AN ENHANCED ELECTRICAL-IMPEDANCE IMAGING ALGORITHM FOR HYPERTHERMIA APPLICATIONS

Electrical impedance imaging is a technique which is under investigati on as a noninvasive method of tracking subsurface temperature distribu tions and/or associated cellular response during hyperthermia. In prev ious work, a finite element image reconstruction algorithm for convert ing surface potential distributions recorded at discrete electrode pos itions into spatial maps of conductivity values was developed. This pa per reports on a series of significant improvements in the basic image reconstruction approach. Specifically, the ability to recover both th e resistive and capacitive components of tissue electrical impedance h ave been incorporated. In addition, the image enhancement schemes of ( 1) total variation minimization, (2) dual meshing, and (3) spatial low -pass filtering, have been added. Through a series of simulation studi es involving both phantom-like and clinically-relevant geometries havi ng discrete regions and continuously-varying electrical property profi les, a significantly improved ability to recover spatial images of ele ctrical properties in the impedance imaging context is demonstrated. T he results show that the new algorithm is much more tolerant of measur ement noise with levels up to 1% causing relatively modest degradation s in image quality (compared to 0.1% which was needed previously in or der to produce high quality images). The recovered electrical properti es, themselves, both resistive and capacitive, are also found to be qu antitative in value with errors in the 10-20% range occurring in the m ajority of cases, although deviations can reach 40% or more when noise levels as high as 10% are used. Temperature estimation simulations sh ow that maximum temperature errors are significantly reduced (to appro ximately 2 degrees C relative to more than 10 degrees C in previous th ermal simulations) with the new algorithm; however, temperature accura cies of better than 0.5 degrees C on average are still found to be dif ficult to achieve with electrical impedance imaging even when the enha nced image reconstruction approach is used.