| Popis: |
Patient-specific one-dimensional (1D) haemodynamic models can support personalized clinical decisions through an improved interpretation of carotid ultrasound (cUS) velocity and diameter waveforms. However, personalized 1D models of the arterial vasculature require the estimation of a large number of parameters from in-vivo measurements, 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, using a systematic method for 1D model reduction, we have shown that the minimum topology required to accurately simulate cUS waveforms varies in virtual subjects of different ages. Using this approach, we have selected age-specific reduced models that retain carotid waveform features with NRMSE |
