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July 28, 2009; 73 (4) Articles

Prevalence, incidence, and risk factors of lacunar infarcts in a community sample

Xiaohua Chen, Wei Wen, Kaarin J. Anstey, Perminder S. Sachdev
First published July 27, 2009, DOI: https://doi.org/10.1212/WNL.0b013e3181aa52ea
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Abstract

Background: Lacunar infarcts are small cavitated lesions no larger than 2 cm in diameter. Although often asymptomatic, they have been suggested as an important pathologic substrate of vascular dementia. The prevalence and risk factor profile of lacunar infarction has been variously reported, but the incidence data are scarce for large community-based data.

Methods: Participants (n = 477) were recruited randomly from the electoral roll of community residents aged 60–64 years as part of the PATH Through Life Study. Demographic information and risk factor data were collected and MRI brain scans performed in two waves, 4 years apart. The number and locations of lacunar infarcts as well as other volumetric data were assessed on T1-weighted and T2-weighted fluid-attenuated inversion recovery images.

Results: In wave 1, 37 (7.8%) participants had at least one lacunar infarct. New lacunar infarcts were detected in 6 (6/375, 1.6%) participants at wave 2. Lacunes present at wave 1 increased significantly in mean volume from 53.90 to 69.86 mm3 over 4 years. Hypertension (odds ratio [OR] = 1.6; 95% confidence interval [CI] = 1.01–2.60), anterior ventricle-brain ratio (%) (OR = 1.02; CI = 1.003–1.036), and volume of white matter hyperintensities (OR = 4.9; CI = 1.53–15.80) were independently associated with the prevalence of lacunar infarction.

Conclusion: Lacunes were common incidental findings in the brains of individuals in their 60s, and their prevalence as well as size increased with age. Hypertension was the major treatable risk factor, and lacunar infarction was usually associated with severe white matter hyperintensities on T2-weighted imaging.

Glossary

BP=
blood pressure;
CI=
confidence interval;
FLAIR=
fluid-attenuated inversion recovery;
FOV=
field of view;
GM=
gray matter;
ICC=
intraclass correlation;
ICV=
intracranial volume;
MMSE=
Mini-Mental State Examination;
OR=
odds ratio;
TE=
echo time;
TI=
inversion time;
TR=
repetition time;
VBR=
ventricle-to-brain ratio;
WM=
white matter;
WMH=
white matter hyperintensity.

Lacunes are small brain infarcts generally no more than 2 cm in size and mostly present in the deep brain structures.1 The prevalence of lacunar infarcts in the brains of otherwise healthy individuals has been reported variously from 5% to as high as 48% in different age groups.2–7 These incidental findings are not truly silent, as they have been associated with cognitive deficits,2,8,9 and their accumulation, or presence in strategic brain regions, has also been suggested as an important pathologic substrate of vascular dementia.10,11

Hypertension-related arteriopathy has been initially suggested by Fisher as the major cause of lacunar infarcts in autopsy studies. With the advent of large community-based MRI studies, it has become possible to systematically examine the risk factors for lacunar infarction, with or without clinical features. One limitation of the published studies, however, is that they are mostly cross-sectional3,5 without knowledge of incidence. Another feature of MRI scans of elderly individuals is the presence of white matter hyperintensities (WMHs). These lesions may represent ischemic regions that have not yet resulted in infarction. The relationship of lacunar infarcts with WMHs is therefore of much interest.

This study aimed to assess the prevalence of lacunar infarcts on MRI in a large community population aged 60–64 years and its incidence over 4 years. We also examined the risk factor profile of lacunar infarcts and its relationship with other volumetric measures.

METHODS

Subjects.

