Background: Aortic arch atheromas may be important sources of cerebral embolism. Aortic plaques are frequently found somewhat distal to the origin of the cerebral arteries, implying that cerebral embolization from such plaques depends on local retrograde blood flow components in this area. Therefore, we investigated the occurrence of blood flow reversal in this part of the aorta. Furthermore, since the presence and magnitude of retrograde flow might be influenced by aortic wall properties, we also studied the relationship between plaque size and distribution, aortic strain and degree of retrograde flow. Methods: We evaluated aortic arch ante- and retrograde blood flow velocities in 56 patients by transesophageal echocardiography using color-Doppler-guided pulsed-Doppler techniques. The velocity-time integrals (VTI) were measured and the diastolic/systolic VTI ratio was calculated. Results: Retrograde diastolic blood flow was noted in all subjects, and diastolic/systolic VTI ratios were higher (p < 0.05) in patients with plaque ≥4 mm (n = 17) compared to those (n = 39) without. Patients exhibiting plaques exclusively in the aortic arch showed the highest VTI ratios (p < 0.01) and tended to have the lowest strain values. Aortic strain was also reduced in patients >50 years of age (p < 0.01). Conclusions: Our findings demonstrate retrograde aortic flow in all subjects and its proportion increases in subjects with atherosclerosis, particularly in the aortic arch. Aortic plaques situated distally to the origin of the cerebral arteries are therefore possible sources of cerebral emboli.

Despite optimum standard anti-platelet therapy, cerebral micro-embolisation occurs in 30% of patients with symptomatic carotid artery disease, which might therefore be a possible risk factor for recurrent neurological symptoms. However, the presence of MES is independent of intrastenotic blood flow disturbances and grey scale ultrasound plaque characteristics. The presence of MES as an indicator of unstable plaque and thereby a possible risk factor for stroke should be evaluated prospectively using various algorithms for plaque classifications.

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