基于临床数据与循环系统模型融合技术的

doi:10.3969/j.issn.0258-8021. 2016. 01.006

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Abstract The purpose of this study is to identify the key factors that affect the accuracy of patient-specific assessment of cardiovascular function (by means of integration of clinical data and cardiovascular model) and quantify their effects so as to provide theoretical evidence for guiding the clinical application of the assessment method. Parameter sensitivity analysis was performed in combination with parameter subset selection to identify the secondary main parameters that are related closely to the modelbased prediction of hemodynamic variables and the assessment of the main parameters (corresponding to the assessed cardiovascular function). Numerical experiments were carried out based on a series of virtual clinical data to quantify the changes in assessment results induced by measurement errors (in a range of 5%) of clinical data and variations in the secondary main parameters (rate of change being 30%). Measurement errors of clinical data were found to induce pronounced changes in assessment results (up to 16.6%), relatively, variations in the secondary main parameters had less influence on the assessment (rates of changes being within 10%). Accurate clinical data measurement is a key step to guaranteeing the reliability of cardiovascular function assessment. The secondary main parameters only have limited influence on the assessment although they may vary significantly among patients.

Key words： Assessment of cardiovascular function cardiovascular model sensitivity analysis subset selection error analysis

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	Li Yi¹Yin Zhaofang² Liang Fuyou^1#*

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Li Yi¹Yin Zhaofang² Liang Fuyou^1#*. Error Analysis on the Assessment of Cardiovascular Function Based on Integration of Clinical Data and Cardiovascular Model[J]. journal1, 2016, 35(1): 47-54.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021. 2016. 01.006 OR http://cjbme.csbme.org/EN/Y2016/V35/I1/47

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