Sensitivity study and optimization of a 3D electric impedance tomography prostate probe

Phantom Studies of Fused-Data TREIT Using Only Biopsy-Probe Electrodes

Transrectal electrical impedance tomography (TREIT) is a novel imaging modality being developed for prostate biopsy guidance and cancer characterization. We describe a novel fused-data TREIT (fd-TREIT) system and approach developed to improve imaging robustness and evaluate it on challenging clinically-representative phantoms. The new approach incorporates 8 electrodes (in 2 rows) on a biopsy probe (BP) and 12 electrodes on the face of a transrectal ultrasound (TRUS) probe and includes a biopsy gun, instrument tracking, 3D-printed needle guide, and EIT hardware and software. The approach was evaluated via simulation, a series of prostate-shaped gel phantoms, and an ex vivo bovine tissue sample using only absolute reconstructions. The simulations surprisingly found that using only biopsy-probe electrode measurements, i.e. omitting TRUS-probe electrode measurements, significantly improves robustness to noise thus leading to simpler modeling and significant decreases in computational times (~13x speed-up/reconstructions in ~27 minutes). The gel phantom experiments resulted in reconstructions with area under the curve (AUC) values extracted from receiver operator characteristic curves of >0.85 for 4 out of the 5 tests, and when incorporating inclusion boundaries resulted in absolute reconstructions yielding 1.9% and 12.2% average percent errors for 3 consistent tests and all 5 tests, respectively. Ex vivo bovine tests revealed qualitatively that the fd-TREIT approach can largely discriminate a complex adipose and muscle interface in a realistic setting using data from 9 biopsy probe states (biopsy core locations). The algorithms developed here on challenging phantoms suggest strong promise for this technology to aid in imaging during routine 12-core biopsies.

Three-dimensional Pulmonary Monitoring Using Focused Electrical Impedance Measurements

Lung pathologies such as edema, atelectasis or pneumonia are potentially life threatening conditions. Especially in critically ill and mechanically ventilated patients, an early diagnosis and treatment is crucial to prevent an Acute Respiratory Distress Syndrome [1]. Thus, continuous monitoring tool for the lung condition available at the bedside would be highly appreciated. One concept for this is Electrical Impedance Tomography (EIT). In EIT, an electrode belt of typically 16 or 32 electrodes is attached at the body surface and multiple impedance measurements are performed. From this, the conductivity change inside the body is reconstructed in a two-dimensional image. In various studies, EIT proved to be a useful tool for quantifying recruitment maneuvers, the assessment of the ventilation homogeneity, the detection of lung edema or perfusion monitoring [2, 3, 4, 5]. Nevertheless, the main problem of EIT is the low spatial resolution (compared to CT) and the limitation to two dimensional images. In this paper, we try to address the latter issue: Instead of projecting conductivity changes onto a two-dimensional image, we adjust electrode positions to focus single tetrapolar measurements to specific, three-dimensional regions of interest. In earlier work, we defined guidelines to achieve this focusing [6, 7]. In this paper, we demonstrate in simulations and in a water tank experiment that applying these guidelines can help to detect pathologies in specific lung regions.

A Novel Regularization Technique for Microendoscopic Electrical Impedance Tomography

A novel regularization technique is developed for end-fired microendoscopic electrical impedance tomography using the dual-mesh method. The new regularization technique coupled with appropriate forward modeling and inverse mesh design is shown to produce dramatically improved reconstructions over previous methods. 3D absolute and difference reconstructions from measured saline tank and ex vivo adipose and muscle tissue experiments are used to validate the approach. The ex vivo experiments are used as a surrogate for prostate tissue, which is the primary clinical application for the probe. Inclusion center of mass errors were less than 0.47 mm for tank experiments with inclusion depths and radial offsets ranging less than 3 mm and 1.5 mm, respectively. Absolute 3D reconstructions on the tissue show quantitatively good accuracy and the ability to spatially distinguish small tissue features (adipose strands of approximately 2.5 mm in width). The reconstruction algorithm developed provides strong evidence for the promise of surgical margin detection using microendoscopic EIT.

