Published online before print June 3, 2004, doi: 10.1161/01.STR.0000132193.35955.69
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(Stroke. 2004;35:1821.)
© 2004 American Heart Association, Inc.
Original Contributions |
White Matter Hyperintensity on Cranial Magnetic Resonance Imaging
A Predictor of Stroke
From the Department of Epidemiology (L.H.K.), University of Pittsburgh, Pittsburgh, Pa; the Departments of Epidemiology and Neurology (W.T.L.), Biostatistics (A.M.A.), and Radiology (N.J.B.), University of Washington, Seattle, Wash; the Division of Neurology (C.B.), University of Nevada, Las Vegas, Nev; and the Department of Radiology (R.N.B.), University of Pennsylvania, Philadelphia, Pa.
Correspondence to Dr Lewis H. Kuller, Department of Epidemiology, University of Pittsburgh, 130 N. Bellefield Avenue, Room 550, Pittsburgh, PA 15213. E-mail KullerL{at}edc.pitt.edu
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Abstract |
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Background and Purpose— We have previously reported that several "silent" infarcts found on magnetic resonance imaging (MRI) were a risk factor for stroke. Several recent reports have shown that high white matter grade (WMG) and increasing WMG over time were risk factors for stroke. We tested the hypothesis that high WMG
2 was a predictor of risk for stroke, independent of other risk factors. Methods— We examined the extent of white matter hyperintensity on cranial MRI of 3293 participants from the Cardiovascular Health Study (CHS). The degree of white matter hyperintensity was graded from least severe (grade=0) to most severe (grade=9). Participants were followed-up for an average of 7 years for the occurrence of a stroke. Clinical stroke diagnoses were based on hospital records reviewed by an adjudication committee expert in stroke diagnosis. During this period, 278 strokes occurred.
Results The relative risk of stroke increased significantly as the WMG increased. The risk of stroke was 2.8% per year for participants with high WMG (grades 5), compared with only 0.6% for participants with grades 0 to 1.
Conclusions The risk of stroke with high WMG is independent of traditional stroke risk factors and persists when controlling for MRI infarcts, another subclinical imaging marker of cerebrovascular disease. Assessment of white matter disease may be valuable in assessing future risk of stroke.
Key Words: stroke • magnetic resonance imaging • white matter • infarcts, silent • hypertension • diabetes mellitus
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Introduction |
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Silent brain infarctions and high white matter grade (WMG), referred to as leukoaraiosis, are frequently observed on magnetic resonance imaging (MRI) scans.1,2 These findings are associated with gait and cognitive and neurobehavioral disturbances,3,4 and are likely of vascular origin.5–8 High WMG is a stronger predictor of lacunar infarcts and is most likely associated with small-vessel pathology.9 Progression of leukoaraiosis over a 6-year follow-up was associated with increased risk of stroke.10
The Rotterdam Scan Study has recently reported that participants in the highest tertile of white matter lesion distribution had a 4.7-fold increased risk of stroke for periventricular and 3.6-fold for subcortical white matter lesions.11
Cerebral MRI examinations for 3660 participants were performed in the Cardiovascular Health Study (CHS).12–16 MRI-detected infarcts and higher WMG were strongly associated with carotid intimal medial thickness and stenosis even after adjustment for age and sex (P<0.02).13 In the multivariate model, age, infarcts on MRI, higher systolic blood pressure, low forced expiratory volume in 1 second, and lower income were associated with higher WMG.12 Silent predominantly subcortical brain infarcts were associated with a 1.9-increased (1.2 to 2.8) risk of stroke over a 4.2-year follow-up. Risk of stroke increased with number of silent infarcts.17
The current report explores the relationship between white matter findings on MRI, other stroke risk factors, including subcortical brain infarcts, and subsequent incidence of stroke, with an average follow-up of 7 years.18
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Materials and Methods |
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Participant Selection
Participants in the CHS study were recruited in 4 communities from Medicare eligibility lists.
There were 5201 participants enrolled from 1989 to 1990, and an additional 687 black participants were added in 1992 to 1993, bringing the total to 5888. Details of CHS design and recruitment have been described elsewhere.19
Of the total cohort of 5888, 3660 participants without contraindication who consented underwent MRI in a standard fashion between 1991 and 1994.14 To determine the role of WMG as a predictor of incident stroke, 338 patients with stroke or transient ischemic attack (TIA) before the baseline MRI were excluded. Twenty-nine individuals were also excluded because of incomplete MRI data, resulting in 3293 participants included in this analysis.
