TY - JOUR
T1 - SmartProbe
T2 - a bioimpedance sensing system for head and neck cancer tissue detection
AU - Cheng, Zhuoqi
AU - Carobbio, Andrea Luigi Camillo
AU - Soggiu, Lara
AU - Migliorini, Marco
AU - Guastini, Luca
AU - Mora, Francesco
AU - Fragale, Marco
AU - Ascoli, Alessandro
AU - Africano, Stefano
AU - Caldwell, Darwin
AU - Canevari, Frank Rikki Mauritz
AU - Parrinello, Giampiero
AU - Peretti, Giorgio
AU - Mattos, Leonardo S
N1 - © 2020 Institute of Physics and Engineering in Medicine.
PY - 2020/6/3
Y1 - 2020/6/3
N2 - OBJECTIVES: This study presents SmartProbe, an electrical bioimpedance (EBI) sensing system based on a concentric needle electrode (CNE). The system allows the use of commercial CNEs for accurate EBI measurement, and was specially developed for in-vivo real-time cancer detection. APPROACH: 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, for 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. MAIN RESULTS: 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 on 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. SIGNIFICANCE: These results are highly promising and indicate a great potential for SmartProbe to be used in various cancer detection tasks.
AB - OBJECTIVES: This study presents SmartProbe, an electrical bioimpedance (EBI) sensing system based on a concentric needle electrode (CNE). The system allows the use of commercial CNEs for accurate EBI measurement, and was specially developed for in-vivo real-time cancer detection. APPROACH: 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, for 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. MAIN RESULTS: 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 on 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. SIGNIFICANCE: These results are highly promising and indicate a great potential for SmartProbe to be used in various cancer detection tasks.
U2 - 10.1088/1361-6579/ab8cb4
DO - 10.1088/1361-6579/ab8cb4
M3 - Journal article
C2 - 32325435
SN - 0967-3334
VL - 41
JO - Physiological Measurement
JF - Physiological Measurement
IS - 5
ER -