A feasibility study of magnetic resonance electrical impedance tomography for prostate cancer detection

Magnetic resonance electrical impedance tomography (MREIT) is an imaging technique that reconstructs the conductivity distribution inside the subject using magnetic flux density or current density measurements acquired by a magnetic resonance imaging system. Since the primary prostate cancer diagnostic method, prostate biopsy, has limited accuracy in cancer diagnosis and malignant tissues have shown significantly different electrical properties from normal or benign tissues, MREIT has potential application in prostate cancer detection. The feasibility of utilizing MREIT in detecting prostate cancer was evaluated via a series of well-designed computer simulations in the present study. MREIT techniques with three different electrode configurations (external, trans-rectal, and trans-urethral electrode arrays) and two different reconstruction algorithms (J-substitution algorithm and harmonic Bz algorithm) were successfully developed. The performance of different MREIT techniques were evaluated and compared based on the imaging accuracy of the reconstructed conductivity distribution in the prostate. Without the presence of noise, the external MREIT achieves a better imaging accuracy than the two endo-MREIT (trans-rectal and trans-urethral) techniques, while the trans-urethral MREIT achieves the best imaging accuracy in noisy environments. We also found that the J-substitution reconstruction algorithm consistently offered better imaging accuracy than the harmonic Bz algorithm. When Gaussian distributed random noise with a standard deviation of 0.25 nT was added, the relative errors (RE) between the reconstructed and target conductivity distributions inside the prostate were observed to be 14.18% and 17.35% by the trans-urethral MREIT with the J-substitution and harmonic Bz algorithms respectively. The lower REs of 9.64% and 11.17% were achieved respectively when the standard deviation of noise was reduced to 0.05 nT. The simulation results demonstrate the feasibility of applying MREIT for prostate cancer detection.

Transrectal electrical impedance tomography of the prostate: spatially coregistered pathological findings for prostate cancer detection

PURPOSE

Prostate cancer ranks as one of the most common malignancies and currently represents the second leading cancer-specific cause of death in men. The current use of single modality transrectal ultrasound (TRUS) for biopsy guidance has a limited sensitivity and specificity for accurately identifying cancerous lesions within the prostate. This study introduces a novel prostate cancer imaging method that combines TRUS with electrical impedance tomography (EIT) and reports on initial clinical findings based on in vivo measurements.

METHODS

The ultrasound system provides anatomic information, which guides EIT image reconstruction. EIT reconstructions are correlated with semiquantitative pathological findings. Thin plate spline warping transformations are employed to overlay electrical impedance images and pathological maps describing the spatial distribution of prostate cancer, with the latter used as reference for data analysis. Clinical data were recorded from a total of 50 men prior to them undergoing radical prostatectomy for prostate cancer treatment. Student's t-tests were employed to statistically examine the electrical property difference between cancerous tissue and benign tissue as defined through histological assessment of the excised gland.

RESULTS

Example EIT reconstructions are presented along with a statistical analysis comparing EIT and pathology. An average transformation error of 1.67% is found when 381 spatially coregistered pathological images are compared with their target EIT reconstructed counterparts. At EIT signal frequencies of 0.4, 3.2, and 25.6 kHz, paired-testing demonstrated that the conductivity of cancerous regions is significantly greater than that of benign regions ( p < 0.0304).

CONCLUSIONS

These preliminary clinical findings suggest the potential benefits electrical impedance measurements might have for prostate cancer detection.

Evaluation of different stimulation and measurement patterns based on internal electrode: application in cardiac impedance tomography