MRI
MRI was performed on General Electric or Picker 1.5-tesla scanners at 3 field centers and on a 0.35-tesla Toshiba scanner at the fourth center. The scanning protocol included standard sagittal and axial spin-echo T1-weighted images (TR/TE 500/15 to 25) and axial spin-density and T2-weighted images (TR/TE 3000/20 to 35/70 to 100), all with 5-mm thickness and no interslice gap.13,14 Axial scans were aligned parallel to a line to the anterior and posterior commissures (AC–PC line). Scans were all performed without contrast administration.
The white matter signal changes of each individual were assessed on a semi-quantitative 10-point WMG (0 to 9) scale using predefined visual standards of 8 reference cases. WMG was estimated as the total extent of periventricular and subcortical white matter signal abnormality on spin-density–weighted axial images that successively increased from no or barely detectable changes (grades 0 and 1, respectively) to almost all white matter involved (grade 9).16 This scale has an interreader reliability agreement within 1 grade of 92.1%, with relaxed kappa of 0.81; intrareader reliability for agreement within 1 grade is 94.5%, with relaxed kappa of 0.93. Volumetric analytic validation of the visual scale corresponded to a rank increase in white matter hyperintensity normalized for cerebral parenchymal volume. Abnormalities interpreted as representing areas of large-vessel cerebral infarction or small-vessel lacunar infarction were coded separately in the database as infarct-like lesions12 (Appendix and Table 1).
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Event Ascertainment
Event ascertainment followed a detailed protocol at each of the field centers.20 Incident stroke was the outcome of interest in the analysis used in this article.21 Participants without stroke or TIA at the time of the MRI scan were considered to be at risk for stroke.
The CHS Events Stroke Subcommittee adjudicated all of the events based on defined criteria.21 The stroke events committee decided by consensus not only by stroke occurrence but also by stroke type and subtype.21 The type of stroke was classified by history and clinical observations as well as available MRI or computed tomography obtained at the time of clinical evaluation. Adjudicated incident strokes occurring after the baseline MRI (1992 to 1994) and before July 1, 2000, are included in this analysis. The median follow-up time was 7 years; interquartile range was 6.2 to 7.5 years, with a maximum of 8.6 years.
Statistical Methods
All analyses were performed using SPSS for Windows, version 10. Values of risk factors for stroke were determined by using participant information obtained from the annual examination closest in time and before the MRI.19 Values of risk factors for participants in the analysis were compared against those of participants not in the analysis for whom data were collected from 1992 to 1993 and who had no history of stroke or TIA. A t test was used to compare differences in means and a 
2 test was used for differences in proportions.
WMG was scored on a scale of 0 to 9, with few participants scoring 0 or >5. To obtain reliable estimates of the relative risk of stroke for each WMG, the upper and lower grades were collapsed. Incidence rates of stroke for the resultant WMG categories were computed by dividing the number of strokes in each category by the person-years at risk. Hazard ratios (HR) were determined from Cox proportional hazards models, with 3 stages of adjustment. Interactions between WMG and each risk factor were tested by likelihood ratio test for nested models. We computed stroke rates and HR for WMG >2 in combination with each of 5 known risk factors for stroke: hypertension, diabetes, history of myocardial infarction, coronary heart failure, and atrial fibrillation. The cutoff point of 2 was chosen to ensure adequate numbers in each cell. There was little change in risk at >2 in the analysis.
We examined the risk associated with the presence of an MRI-detected infarct in combination with WMG scores by computing incidence rates and HR for each WMG category separately for those with and without infarcts.
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Results |
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Participants who underwent MRI tended to be younger and healthier than those who did not (Table 1). WMG increased with age, with a trend toward greater severity in women.3 Strokes occurred in 278 of the 3293 participants in the analysis, with an incidence of 13.3 per 1000 person-years. (Table 1) The distribution of WMG and number of MRI infarcts by WMG are shown in the Figure. The number of participants with WMG >2 is low. There is a strong association of WMG and number of infarcts. We adjusted the analysis for clinic in CHS because of the difference in scanners at the Johns Hopkins University clinic. There was no interaction between scanner type and WMG, or with risk of stroke.
