Why the study?
Does on-line automatic detection using bigated Doppler software accurately detect clinically silent circulating microemboli compared to off-line expert evaluation in normal volunteers and patients with prosthetic aortic valves?
Does on-line automatic detection using bigated Doppler software accurately detect clinically silent circulating microemboli compared to off-line expert evaluation in normal volunteers and patients with prosthetic aortic valves?
Bigated Doppler software provides moderate sensitivity and specificity for automatic on-line detection of microembolic signals, aiding in the screening of stroke-prone patients.
Moderate automated detection accuracy warrants caution before clinical screening use; leaves open need for prospective validation against expert standards.
BACKGROUND AND PURPOSE: Detection of clinically silent circulating microemboli by transcranial Doppler sonography is now being widely investigated in the hope of identifying patients at increased risk for stroke. Automatic detection by bigated Doppler, which uses sampling from two different depths in the artery under study and considers the motion of the embolus, may help to define "periods of interest" that can be evaluated off-line. METHODS: In 12 normal volunteers and 10 patients with prosthetic aortic valves, we performed 1-hour recordings from one middle cerebral artery. In the normal subjects, we produced additional artifacts to use them as false-positives. Detection of microemboli was done off-line from digital audiotapes by an experienced blinded investigator (used as the gold standard) and was compared with on-line detection using specially designed software. RESULTS: With the setting used, 91.5% of all recorded artifacts could correctly be identified as such with the software. Embolic signals were detected by the software with a specificity of 59.9% and a sensitivity of 74.3%. CONCLUSIONS: Bigated Doppler adds a new dimension to the definition and detection of microembolic signals. It constitutes an important step forward toward automatic screening of stroke-prone patients. Assessing on-line periods of interest during the recording and going over the recorded data again off-line helps to save time for the discrimination of embolic signals from both the normal Doppler spectrum background and artifacts.
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Droste et al. (1997) studied this question.
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