The conductivity distribution around the thorax is altered during the cardiac cycle due to the blood perfusion, heart contraction and lung inflation. Previous studies showed that these bio-impedance changes are appropriate for non-invasive cardiac function imaging using Electrical Impedance Tomography (EIT) techniques. However, the spatial resolution is presently low. One of the main obstacles in cardiac imaging at the heart location is the large impedance variation of the lungs by respiration and muscles on the dorsal and posterior side of the body. In critical care units there is a potential to insert an internal electrode inside the esophagus directly behind the heart in the same plane of the external electrodes. The aim of the present study is to evaluate different current stimulation and measurement patterns with both external and internal electrodes. Analysis is performed with planar arrangement of 16 electrodes for a simulated 3D cylindrical tank and pig thorax model. In our study we evaluated current injection patterns consisting of adjacent, diagonal, trigonometric, and radial to the internal electrode. The performance of these arrangements was assessed using quantitative methods based on distinguishability, sensitivity and GREIT (Graz consensus Reconstruction algorithm for Electrical Impedance Tomography). Our evaluation shows that an internal electrode configuration based on the trigonometric injection patterns has better performance and improves pixel intensity of the small conductivity changes related to heart near 1.7 times in reconstructed images and also shows more stability with different levels of added noise. For the internal electrode, when we combined radial or adjacent injection with trigonometric injection pattern, we found an improvement in amplitude response. However, the combination of diagonal with trigonometric injection pattern deteriorated the shape deformation (correlation coefficient r=0.344) more than combination of radial and trigonometric injection (correlation coefficient r=0.836) for the perturbations in the area close to the center of the cylinder. We also find that trigonometric stimulation pattern performance is degraded in a realistic thorax model with anatomical asymmetry. For that reason we recommend using internal electrodes only for voltage measurements and as a reference electrode during trigonometric stimulation patterns in practical measurements.

Anatomically accurate hard priors for transrectal electrical impedance tomography (TREIT) of the prostate

Current prostate biopsy procedures entail sampling tissues at template-based locations that are not patient specific. Ultrasound (US)-coupled transrectal electrical impedance tomography (TREIT), featuring an endorectal US probe retrofitted with electrodes, has been developed for prostate imaging. This multi-modal imaging system aims to identify suspicious tumor regions based on their electrical properties and ultimately provide additional patient-specific locations where to take biopsy samples. Unfortunately, the open-domain geometry associated with TREIT results in a severely ill-posed problem due to the small number of measurements and unbounded imaging domain. Furthermore, reconstructing contrasts within the prostate volume is challenging because the conductivity differences between the prostate and surrounding tissues are much larger than the conductivity differences between benign and malignant tissues within the prostate. To help overcome these problems, anatomically accurate hard priors can be employed to limit estimation of the electrical property distribution to within the prostate volume; however, this requires the availability of structural information. Here, a method that extracts the prostate surface from US images and incorporates this surface into the image reconstruction algorithm has been developed to enable estimation of electrical parameters within the prostate volume. In this paper, the performance of this algorithm is evaluated against a more traditional EIT algorithm that does not use anatomically accurate structural information, in the context of numerical simulations and phantom experiments. The developed anatomically accurate hard-prior algorithm demonstrably identifies contrasts within the prostate volume while an algorithm that does not rely on anatomically accurate structural information is unable to localize these contrasts. While inclusions are identified in the correct locations, they are found to be smaller in size than the actual object due to the rapid decay in sensitivity at increasing distances from the probe surface. Despite this, identifying the size of the inclusion accurately may not be essential for biopsy guidance in a clinical setting; instead, knowledge of the general vicinity of a cancerous lesion may be sufficient for suggesting and guiding clinicians to extract additional biopsy cores.

Incorporating a biopsy needle as an electrode in transrectal electrical impedance imaging

Previous studies have shown that prostate cancer may be detected by a combined transrectal ultrasound and electrical impedance tomography imaging system. However, the sensitivity of the imaging system is limited due to very little current established in the far field distant from the probe surface. Consequently, biopsy needles are introduced to the imaging system to provide current paths in the distal regions. This study demonstrates that image sensitivity can be improved by incorporating the needle electrodes. A phantom experiment is presented to show that contrast to the background is enhanced by 17.4% when imaging with needle electrodes. Simulated reconstructions and some preliminary clinical data also suggest the sensitivity improvement. In summary, TREIT with needle electrodes in the tissue may have great potential in future clinical prostate cancer detection.

Passive bioelectrical properties for assessing high- and low-grade prostate adenocarcinoma

BACKGROUND

The electrical properties of prostate tissues are dependent on cellular morphology and have been demonstrated to distinguish between benign and malignant formations. Because Gleason grading is also based on tissue architecture we explored the hypothesis that the electrical properties might also provide discriminating power between high- and low-Gleason grade cancers.

