title: A comprehensive study on different modelling approaches to predict platelet deposition rates in a perfusion chamber.
abstract: Thrombus formation is a multiscale phenomenon triggered by platelet deposition over a protrombotic surface (eg. a ruptured atherosclerotic plaque). Despite the medical urgency for computational tools that aid in the early diagnosis of thrombotic events, the integration of computational models of thrombus formation at different scales requires a comprehensive understanding of the role and limitation of each modelling approach. We propose three different modelling approaches to predict platelet deposition. Specifically, we consider measurements of platelet deposition under blood flow conditions in a perfusion chamber for different time periods (3, 5, 10, 20 and 30 minutes) at shear rates of 212 s(-1), 1390 s(-1) and 1690 s(-1). Our modelling approaches are: i) a model based on the mass-transfer boundary layer theory; ii) a machine-learning approach; and iii) a phenomenological model. The results indicate that the three approaches on average have median errors of 21%, 20.7% and 14.2%, respectively. Our study demonstrates the feasibility of using an empirical data set as a proxy for a real-patient scenario in which practitioners have accumulated data on a given number of patients and want to obtain a diagnosis for a new patient about whom they only have the current observation of a certain number of variables.
authors.affiliation: Department of Mechanical Engineering, Universitat Rovira i Virgili, Tarragona, Av Paїsos Catalans 26, 43007, Spain.
authors.forename: Jordi
authors.initials: J
authors.lastname: Pallarès
authors.affiliation: Department of Chemical Engineering, Universitat Rovira i Virgili, Tarragona, Av Paїsos Catalans 26, 43007, Spain.
authors.forename: Oriol
authors.initials: O
authors.lastname: Senan
authors.affiliation: Department of Chemical Engineering, Universitat Rovira i Virgili, Tarragona, Av Paїsos Catalans 26, 43007, Spain.|Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Passeig Lluís Companys 10, 08010, Spain.
authors.forename: Roger
authors.initials: R
authors.lastname: Guimerà
authors.affiliation: Department of Mechanical Engineering, Universitat Rovira i Virgili, Tarragona, Av Paїsos Catalans 26, 43007, Spain.
authors.forename: Anton
authors.initials: A
authors.lastname: Vernet
authors.affiliation: Department of Chemical Engineering, Universitat Rovira i Virgili, Tarragona, Av Paїsos Catalans 26, 43007, Spain.
authors.forename: Antoni
authors.initials: A
authors.lastname: Aguilar-Mogas
authors.affiliation: Catalan Institute of Cardiovascular Sciences, CSIC-ICCC, Hospital de la Santa Creu i Sant Pau, Barcelona, Sant Antoni Maria Claret 167, 08025 Spain.
authors.forename: Gemma
authors.initials: G
authors.lastname: Vilahur
authors.affiliation: Catalan Institute of Cardiovascular Sciences, CSIC-ICCC, Hospital de la Santa Creu i Sant Pau, Barcelona, Sant Antoni Maria Claret 167, 08025 Spain.
authors.forename: Lina
authors.initials: L
authors.lastname: Badimon
authors.affiliation: Department of Chemical Engineering, Universitat Rovira i Virgili, Tarragona, Av Paїsos Catalans 26, 43007, Spain.
authors.forename: Marta
authors.initials: M
authors.lastname: Sales-Pardo
authors.affiliation: University of Helsinki, Faculty of Pharmacy, Helsinki, Viikinkaari 9 00014, Finland.
authors.forename: Salvatore
authors.initials: S
authors.lastname: Cito
mesh_terms: D000465:Algorithms; D001792:Blood Platelets / Q000502:physiology*; D003198:Computer Simulation; D006801:Humans; D008962:Models, Theoretical; D010974:Platelet Aggregation; D015203:Reproducibility of Results; D013927:Thrombosis