Study on Esophageal Tumor Detection Based on the MTV Algorithm in Electrical Impedance Imaging

Authors

  • Peng Ran School of Bioinformatics Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • Wei Liu School of Bioinformatics Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • Minchuan Li School of Bioinformatics Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • Yingbing Lai School of Bioinformatics Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • Zhuizhui Jiao School of Automation Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • Ying Zhong School of Bioinformatics Chongqing University of Posts and Telecommunications, Chongqing 400065, China

DOI:

https://doi.org/10.13052/2024.ACES.J.390707

Keywords:

Electrical impedance imaging, esophageal tumor, finite element inverse problem

Abstract

This paper presents a method for detecting and locating esophageal tumors using electrical impedance tomography (EIT) based on the modified total variation (MTV) regularization algorithm, utilizing a four-layer electrode array balloon detection structure. The optimal structure of the electrode array was obtained using the uniform design (UD) method. By integrating esophageal tissue structure information, physical models containing tumors at different locations were constructed. Using the adjacent excitation mode, the study compared average voltage, voltage dynamic range, and boundary voltage changes of electrode pairs within one-quarter of a cycle to analyze esophageal tumor characteristics. By comparing the correlation coefficients, relative errors, and imaging times of three reconstruction algorithms, the MTV algorithm, which best matches the morphological characteristics of the esophagus, was selected for image reconstruction. The calculated tumor height showed an error (ΔH) within 1 mm, indicating that EIT can provide vital information on the position, size, and electrical properties of esophageal tumors, demonstrating significant potential for clinical application in esophageal examinations.

Downloads

Download data is not yet available.

Author Biographies

Peng Ran, School of Bioinformatics Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Peng Ran was born in February 1981. Ph.D., associate professor, Chongqing Innovative Young Talents Training, Chongqing smart Medical system and core technology innovation team member, Chong-qing Medical Electronics and Information Technology Engineering Research Center team member. Since 2006, he has been engaged in cutting-edge research and development of new medical equipment and detection technology.

Wei Liu, School of Bioinformatics Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Wei Liu was born in February 1999. Currently pursuing a master’s degree in Biomedical Engineering at the School of Bioinformatics, Chongqing University of Posts and Telecommunications. Her main research direction is the study of esophageal force electrical imaging models based on mechanical and impedance feature reconstruction.

Minchuan Li, School of Bioinformatics Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Minchuan Li, born in September 1997, is currently a postgraduate student specializing in Biomedical Engineering at the School of Bioinformatics, Chongqing University of Posts and Telecommunications. His research is centered on advanced esophageal dynamic function detection methods, particularly focusing on piezoelectric impedance feature coupling.

Yingbing Lai, School of Bioinformatics Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Yingbing Lai was born in December 1998 and is a graduate student majoring in Biomedical Engineering at the School of Bioinformatics, Chongqing University of Posts and Telecommunications. His main research direction is the analysis of the coupling characteristics between esophageal bioelectrical impedance and mechanics.

Zhuizhui Jiao, School of Automation Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Zhuizhui Jiao was born in February 1996. Currently a graduate student majoring in Instrument Science and Technology at the School of Automation, Chongqing University of Posts and Telecommunications. The research direction is the fluid structure coupling characteristics and dynamic functional detection methods of narrow liquid cavities.

Ying Zhong, School of Bioinformatics Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Ying Zhong was born in October 1998. Currently studying at the School of Bioinformatics, Chongqing University of Posts and Telecommunications. Her research direction includes classification and evaluation methods for gastrointestinal diseases based on the coupling characteristics of biological impedance and biomechanics.

References

R. L. Siegel, K. D. Miller, H. E. Fuchs, and A. Jemal, ”Cancer statistics, 2022,” CA: A Cancer Journal for Clinicians, vol. 72, no. 1, pp. 7-33, Jan. 2022.

H. Li, J. Yu, R. Zhang, X. Li, and W. Zheng, ”Two-photon excitation fluorescence lifetime imaging microscopy: A promising diagnostic tool for digestive tract tumors,” Journal of Innovative Optical Health Sciences, vol. 12, no. 5, art. 1930009,2019.

Z. Yu, X. Bai, R. Zhou, G. Ruan, M. Guo, W. Han, and H. Yang, ”Differences in the incidence and mortality of digestive cancer between Global Cancer Observatory 2020 and Global Burden of Disease 2019,” International Journal of Cancer, vol. 154, no. 4, pp. 615-625, 2024.

Q. Huang, D. Lu, J. Han, H. Yu, W. Dong, K. Cai, and X. Yu, ”Comparison of dielectric properties of normal human esophagus and esophageal cancer using an open-ended coaxial probe,” Journal of Southern Medical University, vol. 41, no. 11, pp. 1741-1746, 2021.

M. Xu, H. He, and Y. Long, ”Lung perfusion assessment by bedside electrical impedance tomography in critically ill patients,” Frontiers in Physiology, vol. 12, art. 748724, 2021.

V. Tomicic and R. Cornejo, ”Lung monitoring with electrical impedance tomography: Technical considerations and clinical applications,” Journal of Thoracic Disease, vol. 11, no. 7, art. 3122,2019.

