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A fully automated method for late ventricular diastole frame selection in post-dive echocardiography without ECG gating.
Markley, Erik; Le, David Q; Germonpré, Peter; Balestra, Costantino; Tillmans, Frauke; Denoble, Petar; Freiberger, John J; Moon, Richard E; Dayton, Paul A; Papadopoulou, Virginie.
Afiliação
  • Markley E; Joint Department of Biomedical Engineering, The University of North Carolina at Chapel Hill and North Carolina State University, U.S.
  • Le DQ; Joint Department of Biomedical Engineering, The University of North Carolina at Chapel Hill and North Carolina State University, U.S.
  • Germonpré P; Center for Hyperbaric Oxygen Therapy, Military Hospital Brussels, Belgium.
  • Balestra C; Environmental and Occupational (Integrative) Physiology Laboratory, Haute Ecole Bruxelles-Brabant (HE2B), Brussels, Belgium.
  • Tillmans F; Environmental and Occupational (Integrative) Physiology Laboratory, Haute Ecole Bruxelles-Brabant (HE2B), Brussels, Belgium.
  • Denoble P; European Research Division, Divers Alert Network, Belgium.
  • Freiberger JJ; Divers Alert Network, Durham, North Carolina, U.S.
  • Moon RE; Divers Alert Network, Durham, North Carolina, U.S.
  • Dayton PA; Center for Hyperbaric Medicine and Environmental Physiology, Duke University, North Carolina, U.S.
  • Papadopoulou V; Center for Hyperbaric Medicine and Environmental Physiology, Duke University, North Carolina, U.S.
Undersea Hyperb Med ; 48(1): 73-80, 2021.
Article em En | MEDLINE | ID: mdl-33648036
Venous gas emboli (VGE) are often quantified as a marker of decompression stress on echocardiograms. Bubble-counting has been proposed as an easy to learn method, but remains time-consuming, rendering large dataset analysis impractical. Computer automation of VGE counting following this method has therefore been suggested as a means to eliminate rater bias and save time. A necessary step for this automation relies on the selection of a frame during late ventricular diastole (LVD) for each cardiac cycle of the recording. Since electrocardiograms (ECG) are not always recorded in field experiments, here we propose a fully automated method for LVD frame selection based on regional intensity minimization. The algorithm is tested on 20 previously acquired echocardiography recordings (from the original bubble-counting publication), half of which were acquired at rest (Rest) and the other half after leg flexions (Flex). From the 7,140 frames analyzed, sensitivity was found to be 0.913 [95% CI: 0.875-0.940] and specificity 0.997 [95% CI: 0.996-0.998]. The method's performance is also compared to that of random chance selection and found to perform significantly better (p≺0.0001). No trend in algorithm performance was found with respect to VGE counts, and no significant difference was found between Flex and Rest (p>0.05). In conclusion, full automation of LVD frame selection for the purpose of bubble counting in post-dive echocardiography has been established with excellent accuracy, although we caution that high quality acquisitions remain paramount in retaining high reliability.
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Algoritmos / Ecocardiografia / Função Ventricular / Diagnóstico por Computador / Mergulho / Embolia Aérea Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Revista: Undersea Hyperb Med Assunto da revista: FISIOLOGIA Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Algoritmos / Ecocardiografia / Função Ventricular / Diagnóstico por Computador / Mergulho / Embolia Aérea Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Revista: Undersea Hyperb Med Assunto da revista: FISIOLOGIA Ano de publicação: 2021 Tipo de documento: Article