MRI Characteristics of the Evolution of Supratentorial Recent Small Subcortical Infarcts

Silent brain infarcts and white matter lesions are associated with an increased risk of subsequent stroke in minor stroke patients. In healthy elderly people, silent brain infarcts and white matter lesions are common, but little is known about their relevance. We examined the risk of stroke associated with these lesions in the general population. The Rotterdam Scan Study is a population-based prospective cohort study among 1077 elderly people. The presence of silent brain infarcts and white matter lesions was scored on cerebral MRI scans obtained from 1995 to 1996. Participants were followed for stroke for on average 4.2 years. We estimated the risk of stroke in relation to presence of brain lesions with Cox proportional hazards regression analysis. Fifty-seven participants (6%) experienced a stroke during follow-up. Participants with silent brain infarcts had a 5 times higher stroke incidence than those without. The presence of silent brain infarcts increased the risk of stroke >3-fold, independently of other stroke risk factors (adjusted hazard ratio 3.9, 95% CI 2.3 to 6.8). People in the upper tertile of the white matter lesion distribution had an increased stroke risk compared with those in the lowest tertile (adjusted hazard ratio for periventricular lesions 4.7, 95% CI 2.0 to 11.2 and for subcortical lesions 3.6, 95% CI 1.4 to 9.2). Silent brain infarcts and severe white matter lesions increased the stroke risk independently of each other. Elderly people with silent brain infarcts and white matter lesions are at a strongly increased risk of stroke, which could not be explained by the major stroke risk factors.

We now propose a new approach to stroke subtyping. The concept is to introduce a complete ‘stroke phenotyping’ classification (i.e. stroke etiology and the presence of all underlying diseases, divided by grade of severity) as distinguished from past classifications that subtype strokes by characterizing only the most likely cause(s) of stroke. In this phenotype-based classification, every patient is characterized by A-S-C-O: A for atherosclerosis, S for small vessel disease, C for cardiac source, O for other cause. Each of the 4 phenotypes is graded 1, 2, or 3. One for ‘definitely a potential cause of the index stroke’, 2 for ‘causality uncertain’, 3 for ‘unlikely a direct cause of the index stroke (but disease is present)’. When the disease is completely absent, the grade is 0; when grading is not possible due to insufficient work-up, the grade is 9. For example, a patient with a 70% ipsilateral symptomatic stenosis, leukoaraiosis, atrial fibrillation, and platelet count of 700,000/mm 3 would be classified as A1-S3-C1-O3. The same patient with a 70% ipsilateral stenosis, no brain imaging, normal ECG, and normal cardiac imaging would be identified as A1-S9-C0-O3. By introducing the ‘level of diagnostic evidence’, this classification recognizes the completeness, the quality, and the timing of the evaluation to grade the underlying diseases. Diagnostic evidence is graded in levels A, B, or C: A for direct demonstration by gold-standard diagnostic tests or criteria, B for indirect evidence or less sensitive or specific tests or criteria, and C for weak evidence in the absence of specific tests or criteria. With this new way of classifying patients, no information is neglected when the diagnosis is made, treatment can be adapted to the observed phenotypes and the most likely etiology (e.g. grade 1 in 1 of the 4 A-S-C-O phenotypes), and analyses in clinical research can be based on 1 of the 4 phenotypes (e.g. for genetic analysis purpose), while clinical trials can focus on 1 or several of these 4 phenotypes (e.g. focus on patients A1-A2-A3).

White matter hyperintensities and lacunes are among the most frequent abnormalities on brain magnetic resonance imaging. They are commonly related to cerebral small vessel disease and associated with both stroke and dementia. We examined the spatial relationships between incident lacunes and white matter hyperintensities and related these findings to information on vascular anatomy to study possible mechanistic links between the two lesion types. Two hundred and seventy-six patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), a genetically defined small vessel disease with mutations in the NOTCH3 gene were followed with magnetic resonance imaging over a total of 633 patient years. Using difference images and Jacobian maps from registered images we identified 104 incident lacunes. The majority (n = 95; 91.3%) of lacunes developed at the edge of a white matter hyperintensity whereas few lacunes were found to develop fully within (n = 6; 5.8%) or outside (n = 3; 2.9%) white matter hyperintensities. Adding information on vascular anatomy revealed that the majority of incident lacunes developed proximal to a white matter hyperintensity along the course of perforating vessels supplying the respective brain region. We further studied the spatial relationship between prevalent lacunes and white matter hyperintensities both in 365 patients with CADASIL and in 588 elderly subjects from the Austrian Stroke Prevention Study. The results were consistent with the results for incident lacunes. Lesion prevalence maps in different disease stages showed a spread of lesions towards subcortical regions in both cohorts. Our findings suggest that the mechanisms of lacunes and white matter hyperintensities are intimately connected and identify the edge of white matter hyperintensities as a predilection site for lacunes. Our observations further support and refine the concept of the white matter hyperintensity penumbra.