CT angiography "spot sign" predicts hematoma expansion in acute intracerebral hemorrhage.

BACKGROUND AND PURPOSE: Morbidity and mortality in spontaneous intracerebral hemorrhage (ICH) are correlated with hematoma progression. We hypothesized that the presence of tiny, enhancing foci ("spot sign") within acute hematomas is associated with hematoma expansion.

METHODS: We prospectively studied 39 consecutive patients with spontaneous ICH by computed tomography angiography within 3 hours of symptom onset. Scans were reviewed by 3 readers. Patients were dichotomized according to the presence or absence of the spot sign. Clinical and radiological outcomes were compared between groups. The predictive value of this sign was assessed in a multivariate analysis.

RESULTS: Thirteen patients (33%) demonstrated 31 enhancing foci. Baseline clinical variables were similar in both groups. Hematoma expansion occurred in 11 patients (28%) on follow-up. Seventy-seven percent of patients with and 4% without hematoma expansion demonstrated the spot sign (P<0.0001). Sensitivity, specificity, positive predictive value, negative predictive value, and likelihood ratio for expansion were 91%, 89%, 77%, 96%, and 8.5, respectively. Interobserver agreement was high (kappa=0.92 to 0.94). In patients with the spot sign, mean volume change was greater (P=0.008), extravasation more common (P=0.0005), and median hospital stay longer (P=0.04), and fewer patients achieved a good outcome (modified Rankin Scale score <2), although the latter was not significant (P=0.16). No differences in hydrocephalus (P=1.00), surgical intervention (P=1.00), or death (P=0.60) were noted between groups. In multiple regression, the spot sign independently predicted hematoma expansion (P=0.0003).

CONCLUSIONS: The computed tomography angiography spot sign is associated with the presence and extent of hematoma progression. Fewer patients achieve a good clinical outcome and hospital stay was longer. Further studies are warranted to validate the ability of this sign to predict clinical outcomes.