In Vivo Classification of Oral Lesions Using Electrical Impedance Spectroscopy

The study included 26 participants (median [IQR] age, 64.3 [59 - 70] years; 11 (42%) female) with oral squamous cell carcinoma. Cancerous tissue was found to have significantly lower resistance and reactance than healthy tissue (p<0.0001). Tissue classification using the permittivity at 40 kHz showed the highest accuracy (88%) with an AUC of 0.88. Multiple impedance parameters achieved AUCs >0.85 for differentiating healthy from malignant tissue. Conclusion & Significance: The study indicates that EIS can effectively differentiate between healthy and cancerous oral mucosa through rapid, non-invasive intraoperative measurements. The data processing pipeline developed demonstrates success in maintaining high data quality amidst the external disturbances presented in intraoperative data collection.

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Publication Details

Journal
IEEE Transactions on Biomedical Engineering
Published
2025-06-19
DOI
https://doi.org/10.1109/tbme.2025.3581465
Citations
2
Primary Topic
Electrical and Bioimpedance Tomography
Type
article
Field-Weighted Citation Impact
1.46
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article

In Vivo Classification of Oral Lesions Using Electrical Impedance Spectroscopy

Darcy A. Kerr, Ethan K. Murphy, Torri E. Lee, Ryan J. Halter et al.
2 citations
IEEE Transactions on Biomedical Engineering
Electrical and Bioimpedance Tomography
1.46
article

In Vivo Classification of Oral Lesions Using Electrical Impedance Spectroscopy

Darcy A. Kerr, Ethan K. Murphy, Torri E. Lee, Ryan J. Halter, Joseph A. Paydarfar, Allaire Doussan, Jacob Peter Thönes, Sophie Lloyd
article en
2 citations

Abstract

The study included 26 participants (median [IQR] age, 64.3 [59 - 70] years; 11 (42%) female) with oral squamous cell carcinoma. Cancerous tissue was found to have significantly lower resistance and reactance than healthy tissue (p<0.0001). Tissue classification using the permittivity at 40 kHz showed the highest accuracy (88%) with an AUC of 0.88. Multiple impedance parameters achieved AUCs >0.85 for differentiating healthy from malignant tissue. Conclusion & Significance: The study indicates that EIS can effectively differentiate between healthy and cancerous oral mucosa through rapid, non-invasive intraoperative measurements. The data processing pipeline developed demonstrates success in maintaining high data quality amidst the external disturbances presented in intraoperative data collection.

IEEE Transactions on Biomedical EngineeringVol. 73(1)
Dartmouth College (US), Dartmouth–Hitchcock Medical Center (US), University of Rostock (DE)
Openalex Percentile: Top 17%
Electrical and Bioimpedance Tomography
1.46
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