期刊论文详细信息
JOURNAL OF BIOMECHANICS 卷:90
Improved biomechanical metrics of cerebral vasospasm identified via sensitivity analysis of a 1D cerebral circulation model
Article
Melis, A.1,2  Moura, F.3  Larrabide, I4  Janot, K.5  Clayton, R. H.1,6  Narata, A. P.5  Marzo, A.1,2 
[1] Univ Sheffield, INSIGNEO Inst Silico Med, Sheffield, S Yorkshire, England
[2] Univ Sheffield, Dept Mech Engn, Sheffield, S Yorkshire, England
[3] Fed Univ ABC, Engn Modeling & Appl Social Sci Ctr, Santo Andre, SP, Brazil
[4] Pladema CONICET UNICEN, Tandil, Argentina
[5] Univ Tours, Univ Hosp Tours, Inserm U930, UMR Imagerie & Cervau, Tours, France
[6] Univ Sheffield, Dept Comp Sci, Sheffield, S Yorkshire, England
关键词: 1D cardiovascular modelling;    Statistical emulator;    Gaussian process;    Vasospasm;    Pulse wave propagation;   
DOI  :  10.1016/j.jbiomech.2019.04.019
来源: Elsevier
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【 摘 要 】

Cerebral vasospasm (CVS) is a life-threatening condition that occurs in a large proportion of those affected by subarachnoid haemorrhage and stroke. CVS manifests itself as the progressive narrowing of intracranial arteries. It is usually diagnosed using Doppler ultrasound, which quantifies blood velocity changes in the affected vessels, but has low sensitivity when CVS affects the peripheral vasculature. The aim of this study was to identify alternative biomarkers that could be used to diagnose CVS. We used a 1D modelling approach to describe the properties of pulse waves that propagate through the cardiovascular system, which allowed the effects of different types of vasospasm on waveforms to be characterised at several locations within a simulated cerebral network. A sensitivity analysis empowered by the use of a Gaussian process statistical emulator was used to identify waveform features that may have strong correlations with vasospasm. We showed that the minimum rate of velocity change can be much more effective than blood velocity for stratifying typical manifestations of vasospasm and its progression. The results and methodology of this study have the potential not only to improve the diagnosis and monitoring of vasospasm, but also to be used in the diagnosis of many other cardiovascular diseases where cardiovascular waves can be decoded to provide disease characterisation. (C) 2020 The Authors. Published by Elsevier Ltd.

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