Automated intraoperative detection of Doppler microembolic signals using the Bigate approach

Background and Purpose-We undertook this study to evaluate the performance of an automated detection software in the detection of Doppler microembolic signals (MES) during cardiac surgery. Methods-Intraoperative 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. Results-A 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, kappa was 0.72. Conclusions-The tested software displayed a satisfactory specificity. Provided that the sensitivity is further improved, it could provide a valuable tool in intraoperative monitoring.