A Clinically Feasible Electrode Array for 3D Intraoperative Electrical Impedance Tomography-Based Surgical Margin Assessment in Robot-Assisted Radical Prostatectomy.

OBJECTIVE: A novel small form factor circular electrode array was designed specifically for electrical impedance tomography (EIT) based assessment of surgical margins during robot assisted radical prostatectomy (RARP). METHODS: The electrode array consists of 33 gold-plated electrodes arranged within a 9.5 mm diameter circular footprint on the end of a surgical probe that can be introduced through a standard 12 mm laparoscopic port used during RARP. The electrode array contains 8 larger, low-contact impedance outer electrodes dedicated for current drive and an internal grid of 25 smaller electrodes for simultaneous voltage measurement. Separating electrode geometry by function is designed to improve current delivery, speed, and resolution while reducing hardware requirements. RESULTS: Simulations demonstrated that 1 mm diameter hemispherical prostate cancer inclusions could be localized within regions of adipose and benign prostate tissue; 1.5 mm diameter inclusions were required for localization within muscle tissue. A 2.38 mm diameter aluminum rod in 0.2 S/m saline could be localized throughout the imaging domain with a position error of less than 2.5 mm for depths from the electrode array surface of up to 1.7 mm. Ex vivo tissue experiments with a bovine model demonstrate visual congruence of muscle and adipose tissue locations between the sample and reconstructed images. CONCLUSION: Simulation and experimental results indicate good detection and location of inclusions. SIGNIFICANCE: These results suggest the proposed electrode array design can provide sufficient accuracy in the detection and localization of prostate cancer against clinically relevant background tissues for use during RARP.

Non-invasive biomarkers for detecting progression toward hypovolemic cardiovascular instability in a lower body negative pressure model.

Occult hemorrhages after trauma can be present insidiously, and if not detected early enough can result in patient death. This study evaluated a hemorrhage model on 18 human subjects, comparing the performance of traditional vital signs to multiple off-the-shelf non-invasive biomarkers. A validated lower body negative pressure (LBNP) model was used to induce progression towards hypovolemic cardiovascular instability. Traditional vital signs included mean arterial pressure (MAP), electrocardiography (ECG), plethysmography (Pleth), and the test systems utilized electrical impedance via commercial electrical impedance tomography (EIT) and multifrequency electrical impedance spectroscopy (EIS) devices. Absolute and relative metrics were used to evaluate the performance in addition to machine learning-based modeling. Relative EIT-based metrics measured on the thorax outperformed vital sign metrics (MAP, ECG, and Pleth) achieving an area-under-the-curve (AUC) of 0.99 (CI 0.95-1.00, 100% sensitivity, 87.5% specificity) at the smallest LBNP change (0-15 mmHg). The best vital sign metric (MAP) at this LBNP change yielded an AUC of 0.6 (CI 0.38-0.79, 100% sensitivity, 25% specificity). Out-of-sample predictive performance from machine learning models were strong, especially when combining signals from multiple technologies simultaneously. EIT, alone or in machine learning-based combination, appears promising as a technology for early detection of progression toward hemodynamic instability.

Rapid patient-specific FEM meshes from 3D smart-phone based scans.

Objective.The objective of this study was to describe and evaluate a smart-phone based method to rapidly generate subject-specific finite element method (FEM) meshes. More accurate FEM meshes should lead to more accurate thoracic electrical impedance tomography (EIT) images.Approach.The method was evaluated on an iPhone®that utilized an app called Heges, to obtain 3D scans (colored, surface triangulations), a custom belt, and custom open-source software developed to produce the subject-specific meshes. The approach was quantitatively validated via mannequin and volunteer tests using an infrared tracker as the gold standard, and qualitatively assessed in a series of tidal-breathing EIT images recorded from 9 subjects.Main results.The subject-specific meshes can be generated in as little as 6.3 min, which requires on average 3.4 min of user interaction. The mannequin tests yielded high levels of precision and accuracy at 3.2 ± 0.4 mm and 4.0 ± 0.3 mm root mean square error (RMSE), respectively. Errors on volunteers were only slightly larger (5.2 ± 2.1 mm RMSE precision and 7.7 ± 2.9 mm RMSE accuracy), illustrating the practical RMSE of the method.Significance.Easy-to-generate, subject-specific meshes could be utilized in the thoracic EIT community, potentially reducing geometric-based artifacts and improving the clinical utility of EIT.

Development of an Electrical Impedance Tomography Coupled Surgical Stapler for Tissue Characterization.

