Determination of a Measurement Procedure for the Study of Cells' Dielectric Properties through Descriptive Statistic.

Livio D'Alvia, Barbara Peruzzi, Ludovica Apa, Zaccaria Del Prete, Emanuele Rizzuto

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Article in Bioengineering (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Livio D'AlviaDepartment of Mechanical and Aerospace Engineering, Sapienza University of Rome, 00184 Rome, Italy.ORCID 0000-0003-2952-5655

Barbara PeruzziBone Physiopathology Research Unit, Bambino Gesù Children's Hospital, IRCCS, 00146 Rome, Italy.

Ludovica ApaDepartment of Mechanical and Aerospace Engineering, Sapienza University of Rome, 00184 Rome, Italy.ORCID 0000-0002-4249-5596

Zaccaria Del PreteDepartment of Mechanical and Aerospace Engineering, Sapienza University of Rome, 00184 Rome, Italy.ORCID 0000-0001-6057-7774

Emanuele RizzutoDepartment of Mechanical and Aerospace Engineering, Sapienza University of Rome, 00184 Rome, Italy.ORCID 0000-0003-2314-6128

Funding

Sapienza University of Rome RM12117A76BE1E97

6 · The paper itself

Abstract

This paper presents a measurement procedure for analyzing the dielectric properties of cells using descriptive statistics. The study focuses on four cancer cell lines (MDA-MB-231 and MCF-7 breast cancer, SaOS-2, and 143B osteosarcoma) and DMEM culture medium, utilizing the Lorentzian fit model of the return-loss function. The measurements are performed using a circular patch resonator with a 40 mm diameter, powered by a miniVNA operating in the frequency range of 1 MHz to 3 GHz. Eight specimens are prepared for each group to ensure reliability, and the return loss is recorded ten times for each specimen. Various statistical parameters are calculated and evaluated, including the average value, standard deviation, coefficient of variation, and relative error between the average and the first values. The results demonstrate that one single acquisition highly represents the entire set of ten data points, especially for the resonant frequency, with an accuracy error lower than 0.05%. These findings have significant implications for the methodological approach to detecting cells' dielectric properties, as they substantially reduce time and preserve the specimens without compromising the accuracy of the experimental results.

Indexed as

biosensorbreast cancercancer cell linesdescriptive statisticdielectric propertiesmetrological evaluationnon-invasive measurementsosteosarcoma

Identifiers

PMID37627792

DOI10.3390/bioengineering10080907

PMCPMC10452017

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LicenceCC BY

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