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Quantification of blood volume by electrical impedance tomography using a tissue-equivalent phantom
Physiological Measurement
|December 24, 1998
Summary
This study presents an electrical impedance tomography (EIT) system for detecting intra-peritoneal blood. Filtering and extended electrodes significantly improve positional independence for accurate blood quantity estimation.
Area of Science:
- Biomedical Engineering
- Medical Imaging
- Electrical Impedance Tomography
Background:
- Accurate estimation of intra-peritoneal blood requires an electrical impedance tomography (EIT) system with responses independent of anomaly position.
- Existing EIT systems may face challenges with positional variations of high conductivity anomalies, such as blood, within the abdominal cavity.
Purpose of the Study:
- To design and assess an in vivo EIT system for accurate intra-peritoneal blood quantity estimation.
- To minimize the system's response dependency on the position of intra-peritoneal blood anomalies.
Main Methods:
- Utilized a cylindrical tissue-equivalent phantom to assess system sensitivity to blood-equivalent resistivity anomalies.
- Employed filtering of resistivity profile images and extended electrodes for data acquisition.
- Developed a 'resistivity index' and applied a correction filter to mitigate radial variations.
Main Results:
- Satisfactorily uniform system response in both radial and axial directions was achieved through image filtering and extended electrodes.
- The correction filter reduced a 30% resistivity index variation (at 0.75 phantom radius) to only 6%.
- Extended electrodes reduced axial position variation in the resistivity index by approximately half compared to small circular electrodes.
Conclusions:
- The developed EIT system, incorporating image filtering and extended electrodes, demonstrates improved accuracy for intra-peritoneal blood detection.
- The resistivity index and correction filter effectively address positional variations, enhancing the reliability of blood quantity estimation.
- This approach offers a more robust solution for in vivo EIT applications requiring precise localization and quantification of internal anomalies.