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The incidence of stroke was 6.0 per 1000 person-years for grades 0 to 1, to 27.6 per 1000 person-years for grades 5, with an age-adjusted HR of 3.3 (Table 2). The HR was slightly attenuated to 3.0 after adjusting for known stroke risk factors and remained significant at 2.2 after additional adjustment for subclinical risk factors and infarcts (Table 2). For all levels of adjustment, P value for a linear trend in WMG was <0.001.
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Risk of stroke was associated with WMG >2 whether a participant had hypertension, diabetes, history of myocardial infarction or congestive heart failure, atrial fibrillation, or none of these on electrocardiogram (Table 3). Risk of stroke was highest for participants with both higher WMG and a traditional risk factor. The combination conferring the greatest risk of stroke was WMG >2 and atrial fibrillation on electrocardiogram. The HR was 9.7 (CI, 5.5 to 17.1), with the wide confidence interval reflecting the fact that the estimate was based on only 36 participants with this combination of risk factors.
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There were 913 participants who had a silent brain infarct on the MRI (Figure). For each level of WMG, the risk of stroke was higher for participants with an infarct than for those with no infarct (Table 4). Similarly, for participants with an infarct, risk of stroke was greater in the presence of white matter disease. There was no significant interaction between WMG and presence of an infarct. The risk of stroke was increased for participants with high WMG, independent of the time from MRI to clinical stroke.
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Most of the clinical strokes in CHS were ischemic; 226 (81%) of 278 incident strokes were ischemic. The ischemic strokes were further subclassified into lacunar 33 (14.6%), cardioembolic 61 (27%), atherosclerotic 12 (5.3%), unknown 105 (46.5%), mixed 14 (6.2%), or other.1 Higher WMG (5) was related to total ischemic stroke (HR, 2.86; CI, 1.70 to 4.80), cardioembolic stroke (HR, 4.82; CI, 1.68 to 13.8), and unknown ischemic stroke (HR, 2.84; CI, 1.35 to 5.97). There was an increased risk of lacunar strokes with higher WMG, but the number of cases was small (33) and rates were very unstable (HR, 1.99; CI, 0.59 to 6.73) for WMG of 4 versus 0 to 1.
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Discussion |
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Our current results are consistent with a recent report from the Rotterdam group.11 Increased WMG is an independent predictor of stroke. This study clarifies the potential value of this marker to future stroke risk.
We have previously reported that high WMG was strongly related to vascular risk factors.13 It is likely that high WMG is determined, in part, by smaller-vessel disease in the brain as reflected by the strong association of infarcts (mostly subcortical) 3 mm on MRI examination. The high WMG may also be a marker of inflammation secondary to ischemic injury. High WMG can be used to identify participants at high risk for stroke, especially in combination with other cardiovascular risk factors such as hypertension and diabetes.
Better characterization of the relationship between pathology and MRI findings would be very useful. Improved methods of imaging may better-determine white matter pathophysiology. Postmortem comparison with premortem MRI is also needed to interpret WMG. Better determinants of the characteristics of WMG (phenotype) could result in better genetic and risk factor profiles.22
It may be useful to measure progression of WMG as a marker of the efficacy of various pharmacologic and nonpharmacologic therapies. We need to determine: (1) age at which differences in extent of WMG are first identified between those with or without vascular risk factors; (2) rates of progression of WMG changes; (3) efficacy of specific therapies to slow WMG change; and (4) possible host susceptibility or genetic determinants of extent of WMG in relation to risk factor levels. Further evaluation of specific localization of WMG in the brain to risk factors and outcomes are also important.
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Appendix |
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Acknowledgments |
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The research reported in this article was supported by contracts N01-HC-85079 through N01-HC-85086, N01-HC-35129, and N01 HC-15103 from the National Heart, Lung, and Blood Institute. For a full list of participating CHS investigators and institutions, see "About CHS: Principal Investigators and Study Sites" online at http://www.chs-nhlbi.org.
Received December 17, 2003; revision received April 21, 2004; accepted April 22, 2004.
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References |
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