Participants were recruited from the PATH Through Life study, which is a prospective longitudinal study of three cohorts aged 20–24, 40–44, and 60–64 years, recruited randomly through the compulsory Australian electoral roll in Canberra and Queanbeyan. This report relates to the 60–64 cohort. Letters were randomly sent to 4,832 persons according to the age information released by the Australian Electoral Commission; 32 were out of study age range (60–64 years), 182 had moved out of the area, 28 were dead, 209 could not be found, and 1,827 refused or their English was too poor to participate in the study. A total of 2,551 (58.3%) participants responded to the initial random mail contact and agreed to participate in the interview. Participants were screened and further assessed for cognitive impairment and one case of dementia and one case of delirium were diagnosed and excluded.12 About one subject in five was selected randomly to enter the MRI study. Consequently, 622 were approached, and 478 (77%) (men = 252) provided written informed consent. The MRI sample was a cognitively healthy sample with a mean Mini-Mental State Examination (MMSE13) score of 29.3/30, although cognitive function was not a criterion for inclusion or exclusion. Those who declined to undergo a scan were more likely to be of non-English speaking background, were less educated, had poorer physical health, and had lower cognitive scores. The sample is comparable with corresponding 2001 census data for Canberra and Queanbeyan in employment status, education, and marital status.

Participants were invited 4 years later to undergo another MRI scan and received a similar clinical assessment as in wave 1 with a mean interval of 1,474.3 ± 92.3 days. The flow chart of participation is presented in figure 1. Those who agreed to have an MRI scan at wave 2 were more educated but did not differ in age, sex, or MMSE scores at either time point. The study was approved by the human research ethics committees of the Australian National University, Canberra, and the University of New South Wales, Sydney, Australia.

Figure

Figure 1 Flow chart of the MRI sample at wave 1 and wave 2 in the 60–64 years of age cohort of the PATH Through Life study

Risk factor assessment.

All participants were interviewed for baseline demographic information. Two readings of resting blood pressure (BP) of 2 hours apart with participants sitting were taken by the interviewer. Blood samples were taken and measured in the center. Buccal swabs and blood were collected for DNA analyses of APOE polymorphism. Hypertension was defined as a trichotomous index based on history and BP readings at baseline assessment: 1) definite hypertension referred to subjects who were on treatment for hypertension or had mean systolic BP ≥160 mm Hg or mean diastolic BP ≥95 mm Hg; 2) borderline hypertension meant self-reported history of hypertension but with no treatment or mean systolic BP ranged 140–159 mm Hg or diastolic BP ranged 90–94 mm Hg; 3) normotensive was defined as no history of hypertension and mean systolic BP ≤140 mm Hg and mean diastolic BP ≤90 mm Hg. Diabetes was defined as having been diagnosed by a medical practitioner and currently being on a diabetic diet, hypoglycemic tablets, or insulin, or a fasting blood glucose level ≥10 mmol/L. Smoking currently and in the past was assessed through self reports of the participants. Weekly alcohol consumption was also estimated according to individual answers to a questionnaire about frequency and amount of drinks (10 g alcohol) consumed on typical drinking days and was calculated by using quantity frequency assessment procedures.14

MRI acquisition.

MRI data were obtained in coronal plane on a 1.5-T Gyroscan scanner (ACS-NT, Philips Medical Systems, Best, The Netherlands). T1-weighted structural MRI were acquired using fast field echo sequence with repetition time (TR) = 28.05 msec, echo time (TE) = 2.64 msec, a flip angle of 30°, matrix size = 256 × 256, and the field of view (FOV) was 260 × 260 mm. Slice thickness was 2.0 mm, with a 1.0 mm mid-slice to mid-slice distance, yielding over-contiguous coronal slices and in-plane spatial resolution of 1.016 × 1.016 mm/pixel. The fluid-attenuated inversion recovery (FLAIR) sequence was acquired with TR = 11,000 msec, TE = 140 msec, TI = 2,600, number of excitations = 2, matrix size = 256 × 256, and the FOV was 230 × 230 mm. Slice thickness was 4.0 mm with no gap between slices and in-plane spatial resolution is 0.898 × 0.898 mm/pixel. At wave 2, MRI data were obtained on another Philips scanner, where T1-weighted images were acquired with TR = 9.35 msec, TE = 3.72 msec, a flip angle of 8°, matrix size = 256 × 256, slices 160, FOV was 256 × 256 mm, with a slice thickness of 1.5 mm. No changes were made in parameters for FLAIR images.

Lacunar infarcts.

