is leukoaraiosis on CT an accurate surrogate marker for the presence of microbleeds in acute stroke patients?
Microbleeds (MB) detected on gradient echo magnetic resonance images (GRE) are a potential risk factor for intracerebral hemorrhage after thrombolysis or oral anticoagulation. We assessed whether the presence of MB could be predicted from the extent of white matter disease (WMD) on computed tomography (CT).


METHODS
We studied consecutive TIA or ischemic stroke patients who presented to the ER and who underwent both CT and GRE. WMD was rated on CT using a three point scale by two independent observers. The presence of MB was assessed on GRE. Logistic regression was used to predict the presence of MB on GRE.


RESULTS
199 consecutive patients underwent both CT and GRE. MB were identified on GRE in 56 patients (28.1%). After adjustment for age and sex, MB were more frequent in patients with leukoaraiosis (OR 2.8 per 1-point increase on the Van Swieten scale, p<0.001) and in patients presenting with a lacunar or posterior circulation syndrome (OR 2.0, p=0.048). The area under the ROC-curve derived from the logistic model was 0.70 (95% CI 0.61-0.79). Age, sex, hypertension, diabetes or the presence of left ventricular hypertrophy on ECG were not different in patients with or without MB.


CONCLUSIONS
White matter disease on CT is associated with the presence of microbleeds on GRE. However, leukoaraiosis does not detect the presence of MB accurately enough to be considered a surrogate marker.
Görner
Astrid
A
Department of Neurology, University Hospitals Leuven, Herestraat 49, B-3000, Leuven, Belgium.
Lemmens
Robin
R
Schrooten
Maarten
M
Thijs
Vincent
V
D000368:Aged; D000369:Aged, 80 and over; D015415:Biomarkers; D002543:Cerebral Hemorrhage / Q000175:diagnosis* / Q000209:etiology*; D005260:Female; D006801:Humans; D049292:Leukoaraiosis / Q000473:pathology*; D016015:Logistic Models; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012372:ROC Curve; D012189:Retrospective Studies; D012307:Risk Factors; D018709:Statistics, Nonparametric; D020521:Stroke / Q000150:complications* / Q000473:pathology; D014057:Tomography, X-Ray Computed / Q000379:methods
D015415:Biomarkers