头颈部癌
癌症检测
头颈部
生物医学工程
主管(地质)
医学
癌症
计算机科学
生物
外科
内科学
古生物学
作者
Zhuoqi Cheng,Andrea Luigi Camillo Carobbio,Lara Soggiu,Marco Migliorini,Luca Guastini,Francesco Mora,Marco Fragale,Alessandro Ascoli,Stefano Africano,Darwin G. Caldwell,Frank Rikki Canevari,Giampiero Parrinello,Giorgio Peretti,Leonardo S. Mattos
出处
期刊:Physiological Measurement
[IOP Publishing]
日期:2020-06-08
卷期号:41 (5): 054003-054003
被引量:19
标识
DOI:10.1088/1361-6579/ab8cb4
摘要
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.
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