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Stroke. 2002;33:1969-1974
doi: 10.1161/01.STR.0000022811.46115.70
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(Stroke. 2002;33:1969.)
© 2002 American Heart Association, Inc.


Original Contributions

Automatic Online Embolus Detection and Artifact Rejection With the First Multifrequency Transcranial Doppler

Rainer Brucher, PhD David Russell, MD

From the Department of Medical Engineering (R.B.), University of Applied Sciences, Ulm, Germany, and the Department of Neurology (D.R.), The National Hospital, Oslo, Norway.

Correspondence to David Russell, Department of Neurology, The National Hospital, 0027 Oslo, Norway. E-mail david.russell{at}klinmed.uio.no

Background and Purpose The goal of this study was to assess the first multifrequency transcranial Doppler system specially developed for online automatic detection of cerebral microemboli.

Methods The multifrequency Doppler instrumentation insonates simultaneously with 2.0- and 2.5-MHz frequencies. The detection threshold for embolus detection used in this study was a relative Doppler energy increase of >20 dB · ms, at which point the Doppler power increase was at least 5 dB and lasted >4 ms above the background energy. Four parameters were used in an optimized binary decision tree to recognize emboli: quarter Doppler shift, maximum duration limit, reference gate, and bidirectional enhancement. In in vitro studies, 200 plastic microspheres (80 µm), 200 gas bubbles (8 to 25 µm), and 600 artifacts were studied in a pulsatile closed-loop system. In vivo studies were carried out for 1 hour in 15 patients with mechanical heart valves and in 45 patients with carotid stenosis. This gave a total of 60 hours of online automatic monitoring in patients.

Results All 400 plastic spheres and microbubbles were automatically detected and correctly classified. Of the 600 artifacts, 596 (99.3%) were correctly classified as artifacts, and 4 (0.7%) were incorrectly identified as emboli ({kappa}=0.992, P<0.001). The experienced observer detected a total of 554 emboli and 800 artifacts in the heart valve (521 emboli, 400 artifacts) and carotid stenosis (33 emboli, 400 artifacts) patients. With multifrequency Doppler, 546 of these emboli (98.6%) and 791 of these artifacts (98.9%) were automatically detected and correctly classified as embolus or artifact ({kappa}=0.953, P<0.0001).

Conclusions We found that multifrequency transcranial Doppler had a relatively high sensitivity and specificity when used to automatically detect cerebral microemboli and reject artifacts online.


Key Words: carotid stenosis • cerebral embolism • mechanical heart valve protheses • ultrasonography, Doppler




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