Comparison of stenosis models for usage in the estimation of pressure gradient across aortic coarctation.

Aortic coarctation Bernoulli loss Entrance effect Poiseuille loss Pressure gradient Stenosis model

Journal

Journal of biological physics
ISSN: 1573-0689
Titre abrégé: J Biol Phys
Pays: Netherlands
ID NLM: 0417731

Informations de publication

Date de publication:
06 2021
Historique:
received: 16 01 2021
accepted: 27 04 2021
pubmed: 27 5 2021
medline: 29 10 2021
entrez: 26 5 2021
Statut: ppublish

Résumé

Non-invasive estimation of the pressure gradient in cardiovascular stenosis has much clinical importance in assisting the diagnosis and treatment of stenotic diseases. In this research, a systematic comparison is conducted to investigate the accuracy of a group of stenosis models against the MRI- and catheter-measured patient data under the aortic coarctation condition. Eight analytical stenosis models, including six from the literature and two proposed in this study, are investigated to examine their prediction accuracy against the clinical data. The two improved models proposed in this study consider comprehensively the Poiseuille loss, the Bernoulli loss in its exact form, and the entrance effect, of the blood flow. Comparison of the results shows that one of the proposed models demonstrates a cycle-averaged mean prediction error of -0.15 ± 3.03 mmHg, a peak-to-peak prediction error of -1.8 ± 6.89 mmHg, which is the best among the models studied.

Identifiants

pubmed: 34036473
doi: 10.1007/s10867-021-09572-x
pii: 10.1007/s10867-021-09572-x
pmc: PMC8184908
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

171-190

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Auteurs

Yubing Shi (Y)

Institute of Integrative Medicine, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, People's Republic of China.
Mathematics and Modelling in Medicine Group, Department of Infection Immunity and Cardiovascular Disease, Faculty of Medicine, Dentistry and Health, University of Sheffield, Sheffield, S10 2RX, UK.

Israel Valverde (I)

Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.
Department of Paediatric and Adult Congenital Heart Disease, Guy's and St Thomas' NHS Foundation Trust, London, UK.
Cardiovascular Pathology Unit, Institute of Biomedicine of Seville, Hospital Virgen de Rocio/CSIC/University of Seville, Seville, Spain.

Patricia V Lawford (PV)

Mathematics and Modelling in Medicine Group, Department of Infection Immunity and Cardiovascular Disease, Faculty of Medicine, Dentistry and Health, University of Sheffield, Sheffield, S10 2RX, UK.
Insigneo Institute for in silico Medicine, Sheffield, UK.

Heynric B Grotenhuis (HB)

Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.
Department of Paediatric and Adult Congenital Heart Disease, Guy's and St Thomas' NHS Foundation Trust, London, UK.

Philipp Beerbaum (P)

Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.
Department of Paediatric and Adult Congenital Heart Disease, Guy's and St Thomas' NHS Foundation Trust, London, UK.
Clinic for Paediatric Cardiology and Paediatric Intensive Care Medicine, University Children's Hospital, Hannover Medical University, Hannover, Germany.

D Rodney Hose (DR)

Mathematics and Modelling in Medicine Group, Department of Infection Immunity and Cardiovascular Disease, Faculty of Medicine, Dentistry and Health, University of Sheffield, Sheffield, S10 2RX, UK. d.r.hose@sheffield.ac.uk.
Insigneo Institute for in silico Medicine, Sheffield, UK. d.r.hose@sheffield.ac.uk.

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