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A canonical correlation analysis of the relationship between clinical attributes and patient-specific hemodynamic indices in adult pulmonary hypertension.
Piskin, Senol; Patnaik, Sourav S; Han, David; Bordones, Alifer D; Murali, Srinivas; Finol, Ender A.
Afiliação
  • Piskin S; Department of Mechanical Engineering, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA; Department of Mechanical Engineering, Istinye University, Zeytinburnu, Istanbul 34010, Turkey.
  • Patnaik SS; Department of Mechanical Engineering, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA. Electronic address: sourav.patnaik@utsa.edu.
  • Han D; Department of Management Science and Statistics, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA. Electronic address: david.han@utsa.edu.
  • Bordones AD; Department of Biomedical Engineering, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA. Electronic address: alifer.bordonesgonzalez@utsa.edu.
  • Murali S; Department of Radiology and Department of Cardiology, Allegheny General Hospital, Allegheny Health Network, Pittsburgh, PA 15212, USA. Electronic address: srinivas.murali@ahn.org.
  • Finol EA; Department of Mechanical Engineering, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA. Electronic address: ender.finol@utsa.edu.
Med Eng Phys ; 77: 1-9, 2020 03.
Article em En | MEDLINE | ID: mdl-32007361
Pulmonary hypertension (PH) is a progressive disease affecting approximately 10-52 cases per million, with a higher incidence in women, and with a high mortality associated with right ventricle (RV) failure. In this work, we explore the relationship between hemodynamic indices, calculated from in silico models of the pulmonary circulation, and clinical attributes of RV workload and pathological traits. Thirty-four patient-specific pulmonary arterial tree geometries were reconstructed from computed tomography angiography images and used for volume meshing for subsequent computational fluid dynamics (CFD) simulations. Data obtained from the CFD simulations were post-processed resulting in hemodynamic indices representative of the blood flow dynamics. A retrospective review of medical records was performed to collect the clinical variables measured or calculated from standard hospital examinations. Statistical analyses and canonical correlation analysis (CCA) were performed for the clinical variables and hemodynamic indices. Systolic pulmonary artery pressure (sPAP), diastolic pulmonary artery pressure (dPAP), cardiac output (CO), and stroke volume (SV) were moderately correlated with spatially averaged wall shear stress (0.60 ≤ R2 ≤ 0.66; p < 0.05). Similarly, the CCA revealed a linear and strong relationship (ρ = 0.87; p << 0.001) between 5 clinical variables and 2 hemodynamic indices. To this end, in silico models of PH blood flow dynamics have a high potential for predicting the relevant clinical attributes of PH if analyzed in a group-wise manner using CCA.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Modelagem Computacional Específica para o Paciente / Hemodinâmica / Hipertensão Pulmonar Tipo de estudo: Prognostic_studies Limite: Adult / Humans Idioma: En Revista: Med Eng Phys Assunto da revista: BIOFISICA / ENGENHARIA BIOMEDICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Turquia País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Modelagem Computacional Específica para o Paciente / Hemodinâmica / Hipertensão Pulmonar Tipo de estudo: Prognostic_studies Limite: Adult / Humans Idioma: En Revista: Med Eng Phys Assunto da revista: BIOFISICA / ENGENHARIA BIOMEDICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Turquia País de publicação: Reino Unido