F. Xu, M. Li, J. Li, and H. Jiang, ”Diagnostic accuracy and prognostic value of three-dimensional electrical impedance tomography imaging in patients with breast cancer,” Gland Surgery, vol. 10, no. 9, pp. 2673-2680, 2021.

A. Witkowska-Wrobel, K. Aristovich, M. Faulkner, J. Avery, and D. Holder, ”Feasibility of imaging epileptic seizure onset with EIT and depth electrodes,” Neuroimage, vol. 173, pp. 311-321,2018.

T. Dowrick, C. Blochet, and D. Holder, ”In vivo bioimpedance changes during haemorrhagic and ischaemic stroke in rats: Towards 3D stroke imaging using electrical impedance tomography,” Physiological Measurement, vol. 37, no. 6, pp. 765-784, 2016.

B. Yang, B. Li, C. Xu, S. Hu, M. Dai, J. Xia, and F. Fu, ”Comparison of electrical impedance tomography and intracranial pressure during dehydration treatment of cerebral edema,” Neuro Image: Clinical, vol. 23, art. 101909, 2019.

Z. Li and C. Ren, ”Gastric motility measurement and evaluation of functional dyspepsia by a bio-impedance method,” Physiological Measurement, vol. 29, no. 6, art. S373, 2008.

M. R. Huerta-Franco, M. Vargas-Luna, J. B. Montes-Frausto, C. Flores-Hernández, and I. Morales-Mata, ”Electrical bioimpedance and other techniques for gastric emptying and motility evaluation,” World Journal of Gastrointestinal Pathophysiology, vol. 3, no. 1, pp. 10-18, 2012.

R. Wicaksono, P. N. Darma, A. Inoue, H. Tsuji, and M. Takei, ”Wearable sectorial electrical impedance tomography and k-means clustering for measurement of gastric processes,” Measurement Science and Technology, vol. 33, no. 9, art. 094002, 2022.

W R. Wicaksono, P. N. Darma, K. Sakai, D. Kawashima, and M. Takei, ”Imaging of gastric acidity scale by integration of pH-conversion model (pH-CM) into 3D-gastro electrical impedance tomography (3D-g-EIT),” Sensors and Actuators B: Chemical, vol. 366, art. 131923, 2022.

C. S. Chaw, E. Yazaki, and D. F. Evans, ”The effect of pH change on the gastric emptying of liquids measured by electrical impedance tomography and pH-sensitive radiotelemetry capsule,” International Journal of Pharmaceutics, vol. 227, no. 1-2, pp. 167-175, 2001.

J. Liu, Ö. Atmaca, and P. P. Pott, ”Needle-based electrical impedance imaging technology for Needle Navigation,” Bioengineering, vol. 10, no. 5, art. 590, 2023.

Z. Cheng, D. Dall’Alba, P. Fiorini, and T. R. Savarimuthu, ”Robot-assisted electrical impedance scanning system for 2D electrical impedance tomography tissue inspection,” in Proc. 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pp. 3729-3733, Nov. 2021.

K. T. Fang and Y. Wang, Number-Theoretic Methods in Statistics. Boca Raton: CRC Press, 1993.

K. T. Fang, D. K. Lin, P. Winker, and Y. Zhang, ”Uniform design: Theory and application,” Technometrics, vol. 42, no. 3, pp. 237-248, 2000.

A. Zandi, A. Gilani, F. Abbasvandi, P. Katebi, S. R. Tafti, S. Assadi, and M. Abdolahad, ”Carbon nanotube based dielectric spectroscopy of tumor secretion; electrochemical lipidomics for cancer diagnosis,” Biosensors and Bioelectronics, vol. 142, art. 111566, 2019.

D. G. Smith, S. R. Potter, B. R. Lee, H. W. Ko, W. R. Drummond, J. K. Telford, and A. W. Partin, ”In vivo measurement of tumor conductiveness with the magnetic bioimpedance method,” IEEE Transactions on Biomedical Engineering, vol. 47, no. 10, pp. 1403-1405, 2000.

P. I. Wu, J. A. Sloan, S. Kuribayashi, and H. Gregersen, ”Impedance in the evaluation of the esophagus,” Annals of the New York Academy of Sciences, vol. 1481, no. 1, pp. 139-153, 2020.

M. Vauhkonen, D. Vadász, P. A. Karjalainen, E. Somersalo, and J. P. Kaipio, ”Tikhonov regularization and prior information in electrical impedance tomography,” IEEE Transactions on Medical Imaging, vol. 17, no. 2, pp. 285-293, 1998.

Downloads

Published

2024-07-31

How to Cite

[1]
P. . Ran, W. . Liu, M. . Li, Y. . Lai, Z. . Jiao, and Y. . Zhong, “Study on Esophageal Tumor Detection Based on the MTV Algorithm in Electrical Impedance Imaging”, ACES Journal, vol. 39, no. 07, pp. 632–641, Jul. 2024.

Issue

2024: Vol 39 Iss 7

Section

General Submission

Categories