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Real-time estimation of cerebrospinal fluid system parameters via oscillating pressure infusion

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Abstract

Hydrocephalus is related to a disturbed cerebrospinal fluid (CSF) system. For diagnosis, lumbar infusion test are performed to estimate outflow conductance, C out, and pressure volume index, PVI, of the CSF system. Infusion patterns and analysis methods used in current clinical practice are not optimized. Minimizing the investigation time with sufficient accuracy is of major clinical relevance. The aim of this study was to propose and experimentally evaluate a new method, the oscillating pressure infusion (OPI). The non-linear model of the CSF system was transformed into a linear time invariant system. Using an oscillating pressure pattern and linear system identification methods, C out and PVI with confidence intervals, were estimated in real-time. Forty-two OPI and constant pressure infusion (CPI) investigations were performed on an experimental CSF system, designed with PVI = 25.5 ml and variable C out. The ARX model robustly estimated C out (mean C out,OPI − C out,CPI = 0.08 μl/(s kPa), n = 42, P = 0.68). The Box–Jenkins model proved most reliable for PVI (23.7 ± 2.0 ml, n = 42). The OPI method, with its oscillating pressure pattern and new parameter estimation methods, efficiently estimated C out and PVI as well as their confidence intervals in real-time. The results from this experimental study show potential for the OPI method and supports further evaluation in a clinical setting.

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Acknowledgments

This project was funded by the Swedish research council, Vinnova, and the Foundation for Strategic Research through their joint initiative Biomedical Engineering for Better Health, and the Objective 2 Norra Norrland—EU Structural Fund.

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Authors and Affiliations

  1. Department of Radiation Sciences, Umeå University, 901-85, Umeå, Sweden

    Kennet Andersson & Anders Eklund

  2. Department of Biomedical Engineering and Informatics, Umeå University Hospital, Umeå, Sweden

    Kennet Andersson & Anders Eklund

  3. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA

    Ian R. Manchester

  4. Department of Applied Physics and Electronics, Umeå University, Umeå, Sweden

    Ian R. Manchester

  5. Department of Clinical Neuroscience, Umeå University, Umeå, Sweden

    Jan Malm

  6. Centre of Biomedical Engineering and Physics, Umeå University, Umeå, Sweden

    Anders Eklund

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  1. Kennet Andersson
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  2. Ian R. Manchester
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  4. Anders Eklund
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Correspondence to Kennet Andersson.

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Andersson, K., Manchester, I.R., Malm, J. et al. Real-time estimation of cerebrospinal fluid system parameters via oscillating pressure infusion. Med Biol Eng Comput 48, 1123–1131 (2010). https://doi.org/10.1007/s11517-010-0670-6

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  • DOI: https://doi.org/10.1007/s11517-010-0670-6

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