Lacunar infarct was defined as small cavitated lesions with diameters ranging from 3 to 20 mm.1,5,15 The lesions were characterized as being hypointense in T1-weighted and FLAIR images, and surrounded by a hyperintense rim in the latter.16,17 Both definite and ambiguous lesions were reviewed in consultation with a neuroradiologist (Dr. R. Shnier) without knowing the history and clinical information of the participants. The detection of lacunar infarcts showed good interrater reliability (κ = 0.89) and intrarater (κ = 1.00) reliability by examining 50 scans. All lacunar infarcts were manually traced and volumes were calculated as the sum of all infarcts for each participant.

Volumetric measures.

The T1-weighted images were first segmented into gray matter (GM), white matter (WM), and CSF partitions using SPM2 (Wellcome Department of Cognitive Neurology, Institute of Neurology, London, UK) on Matlab 7.1 (MathWorks, Natick, MA). The total GM, WM, and CSF volumes were computed and the WMH were detected and measured quantitatively.18 The volumes of hippocampus and amygdala were determined by two tracers. Intraclass correlations (ICCs) between the two raters for the right and left hippocampus were 0.970 and 0.937, and 0.943 and 0.974 for the right and left amygdala. ICCs within raters ranged from 0.948 to 0.989 and 0.981 to 0.993 for the right and left hippocampus, and from 0.975 to 0.989 and 0.995 to 0.996 for the right and left amygdala, respectively.19 Ventricle-to-brain ratio was also measured for each participant.20

Statistical analyses.

Student t test was applied to continuous variables and χ2 test to compare categorical variables between participants with and without lacunar infarcts. The pairwise t test was applied to compare volumes of lacunar infarcts between wave 1 and wave 2. An analysis of covariance was employed to compare volumetric measures between the above two groups, controlling for the effects of total intracranial volumes. A stepwise logistic regression was applied to determine independent risk factors of lacunar infarcts. Statistical significance was set at p < 0.05 and the analyses were conducted using SPSS 14.0 (SPSS/PC, Chicago IL).

RESULTS

In wave 1, 477 participants, aged 62.57 ± 1.45 years, comprising 251 men and 226 women, were assessed for lacunar infarcts. Thirty-seven (7.8%) had at least one lacunar infarct on MRI while 3 (0.6%) subjects had more than one lacunar infarct. Lacunar infarct was detected in 7.2% of the participants without previous diagnoses of stroke and 20% of those with previous diagnoses of stroke. Table 1 compares the demographic characteristics between groups of participants with and without lacunar infarcts at wave 1.

View this table:

Table 1 Demographic characteristics and vascular risk factors of subjects with and without lacunar infarcts

The presence of lacunar infarction was significantly associated with hypertension, higher averaged systolic and mean arterial blood pressure, but not diastolic blood pressure. There was no difference in lacunar infarct volumes between definitely hypertensive, borderline, and normotensive participants (F = 0.586, p = 0.562).

Volumetric measures of other structures were compared between the group with and without lacunar infarcts at wave 1 (table 2). The lacunar infarct group had a higher ratio of anterior VBR as well as greater WMH volumes, including the amount of periventricular, deep white matter, and severe WMHs. However, the volumes of hippocampus, amygdala, or lateral ventricle were not significantly different between the two groups, after adjusting for intracranial volume. A stepwise logistic regression analysis showed that hypertension (OR = 1.6, CI = 1.01–2.60, p = 0.045), anterior VBR (%) (OR = 1.02, CI = 1.003–1.036, p = 0.020), and WMH (OR = 4.9, CI = 1.53–15.80, p = 0.008) were independent correlates for the prevalence of lacunar infarcts.

View this table:

Table 2 Volumetric measures of subjects with and without lacunar infarct

Seven participants with lacunae at wave 1 did not have MRI available at wave 2. Participants who had no MRI scan available at wave 2 did not differ from those who had in the presence of lacunar infarcts at wave 1 (χ2 = 0.145, p = 0.703). At wave 2, lacunar infarct was detected in 33 participants (33/375, 8.8%) while new lacunar infarcts were detected in 6 (6/375, 1.6%) participants (figure 2), including five men and one woman, with an age of 66 ± 1.90 years and an education of 13.5 ± 2.0 years. Three of them had had lacunar infarcts detected at wave 1. Of these six participants, four had definite hypertension, one was borderline hypertensive, and one other was normotensive. The number of incident cases was too small to examine other risk factors for incident infarction. A topographic representation of all lacunar lesions at wave 1, and incident lesions at wave 2, is shown in figure e-1 on theNeurology® Web site at www.neurology.org. The lacunar infarcts were detected in basal ganglia (n = 22, 59.5%), subcortical white matter (n = 11, 29.7%), brainstem (n = 3, 8.1%), and thalamus (n = 1, 2.7%) at wave 1. Incident lesions were found in basal ganglia (n = 3), subcortical white matter (n = 2), and thalamus (n = 1).

