Transcranial Doppler sonography: anatomical landmarks and normal velocity values.

Until recently, both the diagnosis of intracranial occlusive disease of the large brain arteries, as well as intracranial flow abnormalities due to extracranial arterial lesions, have been a "blind spot" for ultrasound techniques. With the advent of transcranial Doppler sonography (TCD), however, a broad spectrum of potential clinical and scientific applications of TCD to the intracranial vasculature has been advocated. In order to achieve an informative insonation of vessels and a correct interpretation of findings, knowledge of both anatomical landmarks within the skull and flow characteristics of distinct vessel segments are necessary. This paper presents such data elaborated from 64 carotid and 42 vertebral angiograms, 40 contrast-medium enhanced CT scans demonstrating the circle of Willis, 122 normal sagittal MRI scans of the brainstem, 40 cadaver skulls, 38 fresh cadavers, 106 normal volunteers and 59 patients with subclavian steal mechanisms. The main findings were as follows: The inner internal carotid artery bifurcation, the M1-segment of the middle cerebral artery, the C3-segment of the carotid siphon, the vertebral artery junction and the top of the basilar artery were found at insonation depths of 60.4 +/- 7, 40 +/- 8 to 60.4 +/- 7, 62 +/- 4, 84 +/- 8 and 108 +/- 8 mm, respectively. Normal mean flow velocities within the M1-segment, the posterior cerebral artery, the carotid siphon and the basilar trunk were 58 +/- 15.6, 39 +/- 9.9, 47 +/- 13.8 and 41 +/- 10 cm/s, respectively, and revealed a marked decrease with age. Intraindividual side-to-side differences were low. Vertebrobasilar data from measurements of neuroradiological material closely met in vivo findings in normals and patients. Criteria for the identification of various vessel segments are provided. On the basis of these findings, a topographical orientation within the skull should be possible in order that beginners commence TCD accurately. Normative velocity data are helpful for differentiating normal and pathological flow conditions at different ages.