A Trust-Region Algorithm for Identification of BMI-Related Fat Tissue Properties

A. R. Ynineb; E. Yumuk; G. Ben Othman; H. Farbakhsh; D. Copot; R. De Keyser; S. Ladaci; C. M. Ionescu

doi:10.1007/978-3-031-97950-7_1

A Trust-Region Algorithm for Identification of BMI-Related Fat Tissue Properties

A. R. Ynineb^*
, E. Yumuk
, G. Ben Othman
, H. Farbakhsh
, D. Copot
, R. De Keyser
, S. Ladaci
, C. M. Ionescu

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper introduces a relation between body mass index and fat tissue properties, thereby addressing a significant gap in conventional pharmacokinetic models for non-lean patients affecting patient outcome from long-term anesthesia. We use a Trust-Region algorithm to approximate the risk of drug trapping in fat cells, correlating the body mass index with the ratio of porosity to permeability in fat tissues. By iterative optimum search algorithms, we obtain approximations of a nonlinear function and compare with classical search methods. By providing a model for comorbidity risk associated with body mass index for general anesthesia, we enhance the expected closed-loop performance of any regulatory algorithm making use of this additional information.

Original language	English
Title of host publication	Mathematical Approaches to Challenges in Biology and Biomedicine - ICMASC 2024
Editors	Martin Golubitsky, Stefano Boccaletti, Carla M.A. Pinto
Publisher	Springer
Pages	1-16
Number of pages	16
ISBN (Print)	9783031979491
DOIs	https://doi.org/10.1007/978-3-031-97950-7_1
Publication status	Published - 2025
Externally published	Yes
Event	International Conference on Mathematical Analysis and Applications in Science and Engineering, ICMASC 2024 - Porto, Portugal Duration: 20 Jun 2024 → 22 Jun 2024

Publication series

Name	Springer Proceedings in Mathematics and Statistics
Volume	507 PROMS
ISSN (Print)	2194-1009
ISSN (Electronic)	2194-1017

Conference

Conference	International Conference on Mathematical Analysis and Applications in Science and Engineering, ICMASC 2024
Country/Territory	Portugal
City	Porto
Period	20/06/24 → 22/06/24

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Keywords

BMI
Drug trapping
Pharmacokinetics
Trust-region algorithm

Access to Document

10.1007/978-3-031-97950-7_1

Cite this

Ynineb, A. R., Yumuk, E., Ben Othman, G., Farbakhsh, H., Copot, D., De Keyser, R., Ladaci, S., & Ionescu, C. M. (2025). A Trust-Region Algorithm for Identification of BMI-Related Fat Tissue Properties. In M. Golubitsky, S. Boccaletti, & C. M. A. Pinto (Eds.), Mathematical Approaches to Challenges in Biology and Biomedicine - ICMASC 2024 (pp. 1-16). (Springer Proceedings in Mathematics and Statistics; Vol. 507 PROMS). Springer. https://doi.org/10.1007/978-3-031-97950-7_1

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title = "A Trust-Region Algorithm for Identification of BMI-Related Fat Tissue Properties",

abstract = "This paper introduces a relation between body mass index and fat tissue properties, thereby addressing a significant gap in conventional pharmacokinetic models for non-lean patients affecting patient outcome from long-term anesthesia. We use a Trust-Region algorithm to approximate the risk of drug trapping in fat cells, correlating the body mass index with the ratio of porosity to permeability in fat tissues. By iterative optimum search algorithms, we obtain approximations of a nonlinear function and compare with classical search methods. By providing a model for comorbidity risk associated with body mass index for general anesthesia, we enhance the expected closed-loop performance of any regulatory algorithm making use of this additional information.",

keywords = "BMI, Drug trapping, Pharmacokinetics, Trust-region algorithm",

author = "Ynineb, \{A. R.\} and E. Yumuk and \{Ben Othman\}, G. and H. Farbakhsh and D. Copot and \{De Keyser\}, R. and S. Ladaci and Ionescu, \{C. M.\}",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.; International Conference on Mathematical Analysis and Applications in Science and Engineering, ICMASC 2024 ; Conference date: 20-06-2024 Through 22-06-2024",

year = "2025",

doi = "10.1007/978-3-031-97950-7\_1",

language = "English",

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series = "Springer Proceedings in Mathematics and Statistics",

publisher = "Springer",

pages = "1--16",

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Ynineb, AR, Yumuk, E, Ben Othman, G, Farbakhsh, H, Copot, D, De Keyser, R, Ladaci, S & Ionescu, CM 2025, A Trust-Region Algorithm for Identification of BMI-Related Fat Tissue Properties. in M Golubitsky, S Boccaletti & CMA Pinto (eds), Mathematical Approaches to Challenges in Biology and Biomedicine - ICMASC 2024. Springer Proceedings in Mathematics and Statistics, vol. 507 PROMS, Springer, pp. 1-16, International Conference on Mathematical Analysis and Applications in Science and Engineering, ICMASC 2024, Porto, Portugal, 20/06/24. https://doi.org/10.1007/978-3-031-97950-7_1

A Trust-Region Algorithm for Identification of BMI-Related Fat Tissue Properties. / Ynineb, A. R.; Yumuk, E.; Ben Othman, G. et al.
Mathematical Approaches to Challenges in Biology and Biomedicine - ICMASC 2024. ed. / Martin Golubitsky; Stefano Boccaletti; Carla M.A. Pinto. Springer, 2025. p. 1-16 (Springer Proceedings in Mathematics and Statistics; Vol. 507 PROMS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Yumuk, E.

AU - Ben Othman, G.

AU - Farbakhsh, H.

AU - Copot, D.

AU - De Keyser, R.

AU - Ladaci, S.

AU - Ionescu, C. M.

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PY - 2025

Y1 - 2025

N2 - This paper introduces a relation between body mass index and fat tissue properties, thereby addressing a significant gap in conventional pharmacokinetic models for non-lean patients affecting patient outcome from long-term anesthesia. We use a Trust-Region algorithm to approximate the risk of drug trapping in fat cells, correlating the body mass index with the ratio of porosity to permeability in fat tissues. By iterative optimum search algorithms, we obtain approximations of a nonlinear function and compare with classical search methods. By providing a model for comorbidity risk associated with body mass index for general anesthesia, we enhance the expected closed-loop performance of any regulatory algorithm making use of this additional information.

AB - This paper introduces a relation between body mass index and fat tissue properties, thereby addressing a significant gap in conventional pharmacokinetic models for non-lean patients affecting patient outcome from long-term anesthesia. We use a Trust-Region algorithm to approximate the risk of drug trapping in fat cells, correlating the body mass index with the ratio of porosity to permeability in fat tissues. By iterative optimum search algorithms, we obtain approximations of a nonlinear function and compare with classical search methods. By providing a model for comorbidity risk associated with body mass index for general anesthesia, we enhance the expected closed-loop performance of any regulatory algorithm making use of this additional information.

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Ynineb AR, Yumuk E, Ben Othman G, Farbakhsh H, Copot D, De Keyser R et al. A Trust-Region Algorithm for Identification of BMI-Related Fat Tissue Properties. In Golubitsky M, Boccaletti S, Pinto CMA, editors, Mathematical Approaches to Challenges in Biology and Biomedicine - ICMASC 2024. Springer. 2025. p. 1-16. (Springer Proceedings in Mathematics and Statistics). doi: 10.1007/978-3-031-97950-7_1

A Trust-Region Algorithm for Identification of BMI-Related Fat Tissue Properties

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Bibliographical note

Keywords

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