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Electric Bioimpedance Sensing for the Detection of Head and Neck Squamous Cell Carcinoma

The early detection of head and neck squamous cell carcinoma (HNSCC) is essential to improve patient prognosis and enable organ and function preservation treatments. The objective of this study is to assess the feasibility of using electrical bioimpedance (EBI) sensing technology to detect HNSCC tis...

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Autores principales: Carobbio, Andrea Luigi Camillo, Cheng, Zhuoqi, Gianiorio, Tomaso, Missale, Francesco, Africano, Stefano, Ascoli, Alessandro, Fragale, Marco, Filauro, Marta, Marchi, Filippo, Guastini, Luca, Mora, Francesco, Parrinello, Giampiero, Canevari, Frank Rikki Mauritz, Peretti, Giorgio, Mattos, Leonardo S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10377945/
https://www.ncbi.nlm.nih.gov/pubmed/37510197
http://dx.doi.org/10.3390/diagnostics13142453
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author Carobbio, Andrea Luigi Camillo
Cheng, Zhuoqi
Gianiorio, Tomaso
Missale, Francesco
Africano, Stefano
Ascoli, Alessandro
Fragale, Marco
Filauro, Marta
Marchi, Filippo
Guastini, Luca
Mora, Francesco
Parrinello, Giampiero
Canevari, Frank Rikki Mauritz
Peretti, Giorgio
Mattos, Leonardo S.
author_facet Carobbio, Andrea Luigi Camillo
Cheng, Zhuoqi
Gianiorio, Tomaso
Missale, Francesco
Africano, Stefano
Ascoli, Alessandro
Fragale, Marco
Filauro, Marta
Marchi, Filippo
Guastini, Luca
Mora, Francesco
Parrinello, Giampiero
Canevari, Frank Rikki Mauritz
Peretti, Giorgio
Mattos, Leonardo S.
author_sort Carobbio, Andrea Luigi Camillo
collection PubMed
description The early detection of head and neck squamous cell carcinoma (HNSCC) is essential to improve patient prognosis and enable organ and function preservation treatments. The objective of this study is to assess the feasibility of using electrical bioimpedance (EBI) sensing technology to detect HNSCC tissue. A prospective study was carried out analyzing tissue from 46 patients undergoing surgery for HNSCC. The goal was the correct identification of pathologic tissue using a novel needle-based EBI sensing device and AI-based classifiers. Considering the data from the overall patient cohort, the system achieved accuracies between 0.67 and 0.93 when tested on tissues from the mucosa, skin, muscle, lymph node, and cartilage. Furthermore, when considering a patient-specific setting, the accuracy range increased to values between 0.82 and 0.95. This indicates that more reliable results may be achieved when considering a tissue-specific and patient-specific tissue assessment approach. Overall, this study shows that EBI sensing may be a reliable technology to distinguish pathologic from healthy tissue in the head and neck region. This observation supports the continuation of this research on the clinical use of EBI-based devices for early detection and margin assessment of HNSCC.
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spelling pubmed-103779452023-07-29 Electric Bioimpedance Sensing for the Detection of Head and Neck Squamous Cell Carcinoma Carobbio, Andrea Luigi Camillo Cheng, Zhuoqi Gianiorio, Tomaso Missale, Francesco Africano, Stefano Ascoli, Alessandro Fragale, Marco Filauro, Marta Marchi, Filippo Guastini, Luca Mora, Francesco Parrinello, Giampiero Canevari, Frank Rikki Mauritz Peretti, Giorgio Mattos, Leonardo S. Diagnostics (Basel) Article The early detection of head and neck squamous cell carcinoma (HNSCC) is essential to improve patient prognosis and enable organ and function preservation treatments. The objective of this study is to assess the feasibility of using electrical bioimpedance (EBI) sensing technology to detect HNSCC tissue. A prospective study was carried out analyzing tissue from 46 patients undergoing surgery for HNSCC. The goal was the correct identification of pathologic tissue using a novel needle-based EBI sensing device and AI-based classifiers. Considering the data from the overall patient cohort, the system achieved accuracies between 0.67 and 0.93 when tested on tissues from the mucosa, skin, muscle, lymph node, and cartilage. Furthermore, when considering a patient-specific setting, the accuracy range increased to values between 0.82 and 0.95. This indicates that more reliable results may be achieved when considering a tissue-specific and patient-specific tissue assessment approach. Overall, this study shows that EBI sensing may be a reliable technology to distinguish pathologic from healthy tissue in the head and neck region. This observation supports the continuation of this research on the clinical use of EBI-based devices for early detection and margin assessment of HNSCC. MDPI 2023-07-24 /pmc/articles/PMC10377945/ /pubmed/37510197 http://dx.doi.org/10.3390/diagnostics13142453 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Carobbio, Andrea Luigi Camillo
Cheng, Zhuoqi
Gianiorio, Tomaso
Missale, Francesco
Africano, Stefano
Ascoli, Alessandro
Fragale, Marco
Filauro, Marta
Marchi, Filippo
Guastini, Luca
Mora, Francesco
Parrinello, Giampiero
Canevari, Frank Rikki Mauritz
Peretti, Giorgio
Mattos, Leonardo S.
Electric Bioimpedance Sensing for the Detection of Head and Neck Squamous Cell Carcinoma
title Electric Bioimpedance Sensing for the Detection of Head and Neck Squamous Cell Carcinoma
title_full Electric Bioimpedance Sensing for the Detection of Head and Neck Squamous Cell Carcinoma
title_fullStr Electric Bioimpedance Sensing for the Detection of Head and Neck Squamous Cell Carcinoma
title_full_unstemmed Electric Bioimpedance Sensing for the Detection of Head and Neck Squamous Cell Carcinoma
title_short Electric Bioimpedance Sensing for the Detection of Head and Neck Squamous Cell Carcinoma
title_sort electric bioimpedance sensing for the detection of head and neck squamous cell carcinoma
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10377945/
https://www.ncbi.nlm.nih.gov/pubmed/37510197
http://dx.doi.org/10.3390/diagnostics13142453
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