.

The association between the severity of dVRS and the presence of lacunes and the volume of WMH suggests that the development of dVRS may be, at least partly, the consequence of an underlying small vessel disorder. These findings are in agreement with pathological data5,7 as well as with MRI results obtained in patients with stroke.18,19 It could be hypothesized that ultrastructural changes observed in the wall of cerebral penetrating arteries, which are associated with the accumulation of ischemic subcortical lesions, may also promote the dilation of perivascular spaces within the brain. Different mechanisms may be involved. An increased permeability of the small vessel wall4,8 has been reported to be associated with alterations of microvascular endothelial cells and of their tight junctions.3,8 In addition, the structural changes within the microvascular wall may also alter the external drainage of the interstitial fluid along the basement membranes that seems mainly driven by the arterial pulse.3,20

The effect of age and hypertension on dVRS seems to be stronger for dVRS located in BG than for those located in WM. Similarly, the association between dVRS and the load of WMH or of lacunes also appears to be stronger in BG than in WM. These results appear in line with the data already obtained in patients with lacunar stroke.18,19 Such differences are not unexpected, because the severity of dVRS in both locations does not match perfectly. Indeed, although the scoring methods are somewhat different, only 23% (22 of 94) of those with degree 4 of dVRS in WM also presented with degree 3 or 4 of dVRS in BG and 42% (10 of 24) with degree 4 of dVRS in BG also presented with degree 3 or 4 of dVRS in WM (data not shown). These data suggest that, despite the fact that some important risk factors are shared, the mechanisms underlying the development of dVRS may differ in different areas of the brain. Similar regional variations in severity have been already observed for different pathological processes such as fibrohyaline thickening, lipohyalinosis, or amyloid deposition within the microvasculature during aging.21–23 These different pathological processes may result in large differences in the vessel wall permeability, the subsequent Virchow-Robin space dilation, and the succeeding parenchymal lesions. The finding that the severity of dVRS in BG is associated with both periventricular and deep WMH in contrast with dVRS in WM only related to the extent that deep WMH may be also related to regional variations in the underlying pathological processes. The link between the regional distribution of dVRS and the underlying microvascular pathological changes deserves obviously more attention and further investigations.

The strengths of this study include the population-based design and the large number of elderly participants. We used high-resolution MRI, small voxel size, and multiplanar reformatting to obtain a reliable analysis of dVRS.1 Potential limitations include the possible underestimation of small ischemic lesions that do not always cavitate24 and the semiquantitative assessment of dVRS. The attribution of severity scores based on the slice containing the highest number of dVRS was pragmatic and was decided after an initial assessment in several dozens of examinations confirmed that the visual counting of each dVRS was unfeasible. In the present study, each of the 124 axially oriented slices was carefully inspected before counting the number of dVRS in the slices containing the greatest number of dVRS and in subjects with small numbers in WM, dVRS were actually evaluated on all the slices.

Because high-resolution MRI with millimetric resolution in 3 dimensions was applied in this research, further studies on comparison between 3-dimensional and 2-dimensional MRI for detection and rating of dVRS are needed to determine the generalizability of the present results in images acquired using conventional 2-dimensional MRI. To our view, because dVRS are usually small and with typical vascular shape, a high-resolution technique and multiplanar (or 3-dimensional) reformatting analysis are actually needed for the detection and discrimination of dVRS from other lesions.

In conclusion, this study strongly suggests that in elderly people, the degree of dVRS increases with age, hypertension, and the presence of markers of small vessel disease such as WM lesions and lacunar infarctions. The present data support that the severity of dVRS should be itself considered as a MRI marker of cerebral small vessel disease in the elderly and that its prognostic value and clinical significance of dVRS warrant further investigations.

Sources of Funding

The Three-City (3C) Study is conducted under a partnership agreement among the Institut National de la Santé et de la Recherche Médicale (INSERM), the Victor Segalen–Bordeaux II University, and Sanofi-Aventis. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The 3C Study is also supported by the Caisse Nationale Maladie des Travailleurs Salariés, Direction Générale de la Santé, MGEN, Institut de la Longévité, Conseils Régionaux of Aquitaine and Bourgogne, Fondation de France, and Ministry of Research–INSERM Programme “Cohortes et collections de données biologiques.” Y.-C.Z. is funded by the French Chinese Foundation for Science and Applications (FFCSA), the China Scholarship Council (CSC), and the Association de Recherche en Neurologie Vasculaire (ARNEVA). Sponsors are not involved either in the design of the study or in the data analyses or article elaboration.


C.D. has received consulting fees from EISAI. C.T. has received investigator-initiated research funding from the French National Research Agency (ANR) and has received fees from Sanofi-Synthelabo for participation in a Data Safety Monitoring Board and from Merck-Sharp & Dohm for participation in a scientific committee. H.C. has already received fees from Eisai, Lundbeck, Servier, and Johnson & Johnson companies for participating to data safety or scientific committees in studies unrelated to the present report.


Correspondence to Christophe Tzourio, MD, PhD, INSERM Unit 708, Hôpital La Salpêtrière, 75651 Paris Cedex 13, France. E-mail


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