Dielectric Characterization of Small Breast Biopsy Via Miniaturized Open-Ended Coaxial Probe

Canicattì, Eliana; Sánchez-Bayuela, Daniel Álvarez; Castellano, Cristina Romero; Gonzalez, Ruben Giovanetti; Hernández, Lina Marcela Cruz; Angulo, Paul Martín Aguilar; Martín, Juan Ruiz; Monorchio, Agostino; Tiberi, Gianluigi

doi:10.1109/ap-s/usnc-ursi47032.2022.9886564

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…We extensively investigated the minimum detectable size of a biopsy sample, accounting for variations in their shapes. Initial evaluations indicated a minimum detectable spherical sample size of approximately 4 mm in diameter [29,30]. However, considering that biopsy tissues often have a cylindrical shape, we demonstrated the successful characterization of cylindrical biopsy samples measuring 2 mm (12 G) in diameter, achieving a reconstruction error of less than 9% in determining dielectric properties [31].…”

Section: Introductionmentioning

confidence: 84%

Open-Ended Coaxial Probe for Effective Reconstruction of Biopsy-Excised Tissues’ Dielectric Properties

Canicattì,

Fontana,

Barmada

et al. 2024

Sensors

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Dielectric characterization is extremely promising in medical contexts because it offers insights into the electromagnetic properties of biological tissues for the diagnosis of tumor diseases. This study introduces a promising approach to improve accuracy in the dielectric characterization of millimeter-sized biopsies based on the use of a customized electromagnetic characterization system by adopting a coated open-ended coaxial probe. Our approach aims to accelerate biopsy analysis without sample manipulation. Through comprehensive numerical simulations and experiments, we evaluated the effectiveness of a metal-coating system in comparison to a dielectric coating with the aim for replicating a real scenario: the use of a needle biopsy core with the tissue inside. The numerical analyses highlighted a substantial improvement in the reconstruction of the dielectric properties, particularly in managing the electric field distribution and mitigating fringing field effects. Experimental validation using bovine liver samples revealed highly accurate measurements, particularly in the real part of the permittivity, showing errors lower than 1% compared to the existing literature data. These results represent a significant advancement for the dielectric characterization of biopsy specimens in a rapid, precise, and non-invasive manner. This study underscores the robustness and reliability of our innovative approach, demonstrating the convergence of numerical analyses and empirical validation.

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Section: Introductionmentioning

confidence: 84%

Open-Ended Coaxial Probe for Effective Reconstruction of Biopsy-Excised Tissues’ Dielectric Properties

Canicattì,

Fontana,

Barmada

et al. 2024

Sensors

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“…To ensure accurate measurements, the coaxial probe was slightly pressed against the tissue samples, applying a controlled pressure to eliminate any air gap between the probe tip and the tissue, since it may adversely affect the measurements [ 18 ]. It has been observed in previous studies that the curvature radius affects the coupling between the probe and the tip, leading to inaccuracies in the reconstruction of the dielectric parameters [ 40 , 41 , 42 ]. However, by maintaining a minimal insertion depth of 0.3 mm, it is possible to achieve high precision and accuracy in the dielectric characterization of both healthy and malignant breast tissue using the presented probe.…”

Section: Methodsmentioning

confidence: 99%

Dielectric Characterization of Breast Biopsied Tissues as Pre-Pathological Aid in Early Cancer Detection: A Blinded Feasibility Study

Canicattì,

Sánchez-Bayuela,

Romero Castellano

et al. 2023

Diagnostics

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Dielectric characterization has significant potential in several medical applications, providing valuable insights into the electromagnetic properties of biological tissues for disease diagnosis, treatment planning, and monitoring of therapeutic interventions. This work presents the use of a custom-designed electromagnetic characterization system, based on an open-ended coaxial probe, for discriminating between benign and malignant breast tissues in a clinical setting. The probe’s development involved a well-balanced compromise between physical feasibility and its combined use with a reconstruction algorithm known as the virtual transmission line model (VTLM). Immediately following the biopsy procedure, the dielectric properties of the breast tissues were reconstructed, enabling tissue discrimination based on a rule-of-thumb using the obtained dielectric parameters. A comparative analysis was then performed by analyzing the outcomes of the dielectric investigation with respect to conventional histological results. The experimental procedure took place at Complejo Hospitalario Universitario de Toledo—Hospital Virgen de la Salud, Spain, where excised breast tissues were collected and subsequently analyzed using the dielectric characterization system. A comprehensive statistical evaluation of the probe’s performance was carried out, obtaining a sensitivity, specificity, and accuracy of 81.6%, 61.5%, and 73.4%, respectively, compared to conventional histological assessment, considered as the gold standard in this investigation.

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Automated Breast Tissue Classification through Machine Learning using Dielectric Data

Sánchez-Bayuela

Canicattì

Badia³

et al. 2023

2023 17th European Conference on Antennas and Propagation (EuCAP)

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Dielectric Characterization of Small Breast Biopsy Via Miniaturized Open-Ended Coaxial Probe

Cited by 3 publications

References 7 publications

Open-Ended Coaxial Probe for Effective Reconstruction of Biopsy-Excised Tissues’ Dielectric Properties

Open-Ended Coaxial Probe for Effective Reconstruction of Biopsy-Excised Tissues’ Dielectric Properties

Dielectric Characterization of Breast Biopsied Tissues as Pre-Pathological Aid in Early Cancer Detection: A Blinded Feasibility Study

Automated Breast Tissue Classification through Machine Learning using Dielectric Data

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