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From the Departments of Neurology and of Cardiothoracic Surgery (H.R.Z.),
Martin-Luther University of Halle-Wittenberg, Halle, Germany.
Correspondence to D Georgiadis, MD, Department of Neurology, University of Halle, Ernst-Grube-Str 40, 06122 Halle, Germany. E-mail dimitrios.georgiadis{at}medizin.uni-halle.de
Background and PurposeWe undertook
this study to evaluate the performance of an automated
detection software in the detection of Doppler
microembolic signals (MES) during cardiac
surgery.
MethodsIntraoperative monitoring was performed over two
spatially separated vessel segments of each middle cerebral artery in
18 patients undergoing coronary artery bypass surgery (n=16) or
cardiac valve replacement (n=2). All monitoring sessions were saved on
digital audiotape and subsequently played back to the same ultrasound
machine, set up to automatically detect MES by evaluating the temporary
delay in their appearance between the two segments, in the presence of
an experienced examiner. Software sensitivity and specificity in MES
detection were then evaluated, with the results of the human observer
considered the gold standard.
ResultsA total of 44 933 high-intensity signals (artifacts and
MES) were evaluated. Overall sensitivity and specificity of the
software, with the human observer considered the gold standard, were
64% and 78.5%, respectively, ranging from 54% to 96% and from 74%
to 90% in individual patients. When the overall results of the
software were compared with those of the human observer,
ConclusionsThe tested software displayed a satisfactory
specificity. Provided that the sensitivity is further improved, it
could provide a valuable tool in intraoperative monitoring.
© 1998 American Heart Association, Inc.
Original Contributions
Automated Intraoperative Detection of Doppler Microembolic Signals Using the Bigate Approach
was
0.72.
Key Words: cardiopulmonary bypass embolism ultrasonography, Doppler
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