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Algorithm for the analysis of pre-extraction computed tomographic images to evaluate implanted lead-lead interactions and lead-vascular attachments.
Holm, Mikayle A; Vatterott, Pierce J; Gaasedelen, Erik N; Syed, Imran; Khan, Akbar; Iles, Tinen L; Iaizzo, Paul A.
Afiliação
  • Holm MA; Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota; Department of Surgery, University of Minnesota, Minneapolis, Minnesota.
  • Vatterott PJ; United Heart and Vascular Clinic, St. Paul, Minnesota.
  • Gaasedelen EN; Department of Surgery, University of Minnesota, Minneapolis, Minnesota; Department of Bioinformatics and Computational Biology, University of Minnesota, Minneapolis, Minnesota.
  • Syed I; United Heart and Vascular Clinic, St. Paul, Minnesota.
  • Khan A; United Heart and Vascular Clinic, St. Paul, Minnesota.
  • Iles TL; Department of Surgery, University of Minnesota, Minneapolis, Minnesota; Department of Bioinformatics and Computational Biology, University of Minnesota, Minneapolis, Minnesota; Institute for Engineering in Medicine, University of Minnesota, Minneapolis, Minnesota.
  • Iaizzo PA; Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota; Department of Surgery, University of Minnesota, Minneapolis, Minnesota; Department of Bioinformatics and Computational Biology, University of Minnesota, Minneapolis, Minnesota; Institute for Engineering in Medicin
Heart Rhythm ; 17(6): 1009-1016, 2020 06.
Article em En | MEDLINE | ID: mdl-31931170
BACKGROUND: The number of lead extractions is growing because of the greater population and increasing age of individuals with a cardiac implantable electronic device. Lead extraction procedures can be complex undertakings with risk of significant mortality, and vascular tears in the superior vena cava are of greatest concern. OBJECTIVE: The purpose of this study was to study whether a novel algorithm that analyzes pre-extraction computed tomographic (CT) images can determine the likelihood and location of lead-lead interactions and lead-vessel attachment within patients' venous vasculatures. This information can be used to identify potential case challenges in the planning stages. METHODS: We developed an algorithm to estimate the presence and position of lead-lead interactions and lead-vessel adherences by tracking distance between the leads and distance between the lead and superior vena cava in a sample of 12 patients referred to the United Heart and Vascular Clinic for lead extractions due to infection (n = 5), lead failure (n = 5), and tricuspid regurgitation (n = 2). RESULTS: Preliminary results indicate that the developed algorithm successfully identified lead-lead and lead-vascular attachments compared to review of CT images by medical experts. CONCLUSION: With future validation and clinical implementation, this algorithm could aid physician preparedness by minimizing intraprocedural emergencies and may improve patient outcomes.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Arritmias Cardíacas / Algoritmos / Tomografia Computadorizada por Raios X / Desfibriladores Implantáveis / Remoção de Dispositivo Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Male Idioma: En Revista: Heart Rhythm Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Arritmias Cardíacas / Algoritmos / Tomografia Computadorizada por Raios X / Desfibriladores Implantáveis / Remoção de Dispositivo Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Male Idioma: En Revista: Heart Rhythm Ano de publicação: 2020 Tipo de documento: Article