Fractal analysis of retinal vessels suggests that a distinct vasculopathy causes lacunar stroke.
OBJECTIVE
Lacunar strokes account for 25% of all ischemic strokes and may represent the cerebral manifestation of a systemic small vessel vasculopathy of unknown etiology. Altered retinal vessel fractal dimensions may act as a surrogate marker for diseased cerebral vessels. We used a cross-sectional study to investigate fractal properties of retinal vessels in lacunar stroke.


METHODS
We recruited patients presenting with lacunar stroke and patients with minor cortical stroke as controls. All patients were examined by a stroke expert and had MRI at presentation. Digital retinal photographs were taken of both eyes. Monofractal and multifractal analyses were performed with custom-written semiautomated software.


RESULTS
We recruited 183 patients. Seventeen were excluded owing to poor photographic quality, leaving 166 patients (86 with lacunar and 80 with cortical stroke). The mean age was 67.3 years (SD 11.5 years). The patients with lacunar stroke were younger but the prevalence of diabetes, hypertension, and white matter hyperintensities did not differ between the groups. The mean Dbox (monofractal dimension) was 1.42 (SD 0.02), the mean D0 (multifractal dimension) 1.67 (SD 0.03). With multivariate analysis, decreased Dbox and D0 (both representing decreased branching complexity) were associated with increasing age and lacunar stroke subtype after correcting for hypertension, diabetes, stroke severity, and white matter hyperintensity scores.


CONCLUSIONS
Lacunar stroke subtype and increasing age are associated with decreased fractal dimensions, suggesting a loss of branching complexity. Further studies should concentrate on longitudinal associations with other manifestations of cerebral small vessel disease.
Doubal
F N
FN
Division of Clinical Neurosciences, University of Edinburgh, Western General Hospital, Edinburgh, UK. fergus.doubal@ed.ac.uk
MacGillivray
T J
TJ
Patton
N
N
Dhillon
B
B
Dennis
M S
MS
Wardlaw
J M
JM
D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000473:pathology; D000792:Angiography / Q000379:methods*; D015415:Biomarkers; D001921:Brain / Q000098:blood supply / Q000473:pathology / Q000503:physiopathology; D020520:Brain Infarction / Q000175:diagnosis* / Q000503:physiopathology; D002536:Cerebral Arteries / Q000473:pathology* / Q000503:physiopathology; D002560:Cerebrovascular Circulation / Q000502:physiology; D003430:Cross-Sectional Studies; D003941:Diagnostic Techniques, Ophthalmological; D005260:Female; D017709:Fractals; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D009413:Nerve Fibers, Myelinated / Q000473:pathology; D011237:Predictive Value of Tests; D012161:Retinal Artery / Q000473:pathology* / Q000503:physiopathology
D015415:Biomarkers