Frequency filtering improves ultrasonic embolic signal detection.
Problems in detection of Doppler cerebral embolic signals primarily occur for embolic signals of low relative intensity. A characteristic feature of embolic signals is that the intensity increase is maximal over a narrow frequency band. Therefore, frequency filtering of the data might improve embolic signal relative intensity and detectability. We implemented an off-line finite impulse response filter in software running on a commercially available transcranial Doppler system, using the time-domain audio data as input. The range of the filter was chosen by placing a box around the embolic signal on the spectral display. One hundred consecutive embolic signals from patients with carotid stenosis were analyzed; all had been recorded by a bigate system and the signal was analyzed in both proximal and distal channels. There was a highly significant increase in embolic signal relative intensity following frequency filtering; mean (SD) proximal channel prefiltering 12.75 (4.83) dB, postfiltering 16.36 (4.93) dB; distal channel prefiltering 13.42 (4.98) dB, postfiltering 16.60 (5.11) dB, for both p < 0.001. Despite all embolic signals being audible and visible in at least one channel on the frequency spectral display, in 17 cases, the amplitude increase associated with the embolic signal could not be clearly seen in time-domain data of one or both channels prior to filtering. Following frequency filtering, this was reduced to 5. Incorporation of such a frequency-filtering approach to an online system is likely to improve the sensitivity of online detection for embolic signals of low relative intensity.
Department of Clinical Neurosciences, King's College School of Medicine and Dentistry, London, UK. h.markus@iop.kcl.ac.uk
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D016893:Carotid Stenosis / Q000000981:diagnostic imaging; D005374:Filtration / Q000295:instrumentation / Q000379:methods; D005583:Fourier Analysis; D006801:Humans; D002542:Intracranial Embolism and Thrombosis / Q000000981:diagnostic imaging*; D008838:Microcomputers; D015588:Observer Variation; D012984:Software; D013997:Time Factors; D017585:Ultrasonography, Doppler, Transcranial / Q000295:instrumentation / Q000379:methods* / Q000706:statistics & numerical data