MOSAIC: Multimodal Stroke Assessment Using Computed Tomography: novel diagnostic approach for the prediction of infarction size and clinical outcome.
OBJECTIVE
With new CT technologies, including CT angiography (CTA), perfusion CT (PCT), and multidetector row technique, this method has regained interest for use in acute stroke assessment. We have developed a score system based on Multimodal Stroke Assessment Using CT (MOSAIC), which was evaluated in this prospective study.


METHODS
Forty-four acute stroke patients (mean age, 63.8 years) were enrolled within a mean of 3.0+/-1.9 hours after symptom onset. The MOSAIC score (0 to 8 points) was generated by results of the 3 sequential CT investigations: (1) presence and amount of early signs of infarction on noncontrast CT (NCCT; 0 to 2 points), (2) stenosis (>50%) or occlusion of the distal internal carotid or middle cerebral artery on CTA (0 to 2 points), and (3) presence and amount of reduced cerebral blood flow on 2 adjacent PCT slices (0 to 4 points). The predictive value of the MOSAIC score was compared with each single CT component with respect to the final size of infarction and the clinical outcome 3 months after stroke by use of the modified Rankin Scale (mRS) and the Barthel Index (BI).


RESULTS
Among the CT components, PCT showed the best correlation to infarction size (r=0.75) and clinical outcome (r=0.60 to 0.62) compared with NCCT (r=0.43 to 0.58) and CTA (r=0.47 to 0.71). The MOSAIC score showed consistently higher correlation factors (r=0.67 to 0.78) and higher predictive values (0.73 to 1.0) than all single CT components with respect to outcome measures. A MOSAIC score <4 predicted independence with 89% to 96% likelihood (mRS </=2, BI >/=90); a MOSAIC score <5 predicted fair outcome with 96% to 100% likelihood (mRS </=3, BI >/=60).


CONCLUSIONS
The MOSAIC score based on multidetector row CT technology is superior to NCCT, CTA, and PCT in predicting infarction size and clinical outcome in hyperacute stroke.
Nabavi
Darius G
DG
Department of Neurology, University of Münster, Münster, Forchheim, Germany. nabavi@uni-muenster.de
Kloska
Stephan P
SP
Nam
Eun-Mi
EM
Freund
Michael
M
Gaus
Christiane G
CG
Klotz
Ernst
E
Heindel
Walter
W
Ringelstein
E Bernd
EB
D000208:Acute Disease; D002544:Cerebral Infarction / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000628:therapy; D003287:Contrast Media / Q000008:administration & dosage; D005260:Female; D005500:Follow-Up Studies; D006493:Heparin / Q000627:therapeutic use; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D010975:Platelet Aggregation Inhibitors / Q000627:therapeutic use; D011237:Predictive Value of Tests; D011379:Prognosis; D011446:Prospective Studies; D012372:ROC Curve; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index; D020521:Stroke / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000628:therapy; D015996:Survival Rate; D010959:Tissue Plasminogen Activator / Q000627:therapeutic use; D014057:Tomography, X-Ray Computed / Q000379:methods; D016896:Treatment Outcome
D003287:Contrast Media; D010975:Platelet Aggregation Inhibitors; D006493:Heparin; D010959:Tissue Plasminogen Activator