Electromagnetic (EM) breast imaging provides low-cost, safe and potentially a more specific modality for cancer detection than conventional imaging systems. A primary difficulty in validating these EM imaging modalities is that the true dielectric property values of the particular breast being imaged are not readily available on an individual subject basis. Here, we describe our initial experience in seeking to correlate tomographic EM imaging studies with discrete point spectroscopy measurements of the dielectric properties of breast tissue. The protocol we have developed involves measurement of in vivo tissue properties during partial and full mastectomy procedures in the operating room (OR) followed by ex vivo tissue property recordings in the same locations in the excised tissue specimens in the pathology laboratory immediately after resection.We have successfully applied all of the elements of this validation protocol in a series of six women with cancer diagnoses. Conductivity and permittivity gauged from ex vivo samples over the frequency range 100 Hz-8.5 GHz are found to be similar to those reported in the literature. A decrease in both conductivity and permittivity is observed when these properties are gauged from ex vivo samples instead of in vivo. We present these results in addition to a case study demonstrating how discrete point spectroscopy measurements of the tissue can be correlated and used to validate EM imaging studies.

Bio-electric impedance signatures arise primarily from differences in cellular morphologies within an organ and can be used to differentiate benign and malignant pathologies, specifically in the breast. Electrical impedance tomography (EIT) is an imaging modality that determines the impedance distribution within tissue and has been used in prior work to map the electrical properties of breast at signal frequencies ranging from a few kHz to 1 MHz. It has been suggested that by extending the frequency range, additional information of clinical significance may be obtained. We have, therefore, developed a new EIT system for breast imaging which covers the frequency range from 10 kHz to 10 MHz. The instrument developed here is a distributed processor tomograph with 64 channels, capable of generating and measuring voltages and currents. Electrical benchmarking has shown the system to have a SNR greater than 94 dB up to 2 MHz, 90 dB up to 7 MHz, and 65 dB at 10 MHz. In addition, the system measures impedances to an accuracy of 99.7 % and has channel-to-channel variations of less than 0.05 %. Phantom imaging has demonstrated the ability to image across the entire frequency range in both single- and multiplane configurations. Further, 96 women have participated safely in breast exams with the system and the associated conductivity spectra obtained from 3-D image reconstructions range from 0.0237 S/m at 10 kHz to 0.2174 S/m at 10 MHz. These findings are consistent with impedance values reported in the literature.

Purpose Electrical properties of the prostate may provide sufficient contrast for distinguishing malignant and benign formations in the gland. We evaluated how well these electrical properties discriminate cancer from noncancer tissues in the prostate. Materials and Methods Electrical admittivity (conductivity and permittivity) was recorded at 31 discrete frequencies of 0.1 to 100 kHz from each of 50 ex vivo human prostates. A specifically designed admittivity probe was used to gauge these electrical properties from sectioned prostate specimens. The specific tissue area probed was marked to provide precise colocalization between tissue histological assessment and recorded admittivity spectra. Results Adenocarcinoma, benign prostatic hyperplasia, nonhyperplastic glandular tissue and stromal tissue were the primary tissue types probed. Mean cancer conductivity was significantly less than that of glandular and stromal tissues at all frequencies (p <0.05), while mean cancer permittivity was significantly greater than that of all benign tissues at 100 kHz (p <0.0001). ROC curves showed that permittivity at 100 kHz was optimal for discriminating cancer from all benign tissues. This parameter had 77% specificity at 70% sensitivity and an ROC AUC of 0.798. Conclusions The contrast in electrical admittivity properties of different prostate tissues shows promise for distinguishing cancer from benign tissues. Sensitivity and specificity exceed those reported for current prostate specific antigen screening practices at low prostate specific antigen, making this an attractive addition to the clinical armamentarium for identifying prostate cancer.

