Acute ischemic stroke: predictive value of 2D phase-contrast MR angiography--serial study with combined diffusion and perfusion MR imaging.

Abstract

To evaluate phase-contrast magnetic resonance (MR) angiography and diffusion- and perfusion-weighted imaging in predicting evolution of infarction and clinical outcome. Phase-contrast angiographic and diffusion-weighted images obtained 1 and 2 days after acute middle cerebral artery (MCA) stroke were assessed in 43 patients; 39 underwent perfusion-weighted imaging on day 1. Follow-up phase-contrast angiographic and T2-weighted images (n = 38) were obtained on day 8. Clinical outcome was assessed at 3 months. Patients were assigned to three groups according to angiographic findings on day 1: group 1, absence of flow in proximal MCA (M1 segment); group 2, internal carotid artery (ICA) occlusion with collateral M1 flow; group 3, flow in ICA and M1. Differences in lesion volumes on diffusion- and perfusion-weighted maps among groups were compared with one-way analysis of variance with Tukey post hoc multiple comparisons. Patients in group 1 had significantly larger infarct growth, volumes of hypoperfusion on relative cerebral blood volume (rCBV) and relative cerebral blood flow maps, and initial and final infarct volumes than did other patients (P <.05). Initial perfusion deficits on mean transit time maps were significantly (P =.002) larger in group 2 than in group 3, but there were no significant differences in infarct growth (P =.977), final infarct volume on day 8 (P =.947), and clinical outcome (P =.969). Absence of M1 flow on day 1 was significantly associated with unfavorable clinical outcome (modified Rankin score > or = 3) at 3 months (P =.010, chi(2) test). Discriminant analysis revealed that rCBV maps alone and combination of diffusion-weighted imaging and MR angiography yielded the highest accuracy in predicting an unfavorable clinical outcome. Phase-contrast MR angiography can provide complementary information to that with diffusion- and perfusion- weighted imaging in predicting the outcome of patients with acute stroke.