Affiliations: [a] Department of Automobile Engineering, MIT Campus, Anna University, Chennai, India | [b] Department of Instrumentation Engineering, MIT Campus, Anna University, Chennai, India
Correspondence:
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Corresponding author: K. Kamalanand, Department of Instrumentation Engineering, MIT Campus, Anna University, Chennai, India. E-mail: [email protected].
Abstract: Background:Analysis of liver tissue in normal and abnormal conditions is essential for disease research, medical device design and treatment planning. Currently cirrhosis and malignancies of liver are among the major causes of mortality, worldwide. Objective:The objective of this work is to design an efficient capacitive sensor using Finite Element Methods (FEM), for diagnosis of cirrhotic and malignant liver. Methods:In this work, 3D geometric FEM models (N = 120) of normal, cirrhotic and malignant liver were generated using Comsol 3.5a. A set of ‘E’ shaped metallic plates, each with a dimension of 1 × 1 × 1 mm were modeled and mounted on the developed liver models. Four different bio-compatible metals namely Gold, Silver, Palladium and Platinum were used for analysis. Further, the observed capacitance values were converted into voltage using a De Sauty's bridge circuit implemented using Proteus 8. Finally, the statistical significance of the results was analyzed using the ANOVA test. Results:Results demonstrate that the observed voltages show significant variations between different liver pathologies. The developed sensor characteristic was found to be linear and the sensitivity of the sensor was found to be high when platinum electrodes were used. The diagnostic ability of the developed sensors for the adopted biocompatible metals was found to be highly statistically significant (P < 0.001). Conclusions:The proposed sensor design is compact with small dimensions and can be placed in contact with the human liver using endoscopic techniques. Hence, the developed sensor may provide a minimally invasive technique for liver diagnosis. This study appears to be of high clinical relevance since modelling of normal and abnormal liver, as well as design of suitable sensors for identification of liver abnormalities is required for improving the present diagnostic techniques.