Tissue electrical impedance is a function of its architecture and has been used to differentiate normal and cancer tissues in a variety of organs including breast, cervix, skin, and bladder. This paper investigates the possibility of differentiating normal and malignant prostate tissue using bioimpedance spectra. A probe was designed to measure impedance spectra over the range of 10 kHz to 1 MHz. The probe was fully characterized using discrete loads and saline solutions of different concentrations. Impedance spectra of five ex vivo prostates were measured in the operating room immediately following radical prostatectomy. Wilcoxon signed-rank tests were used to compare the normal and malignant findings. The impedance probe had a signal-to-noise ratio (SNR) > 84 dB across the entire spectrum and measured a tissue volume of approximately 46 mm(3). At 10 kHz, prostate conductivity (or) ranged from 0.232 S/m to 0.310 S/m for tumor and from 0.238 S/m to 0.901 S/m for normal tissue. At 1 MHz the ranges were 0.301 S/m to 0.488 S/m for tumor and 0.337 S/m to 1.149 S/m for normal. Prostate permittivity (epsilonr) ranged from 6.64 x10(4) to 1.25 x 10(5) for tumor and from 9.08 x 10(4) to 4.49 x 10(5) for normal tissues at 10 kHz. And, at 1 MHz the er ranges were 9.23 x 10(2) to 1.88 x 10(3) for tumor and 1.16 x 10(3) to 2.18 x 10(3) for normal tissue. Both sigma and epsilonr of tumor tissue were found to be significantly lower than that of normal tissue (P < 0.0001). Conductivity and permittivity are both higher in normal prostate tissues than they are in malignant tissue making them suitable parameters for tissue differentiation. This is in agreement with trends observed in other tissues reported in much of the literature. Expanded studies are needed to further validate this finding and to explore the biological mechanism responsible for generating the results.

The electrical properties of benign and malignant prostate tissues differ significantly. This should be considered for use as a diagnostic tool. The differences observed between cancer and benign prostatic hyperplasia are especially important since current screening methods do not reliably differentiate between the 2 conditions.

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We employed electrical impedance spectroscopy (EIS) to evaluate the electrical properties of prostatic tissues. We collected freshly excised prostates from 23 men immediately following radical prostatectomy. The prostates were sectioned into 3 mm slices and electrical property measurements of complex resistivity were recorded from each of the slices using an impedance probe over the frequency range of 100 Hz to 100 kHz. The area probed was marked so that following tissue fixation and slide preparation, histological assessment could be correlated directly with the recorded EIS spectra. Prostate cancer (CaP), benign prostatic hyperplasia (BPH), non-hyperplastic glandular tissue and stroma were the primary prostatic tissue types probed. Genetic and least squares parameter estimation algorithms were implemented for fitting a Cole-type resistivity model to the measured data. The four multi-frequency-based spectral parameters defining the recorded spectrum (rho(infinity), Deltarho, f(c) and alpha) were determined using these algorithms and statistically analyzed with respect to the tissue type. Both algorithms fit the measured data well, with the least squares algorithm having a better average goodness of fit (95.2 mOmega m versus 109.8 mOmega m) and a faster execution time (80.9 ms versus 13 637 ms) than the genetic algorithm. The mean parameters, from all tissue samples, estimated using the genetic algorithm ranged from 4.44 to 5.55 Omega m, 2.42 to 7.14 Omega m, 3.26 to 6.07 kHz and 0.565 to 0.654 for rho(infinity), Deltarho, f(c) and alpha, respectively. These same parameters estimated using the least squares algorithm ranged from 4.58 to 5.79 Omega m, 2.18 to 6.98 Omega m, 2.97 to 5.06 kHz and 0.621 to 0.742 for rho(infinity), Deltarho, f(c) and alpha, respectively. The ranges of these parameters were similar to those reported in the literature. Further, significant differences (p < 0.01) were observed between CaP and BPH for the spectral parameters Deltarho and f(c); this is especially important since current prostate cancer screening methods do not reliably differentiate between these two tissue types.

Transrectal electrical impedance tomography (TREIT) has been proposed as an adjunct modality for enhancing standard clinical ultrasound (US) imaging of the prostate. The proposed TREIT probe has an array of electrodes adhered to the surface of a cylindrical US probe that is introduced inside of the imaging volume. Reconstructing TREIT images in the open-domain geometry established with this technique poses additional challenges to those encountered with closeddomain geometries, present in more conventional EIT systems, because of the rapidly decaying current densities at increasing distances from the probe surface. We developed a finite element method (FEM)-based dual-mesh reconstruction algorithm which employs an interpolation scheme for linking a fine forward mesh with a coarse grid of pixels, used for conductivity estimation. Simulation studies using the developed algorithm demonstrate the feasibility of imaging moderately contrasting inclusions at distances of three times the probe radius from the probe surface and at multiple angles about the probe's axis. The large, dense FEM meshes used here require significant computational effort. We have optimized our reconstruction algorithm with multi-core processing hardware and efficient parallelized computational software packages to achieve a speedup of 9.3 times when compared to a more traditional Matlab-based, single CPU solution. The simulation findings and computational optimization provide a state-of-the-art reconstruction platform for use in further evaluating transrectal electrical impedance tomography.