Middle cerebral artery anatomy and characteristics of embolic signals: a dual gate computer simulation study.
In terms of microembolic signal (MES) detection, the anatomy of the middle cerebral artery (MCA) mainstem has only scarcely been considered. The vessel itself, however, could be at least partly responsible for the enormous variation when calculating the essential time difference (deltat) values of MES using the dual-gate technique. Therefore, we studied the time characteristics of MES in a computer simulation applying an anatomically realistic vessel and a dual-gate TCD approach. Three different MCA anatomies and two MES to blood intensities were simulated as well as two different sample volume settings. The MES length (proximal sample volume t1; distal sample volume t2) and deltat were calculated for different angles of insonation and sample volume depths. The calculations of the time characteristics of MES showed extreme variation, with only modest changes of the insonation angle (t1 4-34 ms; deltat 9-27 ms) or the sample volume depth (t1 7-27 ms; deltat 6-32 ms). The variation could be considerably reduced with modified TCD settings i.e., a shorter gate separation combined with a shorter receiver gate time in the distal sample volume (deltat with changing insonation angles 6-19 ms; deltat with changing insonation depths 13-17 ms). These results not only urge us to a cautious interpretation of the properties of single MES, but also contribute to an understanding of the marked deltat variation using the dual-gate technique.
Mess
W H
WH
St. Antonius Hospital, Dept. of Clinical Neurophysiology, Nieuwegein, The Netherlands. max@fknf.azm.nl
Titulaer
B M
BM
Ackerstaff
R G
RG
D002536:Cerebral Arteries / Q000033:anatomy & histology / Q000000981:diagnostic imaging*; D003198:Computer Simulation; D006801:Humans; D002542:Intracranial Embolism and Thrombosis / Q000000981:diagnostic imaging* / Q000473:pathology; D008838:Microcomputers; D008954:Models, Biological; D013997:Time Factors; D017585:Ultrasonography, Doppler, Transcranial / Q000379:methods* / Q000706:statistics & numerical data