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Session: Poster session 2 (Odd numbers)
Session starts: Friday 27 January, 10:00
Presentation starts: 10:00

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Irene Suriani ()
Massimo Mischi ()
R. Arthur Bouwman ()
Kevin D. Lau ()

Abstract:
Patient-specific one-dimensional (1D) haemodynamic models can support personalized clinical decisions through an improved interpretation of carotid ultrasound (cUS) velocity and diameter waveforms [1]. However, personalized 1D models of the arterial vasculature require the estimation of a large number of parameters from in-vivo measurements (e.g., vessel lengths, diameters, compliances) [2], some often not readily available in most clinical settings. In such cases, we are confronted with a problem of complexity optimization: what is the minimum required 1D topology (i.e., the number of 1D arterial branches included in the model network) such that the least possible number of parameters are to be assumed, while still being able to accurately capture characteristic cUS waveform features? In this work, pulsatile haemodynamics were simulated by solving the 1D blood flow equations with an elastic tube law using the NEKTAR++ Pulse Wave Solver. Using a systematic method for 1D model reduction, starting from a clinically validated 55-branch baseline topology [3], we have shown that the minimum topology required to accurately simulate cUS waveforms varies in virtual subjects of different ages [4]. Using this approach, we have selected age-specific reduced models that retain carotid waveform features with NRMSE <4% for velocity and <0.15% for diameter, while reducing the initial parameter set by more than half. Finally, we have used wave power analysis to elucidate the location of origin of reflected waves responsible for cUS waveform features, and investigated the effect of model reduction on these. This work sets the basis for the generation of patient-specific 1D models for the study of carotid haemodynamics in subjects of different ages. [1] I. Suriani, et al., “Carotid Doppler ultrasound for non-invasive haemodynamic monitoring: a narrative review,” Physiological Measurement, Accepted Manuscript, 2020. [2] J. Alastruey, et al., “On the impact of modelling assumptions in multi-scale, subject-specific models of aortic haemodynamics,” J. R. Soc. Interface, vol. 13, no. 119, 2016. [3] J. Alastruey, et al., “Arterial pulse wave haemodynamics,” in 11th International Conference on Pressure Surges, 2012, pp. 401–443. [4] I. Suriani, et al., “Development, validation and uses of an age-specific virtual population for the study of carotid haemodynamics,” Manuscript in Preparation.