Early thrombus detection in ECMO with optimized impedance measurements: A simulative study

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00385862" target="_blank" >RIV/68407700:21230/25:00385862 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.2478/joeb-2025-0011" target="_blank" >https://doi.org/10.2478/joeb-2025-0011</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.2478/joeb-2025-0011" target="_blank" >10.2478/joeb-2025-0011</a>

Result language

angličtina

Original language name

Early thrombus detection in ECMO with optimized impedance measurements: A simulative study

Original language description

Extracorporeal oxygenation supports patients with severe cardiac or respiratory failure, with the oxygenator providing critical gas exchange. Thrombus formation in the oxygenator can impair efficiency and increase risks such as hemolysis and embolism, but existing detection methods are limited in accuracy and timeliness. This study introduces a computational bioimpedance approach for early thrombus detection that integrates advanced modeling and machine learning techniques while preserving the oxygenator’s functionality. We developed a finite element model of an oxygenator to simulate bioimpedance measurements using varied electrode configurations. Neural networks optimized electrode placement and injection-measurement patterns, enhancing sensitivity to conductivity changes. A second neural network was trained on simulated data to distinguish between normal and thrombus-affected conditions, achieving an F1-score exceeding 94% in classification tasks. Simulations demonstrated the feasibility of this method, with optimized configurations significantly improving detection accuracy. The findings suggest that computational bioimpedance, combined with neural network optimization, provides a robust framework for automated thrombus detection inside an oxygenator.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

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OECD FORD branch

20201 - Electrical and electronic engineering

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Journal of Electrical Bioimpedance

ISSN

1891-5469

e-ISSN

1891-5469

Volume of the periodical

16

Issue of the periodical within the volume

1

Country of publishing house

NO - NORWAY

Number of pages

9

Pages from-to

80-88

UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-105012384093