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Titolo:
Automatic classification of HITS into artifacts or solid or gaseous emboliby a wavelet representation combined with dual-gate TCD
Autore:
Devuyst, G; Darbellay, GA; Vesin, JM; Kemeny, V; Ritter, M; Droste, DW; Molina, C; Serena, J; Sztajzel, R; Ruchat, P; Lucchesi, C; Dietler, G; Ringelstein, EB; Despland, PA; Bogousslavsky, J;
Indirizzi:
CHU Vaudois, Dept Neurol, CH-1011 Lausanne, Switzerland CHU Vaudois Lausanne Switzerland CH-1011 , CH-1011 Lausanne, Switzerland Swiss Fed Inst Technol, Signal Proc Lab, CH-1015 Lausanne, Switzerland Swiss Fed Inst Technol Lausanne Switzerland CH-1015 ausanne, Switzerland UNIL, Dept Appl Phys, Lausanne, Switzerland UNIL Lausanne SwitzerlandUNIL, Dept Appl Phys, Lausanne, Switzerland HCUG, Dept Neurol, Geneva, Switzerland HCUG Geneva SwitzerlandHCUG, Dept Neurol, Geneva, Switzerland Univ Hosp, Dept Neurol, Munster, Germany Univ Hosp Munster GermanyUniv Hosp, Dept Neurol, Munster, Germany Univ Hosp, Dept Neurol, Barcelona, Spain Univ Hosp Barcelona SpainUniv Hosp, Dept Neurol, Barcelona, Spain Univ Hosp, Dept Neurol, Girona, Spain Univ Hosp Girona SpainUniv Hosp, Dept Neurol, Girona, Spain
Titolo Testata:
STROKE
fascicolo: 12, volume: 32, anno: 2001,
pagine: 2803 - 2809
SICI:
0039-2499(200112)32:12<2803:ACOHIA>2.0.ZU;2-U
Fonte:
ISI
Lingua:
ENG
Soggetto:
CAROTID-ARTERY STENOSIS; INTENSITY TRANSIENT SIGNALS; TRANSCRANIAL DOPPLER; CEREBRAL MICROEMBOLISM; NEURAL-NETWORK; REAL-TIME; ULTRASOUND; ENDARTERECTOMY; STROKE; RISK;
Keywords:
HITS; solid/gaseous emboli; automated system; dual-gate TCD; wavelets;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Clinical Medicine
Life Sciences
Citazioni:
37
Recensione:
Indirizzi per estratti:
Indirizzo: Devuyst, G CHU Vaudois, Dept Neurol, Rue Bugnon 15, CH-1011 Lausanne, Switzerland CHU Vaudois Rue Bugnon 15 Lausanne Switzerland CH-1011 zerland
Citazione:
G. Devuyst et al., "Automatic classification of HITS into artifacts or solid or gaseous emboliby a wavelet representation combined with dual-gate TCD", STROKE, 32(12), 2001, pp. 2803-2809

Abstract

Background and Purpose-Transcranial Doppler (TCD) can detect high-intensity transient signals (HITS) in the cerebral circulation. HITS may correspondto 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 automatedclassification 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, weachieved a sensitivity of 97%, a specificity of 98%, a positive predictivevalue (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 of89%. 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.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 23/01/21 alle ore 03:44:35