title: Automatic classification of HITS into artifacts or solid or gaseous emboli by a wavelet representation combined with dual-gate TCD.
abstract: OBJECTIVE
  Transcranial 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.
  
  
  METHODS
  We 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.
  
  
  RESULTS
  A 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%.
  
  
  CONCLUSIONS
  An 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.
authors.affiliation: Department of Neurology, CHUV, the Signal Processing Laboratory, Swiss Federal Institute of Technology, Lausanne, Geneva, Switzerland. gerald.devuyst@chuv.hospvd.ch
authors.forename: G
authors.initials: G
authors.lastname: Devuyst
authors.forename: G A
authors.initials: GA
authors.lastname: Darbellay
authors.forename: J M
authors.initials: JM
authors.lastname: Vesin
authors.forename: V
authors.initials: V
authors.lastname: Kemény
authors.forename: M
authors.initials: M
authors.lastname: Ritter
authors.forename: D W
authors.initials: DW
authors.lastname: Droste
authors.forename: C
authors.initials: C
authors.lastname: Molina
authors.forename: J
authors.initials: J
authors.lastname: Serena
authors.forename: R
authors.initials: R
authors.lastname: Sztajzel
authors.forename: P
authors.initials: P
authors.lastname: Ruchat
authors.forename: C
authors.initials: C
authors.lastname: Lucchesi
authors.forename: G
authors.initials: G
authors.lastname: Dietler
authors.forename: E B
authors.initials: EB
authors.lastname: Ringelstein
authors.forename: P A
authors.initials: PA
authors.lastname: Despland
authors.forename: J
authors.initials: J
authors.lastname: Bogousslavsky
mesh_terms: D000328:Adult; D000465:Algorithms; D016477:Artifacts; D016893:Carotid Stenosis / Q000150:complications; D006344:Heart Septal Defects, Atrial / Q000150:complications; D006801:Humans; D020766:Intracranial Embolism / Q000145:classification* / Q000150:complications / Q000175:diagnosis*; D008875:Middle Aged; D020768:Middle Cerebral Artery / Q000000981:diagnostic imaging; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D017585:Ultrasonography, Doppler, Transcranial / Q000379:methods*