METHODS

Electrical properties (σ, ε, Δσ, σ(∞) , f(c) , and α) were gauged from 546 prostate tissue samples and correlated with histopathological assessment. Primary and secondary Gleason grades and a Gleason score were assigned to the tissues identified as cancer. We evaluated how well differently graded cancers were separable from benign tissues and from each other on the basis of these properties using ROC curves.

RESULTS

Of the 546 prostate tissue samples, 71 were identified as cancer and 465 as benign. ε, Δσ, σ(∞) , and f(c) provided the most discriminatory power with area under the curves (AUCs) ranging from 0.77-0.82 for detecting any cancer, 0.72-0.8 for low-grade cancer, and increasing to 0.87-0.9 for detecting high-grade cancer. Further, ε, Δσ, and σ(∞) , provided AUCs ranging from 0.74 to 0.75 for discriminating between low- and high-grade cancers.

CONCLUSIONS

Using the electrical properties to identify prostate cancer is improved when high-grade cancers are sought. These electrical properties can also discriminate between different grades of tumors. These findings suggest that technologies being developed to sense and image these properties in vivo may discriminate between aggressive and indolent lesions.

Sensitivity study of an ultrasound coupled transrectal electrical impedance tomography system for prostate imaging

In 2009, prostate cancer ranked as the most common cancer and the second most fatal cancer in men in the United States. Unfortunately, the current clinical diagnostic methods (e.g. prostate-specific antigen (PSA), digital rectal examination, endorectal MRI, transrectal ultrasound, biopsy) used for detecting and staging prostate cancer are limited. It has been shown that cancerous prostate tissue has significantly different electrical properties when compared to benign tissues. Based on these electrical property findings, a transrectal electrical impedance tomography (TREIT) system is proposed as a novel prostate imaging modality. The TREIT system comprises an array of electrodes interfaced with a clinical transrectal ultrasound (TRUS) probe. We evaluate this imaging system through a series of phantom imaging experiments to assess the system's ability to image high and low contrast objects at various positions. We found that the TREIT system can easily discern high contrast inclusions of 1 cm in diameter at distances centered at two times the radius of the TREIT probe away from the probe surface. Furthermore, this technology's ability to detect low contrast inclusions suggests that it has the potential to successfully detect prostate cancer.

Electrical impedance tomography reconstruction for three-dimensional imaging of the prostate

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 closed-domain 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.

Electrical properties of prostatic tissues: II. Spectral admittivity properties

PURPOSE

The electrical properties of prostate tissues gauged at discrete frequencies provide sufficient contrast to discriminate malignant from benign prostatic tissues. The frequency dependence of these properties is also a function of tissue morphology. We evaluated the potential of this spectral dependence to provide additional diagnostic information for prostate cancer detection.

MATERIALS AND METHODS

Electrical conductivity and permittivity were recorded from 50 ex vivo prostates at 31 logarithmically spaced frequencies of 100 Hz to 100 kHz. We used a well established, 4 parameter (sigma(infinity), Delta sigma, f(c) and alpha) model to describe individual spectra with each model parameter influenced by tissue morphology. We evaluated these parameters in terms of discriminatory power using ROC curves.

RESULTS

Of the 4 spectral parameters sigma(infinity) and f(c) were significantly greater in cancer than in benign tissues and Delta sigma was significantly more negative in cancer than in benign tissues (each p <0.0001). f(c) provided the maximum discriminating power with an ROC AUC of 0.821 and 81.5% specificity at 70% sensitivity. Also, sigma(infinity) and Delta sigma provided high levels of discrimination with an AUC of 0.770 and 0.782, respectively.

CONCLUSIONS

Spectral electrical admittivity properties provide sufficient levels of ex vivo cancer discrimination that may potentially enhance disease localization when prostate cancer is suspected. The development of novel technologies gauging these properties in vivo has the potential to provide new tissue characterizing tools for prostate cancer detection and identification.