A multi-objective optimisation approach for the linear modelling of cerebral autoregulation system

Dynamic cerebral autoregulation (dCA) has been addressed through different approaches for discriminating between normal and impaired conditions based on spontaneous fluctuations in arterial blood pressure (ABP) and cerebral blood flow (CF). This work presents a novel multi-objective optimisation (MO...

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Bibliographic Details
Published in:BioSystems 2024-07, Vol.241, p.105231-105231, Article 105231
Main Authors: Bello-Robles, Felipe-Andrés, Villalobos-Cid, Manuel, Chacón, Max, Inostroza-Ponta, Mario
Format: Article
Language:English
Subjects:
Cerebral autoregulation
Multi-objective optimisation
NSGA-II
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Summary:Dynamic cerebral autoregulation (dCA) has been addressed through different approaches for discriminating between normal and impaired conditions based on spontaneous fluctuations in arterial blood pressure (ABP) and cerebral blood flow (CF). This work presents a novel multi-objective optimisation (MO) approach for finding good configurations of a cerebrovascular resistance-compliance model. Data from twenty-nine subjects under normo and hypercapnic (5% CO2 in air) conditions was used. Cerebrovascular resistance and vessel compliance models with ABP as input and CF velocity as output were fitted using a MO approach, considering fitting Pearson’s correlation and error. MO approach finds better model configurations than the single-objective (SO) approach, especially for hypercapnic conditions. In addition, the Pareto-optimal front from the multi-objective approach enables new information on dCA, reflecting a higher contribution of myogenic mechanism for explaining dCA impairment.
ISSN:0303-2647
1872-8324
DOI:10.1016/j.biosystems.2024.105231