This study presents SmartProbe, an electrical bioimpedance (EBI) sensing system based on a concentric needle electrode (CNE). The system allows the use commercial CNEs for accurate EBI measurement, and was specially developed for in-vivo real-time cancer detection. Considering the uncertainties in EBI measurements due to the CNE manufacturing tolerances, we propose a calibration method based on statistical learning. This is done by extracting the correlation between the measured impedance value |Z| and the material conductivity σ of a group of reference materials. By utilizing this correlation, the relationship of σ and |Z| can be described as a function and reconstructed using a single measurement on a reference material of known conductivity. This method simplifies the calibration process, and is verified experimentally. Its effectiveness is demonstrate by results that show less than 6% relative error. An additional experiment is conducted for evaluating the system's capability to detect cancerous tissue. Four types of ex-vivo human tissue from the head and neck region, including mucosa, muscle, cartilage and salivary gland, are characterized using SmartProbe. The measurements include both cancer and surrounding healthy tissue excised from 10 different patients operated for head and neck cancer. The measured data is then processed using dimension reduction and analyzed for tissue classification. The final results show significant differences between pathologic and healthy tissues in muscle, mucosa and cartilage specimens. These results are highly promising and indicate a great potential for SmartProbe to be used in various cancer detection tasks.

SmartProbe: a bioimpedance sensing system for head and neck cancer tissue detection

Cheng, Zhuoqi;Carobbio, Andrea Luigi Camillo;Guastini, Luca;Mora, Francesco;Fragale, Marco;Ascoli, Alessandro;Africano, Stefano;Canevari, Frank Rikki Mauritz;Parrinello, Giampiero;Peretti, Giorgio;
2020

Abstract

This study presents SmartProbe, an electrical bioimpedance (EBI) sensing system based on a concentric needle electrode (CNE). The system allows the use commercial CNEs for accurate EBI measurement, and was specially developed for in-vivo real-time cancer detection. Considering the uncertainties in EBI measurements due to the CNE manufacturing tolerances, we propose a calibration method based on statistical learning. This is done by extracting the correlation between the measured impedance value |Z| and the material conductivity σ of a group of reference materials. By utilizing this correlation, the relationship of σ and |Z| can be described as a function and reconstructed using a single measurement on a reference material of known conductivity. This method simplifies the calibration process, and is verified experimentally. Its effectiveness is demonstrate by results that show less than 6% relative error. An additional experiment is conducted for evaluating the system's capability to detect cancerous tissue. Four types of ex-vivo human tissue from the head and neck region, including mucosa, muscle, cartilage and salivary gland, are characterized using SmartProbe. The measurements include both cancer and surrounding healthy tissue excised from 10 different patients operated for head and neck cancer. The measured data is then processed using dimension reduction and analyzed for tissue classification. The final results show significant differences between pathologic and healthy tissues in muscle, mucosa and cartilage specimens. These results are highly promising and indicate a great potential for SmartProbe to be used in various cancer detection tasks.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1007377
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