• Stroke · Dec 2001

    Clinical Trial Controlled Clinical Trial

    Automatic classification of HITS into artifacts or solid or gaseous emboli by a wavelet representation combined with dual-gate TCD.

    • G Devuyst, G A Darbellay, J M Vesin, V Kemény, M Ritter, D W Droste, C Molina, J Serena, R Sztajzel, P Ruchat, C Lucchesi, G Dietler, E B Ringelstein, P A Despland, and J Bogousslavsky.
    • Department of Neurology, CHUV, the Signal Processing Laboratory, Swiss Federal Institute of Technology, Lausanne, Geneva, Switzerland. gerald.devuyst@chuv.hospvd.ch
    • Stroke. 2001 Dec 1; 32 (12): 2803-9.

    Background And PurposeTranscranial Doppler (TCD) can detect high-intensity transient signals (HITS) in the cerebral circulation. HITS may correspond to artifacts or solid or gaseous emboli. The aim of this study was to develop an offline automated Doppler system allowing the classification of HITS.MethodsWe studied 600 HITS in vivo, including 200 artifacts from normal subjects, 200 solid emboli from patients with symptomatic internal carotid artery stenosis, and 200 gaseous emboli in stroke patients with patent foramen ovale. The study was 2-fold, each part involving 300 HITS (100 of each type). The first 300 HITS (learning set) were used to construct an automated classification algorithm. The remaining 300 HITS (validation set) were used to check the validity of this algorithm. To classify HITS, we combined dual-gate TCD with a wavelet representation and compared it with the current "gold standard," the human experts.ResultsA combination of the peak frequency of HITS and the time delay makes it possible to separate artifacts from emboli. On the validation set, we achieved a sensitivity of 97%, a specificity of 98%, a positive predictive value (PPV) of 99%, and a negative predictive value (NPV) of 94%. To distinguish between solid and gaseous emboli, where positive refers now to the solid emboli, we used the peak frequency, the relative power, and the envelope symmetry of HITS. On the validation set, we achieved a sensitivity of 89%, a specificity of 86%, a conditional PPV of 89%, and a conditional NPV of 89%.ConclusionsAn automated wavelet representation combined with dual-gate TCD can reliably reject artifacts from emboli. From a clinical standpoint, however, this approach has only a fair accuracy in differentiating between solid and gaseous emboli.

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