An electrical Impedance based tool is designed and developed to aid physicians performing clinical exams focusing on cancer detection. Current research envisions improvement in sensor-based measurement technology to differentiate malignant and benign lesions in human subjects. The tool differentiates malignant anomalies from nonmalignant anomalies using Electrical Impedance Spectroscopy (EIS). This method exploits cancerous tissue behavior by using EIS technique to aid early detection of cancerous tissue. The correlation between tissue electrical properties and tissue pathologies is identified by offering an analysis technique based on the Cole model. Additional classification and decision-making algorithm is further developed for cancer detection. This research suggests that the sensitivity of tumor detection will increase when supplementary information from EIS and built-in intelligence are provided to the physician.

The present study determines the effect of compression over bioimpedance of healthy soft tissue (in-vitro and in-vivo). Electrical impedance spectroscopy (EIS) is a promising tissue characterization and tumor detection technique that uses tissue impedance or admittance to characterize tissue and identify tissue properties as well as cell structure. Variation in EIS measurements while applying pressure suggests that compression tends to affect soft tissue bioimpedance. Moreover, the displacements in tissue caused by applied compression may provide useful information about the structure and state of the tissue. Thus combining the changes to the electrical properties of tissue resulted by applied compression, with the changes in tissue displacements caused by applied compression, and consequently measuring the effect that electrical and mechanical properties have on each other, can be useful to identify tissue structure. In this study, multifrequency bioimpedance measurements were performed on in-vitro and invivo soft tissue at different pressure levels. Increasing compression on the in-vitro tissue results in an increase in both extracellular resistance and membrane capacitance while it causes a reduction in the intracellular resistance. However, as the compression over the in-vivo samples increases, the intracellular and extracellular resistance increase and the membrane capacitance decreases. The in-vivo measurements on human body are also tested on contralateral tissue sites and similar tissue impedance variation trends are observed in the contra-lateral sites of human body. The evidence from these tests suggests the possibility of using this EIS-Pressure combined measurement method to improve tumor detection in soft tissue. Based upon the observations, the authors envision developing an advanced model based upon the Cole model, which is dependent on tissue displacements.

Tissue classification using computer aided diagnosis can help automated decision making to aid clinical diagnosis. Classification of breast tissue based on spectral features of impedance loci has frequently been done to classify malignant tissue with further requirement of more complex classification methodologies needed to improve the characterisation. In current study, tissue classification is done using in vivo electrical impedance data of 18 human subjects, from four quadrants of breast, palm, nail, arm, bicep and classified using algorithms involving machine learning methodologies, specifically support vector machines (SVMs) that are supervised learning models. They consist of learning algorithms based on the principal of structural risk minimisation. Two methodologies of SVM have been used in this study: with data binning and data pruning and without data binning and data pruning. Data binning and data pruning have improved the sensitivity of the SVM from 76.76 to 89.23%, but the specificity has decreased from 76.23 to 74.15%. This is a pilot study towards testing the reliability of the developed electrical impedance measuring system and developing a data mining-based decision making system into an electrical impedance spectroscopy system, to help users (physicians) with tissue classification leading to reliable objective decision making.

BackgroundIn radiotherapy, temporary translocations of the internal organs and tumor induced by respiratory and cardiac activities can undesirably lead to significantly lower radiation dose on the targeted tumor but more harmful radiation on surrounding healthy tissues. Respiratory and cardiac gated radiotherapy offers a potential solution for the treatment of tumors located in the upper thorax. The present study focuses on the design and development of simultaneous acquisition of respiratory and cardiac signal using electrical impedance technology for use in dual gated radiotherapy.MethodsAn electronic circuitry was developed for monitoring the bio-impedance change due to respiratory and cardiac motions and extracting the cardiogenic ECG signal. The system was analyzed in terms of reliability of signal acquisition, time delay, and functionality in a high energy radiation environment. The resulting signal of the system developed was also compared with the output of the commercially available Real-time Position Management™ (RPM) system in both time and frequency domains.ResultsThe results demonstrate that the bioimpedance-based method can potentially provide reliable tracking of respiratory and cardiac motion in humans, alternative to currently available methods. When compared with the RPM system, the impedance-based system developed in the present study shows similar output pattern but different sensitivities in monitoring different respiratory rates. The tracking of cardiac motion was more susceptible to interference from other sources than respiratory motion but also provided synchronous output compared with the ECG signal extracted. The proposed hardware-based implementation was observed to have a worst-case time delay of approximately 33 ms for respiratory monitoring and 45 ms for cardiac monitoring. No significant effect on the functionality of the system was observed when it was tested in a radiation environment with the electrode lead wires directly exposed to high-energy X-Rays.ConclusionThe developed system capable of rendering quality signals for tracking both respiratory and cardiac motions can potentially provide a solution for simultaneous dual-gated radiotherapy.

Phantoms are widely used in medical imaging to predict image quality prior to clinical imaging. This paper discusses the possible use of bolus material, as a conductivity phantom, for validation and interpretation of electrical impedance tomography (EIT) images. Bolus is commonly used in radiation therapy to mimic tissue. When irradiated, it has radiological characteristics similar to tissue. With increased research interest in CT/EIT fusion imaging there is a need to find a material which has both the absorption coefficient and electrical conductivity similar to biological tissues. In the present study the electrical properties, specifically resistivity, of various commercially available bolus materials were characterized by comparing their frequency response with that of in-vivo connective adipose tissue. It was determined that the resistivity of Gelatin Bolus is similar to in-vivo tissue in the frequency range 10 kHz to 1MHz and therefore has potential to be used in EIT/CT fusion imaging studies.