Figure

Figure 2 A lacunar infarct located in the right temporal white matter in the same participant on (A) T1-weighted MRI, (B) FLAIR scan at wave 1, (C) T1-weighted MRI, and (D) FLAIR scan at wave 2

(A) Axial T1-weighted image of a participant at wave 1 who showed a new lacunar infarct (red arrows) in right putamen at wave 2 (B). Fluid-attenuated inversion recovery (FLAIR) images at wave 1 (C) and at wave 2 (D) show a hyperintense rim surrounding the lesion.

We measured the volumes of the same infarcts in waves 1 and 2. The mean volume of lacunar infarcts was 53.90 ± 125.41 mm3 at wave 1 and 69.86 ± 157.81 mm3 at wave 2, suggesting an increase of 18.16 ± 37.21 mm3 in volume in 4 years (t = −2.628, p = 0.014). The difference in volumes of lacunar infarcts at wave 1 between men (70.54 ± 168.08 mm3) and women (29.97 ± 27.43 mm3) was not significant. Similarly, the correlation between age and the volume of lacunar infarct either at wave 1 (r = −0.328, p = 0.051) or wave 2 (r = −0.314, p = 0.066) did not reach significance.

DISCUSSION

Asymptomatic lacunar lesions have been widely reported in population-based studies with estimated prevalence ranging from 5 to 48%.2–5 Our study has shown a prevalence of 7.8% for lacunar infarcts in a cohort aged 60–64 years. These data are comparable with other community-based studies using MRI, of which one reported 86 and another 8.6% (55/635) in participants aged 60–64 years.5 Similar results have also been reported in the Austrian stroke prevention study, where lacunes were found by MRI in 6.9% community-dwelling subjects aged 50–75 years,4 and 7.7% of subjects aged 60–69 years at death who had silent brain infarcts detected in postmortem.21 A recent report from the Framingham offspring study which sampled 2,040 subjects showed silent cerebral infarcts by MRI in about 11% of men and 10% of women aged 60–69 years.7

The prevalence of lacunar lesions in previous studies has varied mostly due to the age of the populations being studied.3,6,22 The association between higher prevalence of lacunar infarct and advanced age is not linear, with the risk of lacunar infarct rising dramatically in those over 65 years.5,23 Therefore, the lacunar infarcts in a cohort comprising a large age range are mostly contributed by the elderly in the cohort. As our study comprises a large number of participants within a limited age range, the result represents the prevalence of lacunar infarct at midlife.

In our study, newly detected lacunar infarcts were found in 1.6% of the population, which is consistent with another community-based study, where newly onset lacunes were reported in 5 subjects (2%) after 3 and 6 years.24 Incidence of silent brain infarction has been reported at around 3% per year in the elderly.25,26 Community-based data of incidence for silent lacunar infarcts are scarce. If we assume the rate of lacunar infarcts in subjects younger than 60 is similar to what we observed in the current sample, i.e., 0.6%/year, the upper bound of the age at onset would be around 40. This result is comparable to previous studies such as The NILS-LSA Study, where prevalence in subjects aged 40 or higher is about 1–2%.27 However, there is no information about subjects younger than 60 in the current study. A recent report showed newly onset lacunar infarct in 18.7% of an elderly cohort aged 65–84 years over 3 years,28 suggesting a higher incidence associated with advanced age. Our study also showed that the volume of lacunar infarcts had increased over 4 years. Although this was only demonstrated in a limited number of subjects, it may indicate a progressive process of atrophy in surrounding tissue of the lesion.

