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

Author:

Carobbio Andrea Luigi Camillo123ORCID,Cheng Zhuoqi4,Gianiorio Tomaso5,Missale Francesco167ORCID,Africano Stefano12,Ascoli Alessandro12ORCID,Fragale Marco12,Filauro Marta18ORCID,Marchi Filippo12ORCID,Guastini Luca12,Mora Francesco12,Parrinello Giampiero1,Canevari Frank Rikki Mauritz12ORCID,Peretti Giorgio12,Mattos Leonardo S.5ORCID

Affiliation:

1. IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy

2. Department of Surgical Sciences and Integrated Diagnostics (DISC), University of Genoa, 16132 Genoa, Italy

3. Section of Otorhinolaryngology-Head and Neck Surgery, Department of Neurosciences, University of Padua-“Azienda Ospedaliera di Padova”, 35128 Padua, Italy

4. Maersk Mc-Kinney Moller Institute, University of Southern Denmark, 5230 Odense, Denmark

5. Department of Advanced Robotics, Istituto Italiano di Tecnologia, 16163 Genova, Italy

6. Department of Molecular and Translational Medicine, University of Brescia, 25125 Brescia, Italy

7. Department of Head & Neck Oncology & Surgery, Antoni Van Leeuwenhoek, Nederlands Kanker Instituut, 1066 Amsterdam, The Netherlands

8. Department of Experimental Medicine (DIMES), University of Genoa, 16132 Genoa, Italy

Abstract

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.

Publisher

MDPI AG

Subject

Clinical Biochemistry

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