Computational assessment of hemodynamics-based diagnostic tools using a database of virtual subjects: Application to three case studies

• Published in: Journal of biomechanics Vol. 49; no. 16; pp. 3908 - 3914
• Main Authors: Willemet, Marie, Vennin, Samuel, Alastruey, Jordi
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 08.12.2016; Elsevier Limited; Elsevier Science
• Subjects: 1D modelling; Accuracy; Algorithms; Aortic flow; Arterial hemodynamics; Arteries - physiology; Assessments; Augmentation index; Bias; Blood Pressure; Blood Pressure Determination; Cardiovascular disease; Cardiovascular Diseases - diagnosis; Central pressure; Clinical medicine; Computation; Computer Simulation; Coronary vessels; Estimating; Heart; Hemodynamics; Humans; Mathematical models; Methodology; Physical Medicine and Rehabilitation; Propagation; Pulse Wave Analysis; Pulse wave velocity; Pulse wave velocity; Aortic flow; Arterial hemodynamics; Augmentation index; 1D modelling; Central pressure
• ISSN: 0021-9290; 1873-2380; 1873-2380
• DOI: 10.1016/j.jbiomech.2016.11.001

Many physiological indexes and algorithms based on pulse wave analysis have been suggested in order to better assess cardiovascular function. Because these tools are often computed from in-vivo hemodynamic measurements, their validation is time-consuming, challenging, and biased by measurement errors. Recently, a new methodology has been suggested to assess theoretically these computed tools: a database of virtual subjects generated using numerical 1D-0D modeling of arterial hemodynamics. The generated set of simulations encloses a wide selection of healthy cases that could be encountered in a clinical study. We applied this new methodology to three different case studies that demonstrate the potential of our new tool, and illustrated each of them with a clinically relevant example: (i) we assessed the accuracy of indexes estimating pulse wave velocity; (ii) we validated and refined an algorithm that computes central blood pressure; and (iii) we investigated theoretical mechanisms behind the augmentation index. Our database of virtual subjects is a new tool to assist the clinician: it provides insight into the physical mechanisms underlying the correlations observed in clinical practice.