In previous studies, lacunar infarction has been associated with a number of risk factors with inconsistent results.3,5,6 One widely reported factor is hypertension,29 which was shown to have a significant association with lacunar infarction in the current study. Our study replicated the finding of higher systolic blood pressure in lacunar infarction which has been reported in previous studies,6,7,30 but not diastolic blood pressure.3,6 In our study, participants with and without lacunar infarct had a comparable sex ratio, history of diabetes and smoking, similar consumption of alcohol, nearly equal BMI, and similar blood lipid profiles. Higher risk of lacunar infarct has been reported both in men3 and women,6 while sex was not associated with lacunar infarct in another study.5 Incidences of silent brain infarct were similar in men and in women in the literature.7,31 However, we found that five of six cases with newly onset lacunar infarct at wave 2 were men, suggesting the possibility of a higher risk of men developing new lacunar infarct at this age.

Just like lacunar infarcts, WMHs are considered to be a surrogate of small vascular disease. Greater total WMHs, periventricular WMHs, deep WMHs, and severe WMHs were correlated with lacunar infarcts in this study, which is consistent with the literature.32,33 Some studies have shown that lacunar infarcts share some risk factors with WMHs such as age and hypertension,3 which might explain the link between them. However, WMHs were shown to have slightly different risk factor profiles. In one study, age and hypertension were associated with leukoaraiosis, whereas hypercholesterolemia, diabetes, and myocardial infarction were associated with lacunar infarction.34 Furthermore, sex affects WMHs and lacunar infarcts differently, in that women have shown relatively more WMHs than men35 while they have a comparable amount of lacunar infarcts in our study. In fact, hypertension and WMHs contributed independently to the prevalence of lacunar infarcts. In addition, progression of WMHs and lacunar infarct is neither identical nor precipitated by the same risk factors.28 We speculate that although both lacunar infarct and WMHs are structural correlates of small vessel disease, they may have different susceptibilities to the effect of hypertension, or other vascular risk factors. The link between lacunar infarct and WMHs may reflect similar ongoing vasculopathy in small vessels, i.e., increased small blood vessel permeability, which is not entirely due to hypertension.36

The present study showed that lacunar infarction was correlated with a higher anterior VBR but not midbrain VBR, both of which are measures of central atrophy. Lacunar infarcts could contribute to central atrophy as a result of loss of white matter volumes, given that volumes of lacunar infarcts increased during follow-up in our study. However, lacunar infarction was not associated with hippocampal or amygdala atrophy in this study. Previous results were not consistent, with one population-based study showing no correlation between hippocampus volumes and lacunar infarct, but they only examined men.37 Other studies were mostly based on small samples of AD, mild cognitive impairment, or dementia.38,39 Lacunar infarction therefore seems to affect the brain independently of gray matter pathologies in the normal population.

First, lacunar infarction was diagnosed on the basis of FLAIR images, which are not as sensitive as T2-weighted scans in detecting lesions in the thalami,40 as reported by one study, in which, however, about 70% of lesions were relatively small with a diameter within 5 mm. As such, they are not likely to be lacunar infarcts by the criteria used in the current study. Therefore, the influence of undetected lesions in our study is likely to be minor. Second, the limited age range of the current cohort constrains the conclusions from being applied to the general ageing population. Third, the current findings were likely biased by recruiting individuals who are relatively higher functioning. Nonetheless, this study provides invaluable information on the healthy population in their 60s, which is the main target of primary prevention in vascular disease.

AUTHOR CONTRIBUTIONS

Statistical analyses were conducted by X.C.

ACKNOWLEDGMENT

The authors thank Dr. Ron Shnier for his opinion on the imaging definition of lacunar infarct and Terence Chua for validating the reliability of the method to detect lacunar infarct. The authors also thank the following people for their contribution to the PATH Through Life Project: Helen Christensen, Anthony F. Jorm, June Cullen, Trish Jacomb, Rajeev Kumar, Jerome Maller, Karen Maxwell, Chantal Meslin, Jeremy Price, Bryan Rodgers, and the PATH Interviewing Team.

Footnotes

  • Embedded Image

  • Supplemental data at www.neurology.org

    Supported by Project Grant ID 157125 and Program Grant 179805 from the National Health and Medical Research Council (NHMRC) of Australia.

    Disclosure: The authors report no disclosures.

    Received September 8, 2008. Accepted in final form March 16, 2009.

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