OBJECTIVE: This study explores the feasibility of coupling Electrical Impedance Tomography (EIT) to a standard-of-care laparoscopic surgical stapler, stapler+EIT, with the long-term goal of enabling intraoperative tissue differentiation for tumor margin detection. METHODS: Two custom printed-circuit-board-based electrode arrays with 60 and 8 electrodes, respectively, matching the stapler geometry, served as the jaws of an electrode-integrated surrogate stapler+EIT device. The device was evaluated through a series of simulations and bench-top imaging experiments of agar-gel phantoms and bovine tissue samples to evaluate the technique and determine optimal imaging parameters. RESULTS: Electrodes localized to only one jaw (the 60-electrode side) of the stapler outperformed a dual-jaw distribution of electrodes. Using this one-sided electrode array, reconstructions achieved an Area-Under-the-Curve (AUC) ≥ 0.94 for inclusions with conductivity contrasts of ≥30% for any size considered on measured agar-gel tests, and an AUC of 0.80 for bovine tissue samples. CONCLUSION: A stapler+EIT algorithm has been tuned and evaluated on challenging phantom tests and demonstrated to produce accurate reconstructions. SIGNIFICANCE: This work is an important step in the development of a surgical stapler+EIT technique for margin assessment.

Towards intraoperative surgical margin assessment: Validation of an electrical impedance-based probe with ex vivo bovine tissue.

Radical prostatectomy (RP) is a common surgical therapy to treat prostate cancer. The procedure has a high positive surgical margin (PSM) rate ranging from 4-48%. Patients with PSMs have a higher rate of cancer recurrence and often undergo noxious adjuvant therapy. Intraoperative surgical margin assessment (SMA) with an electrical impedance-based probe can potentially identify PSMs in real-time. This would enable surgeons to make data-based decisions in the operating room to improve patient outcomes. This paper focuses on characterizing an impedance sensing SMA probe with specialized electrodes to improve speed and bandwidth while maintaining accuracy. 3D electrical impedance tomography (EIT) reconstructions were generated from ex vivo bovine tissue to characterize probe imaging and to determine an optimal applied pressure range (15 Pa to 38 Pa). Classification accuracy of adipose and muscle tissue was evaluated by comparing the experimental data set to simulated data based on a ground truth binary map of the tissue. Experimental AUCs ≥0.83 were maintained up to 50 kHz. The developed impedance sensing probe successfully classified between muscle and adipose tissue in an ex vivo bovine model. Future work includes improving performance of the SMA probe with custom hardware and collecting data from ex vivo and in vivo prostatic tissues.Clinical Relevance-This technology is expected to reduce the rate of PSMs in RP and decrease the use of post-surgical adjuvant therapies. It is also anticipated that intraoperative impedance measurements will increase efficacy of nerve sparing procedures and reduce complications such as incontinence and erectile dysfunction.

Detection of subclinical hemorrhage using electrical impedance: a porcine study.

Objective.Analyze the performance of electrical impedance tomography (EIT) in an innovative porcine model of subclinical hemorrhage and investigate associations between EIT and hemodynamic trends.Approach. Twenty-five swine were bled at slow rates to create an extended period of subclinical hemorrhage during which the animal's heart rate (HR) and blood pressure (BP) remained stable from before hemodynamic deterioration, where stable was defined as <15% decrease in BP and <20% increase in HR-i.e.hemorrhages were hidden from standard vital signs of HR and BP. Continuous vital signs, photo-plethysmography, and continuous non-invasive EIT data were recorded and analyzed with the objective of developing an improved means of detecting subclinical hemorrhage-ideally as early as possible.Main results. Best area-under-the-curve (AUC) values from comparing bleed to no-bleed epochs were 0.96 at a 80 ml bleed (∼15.4 min) using an EIT-data-based metric and 0.79 at a 120 ml bleed (∼23.1 min) from invasively measured BP-i.e.the EIT-data-based metric achieved higher AUCs at earlier points compared to standard clinical metrics without requiring image reconstructions.Significance.In this clinically relevant porcine model of subclinical hemorrhage, EIT appears to be superior to standard clinical metrics in early detection of hemorrhage.

Novel Electrode Placement in Electrical Bioimpedance-Based Stroke Detection: Effects on Current Penetration and Injury Characterization in a Finite Element Model.

OBJECTIVE: Reducing time-to-treatment and providing acute management in stroke are essential for patient recovery. Electrical bioimpedance (EBI) is an inexpensive and non-invasive tissue measurement approach that has the potential to provide novel continuous intracranial monitoring-something not possible in current standard-of-care. While extensive previous work has evaluated the feasibility of EBI in diagnosing stroke, high-impedance anatomical features in the head have limited clinical translation. METHODS: The present study introduces novel electrode placements near highly-conductive cerebral spinal fluid (CSF) pathways to enhance electrical current penetration through the skull and increase detection accuracy of neurologic damage. Simulations were conducted on a realistic finite element model (FEM). Novel electrode placements at the tear ducts, soft palate and base of neck were evaluated. Classification accuracy was assessed in the presence of signal noise, patient variability, and electrode positioning. RESULTS: Algorithms were developed to successfully determine stroke etiology, location, and size relative to impedance measurements from a baseline scan. Novel electrode placements significantly increased stroke classification accuracy at various levels of signal noise (e.g., p < 0.001 at 40 dB). Novel electrodes also amplified current penetration, with up to 30% increase in current density and 57% increased sensitivity in central intracranial regions (p < 0.001). CONCLUSION: These findings support the use of novel electrode placements in EBI to overcome prior limitations, indicating a potential approach to increasing the technology's clinical utility in stroke identification. SIGNIFICANCE: A non-invasive EBI monitor for stroke could provide essential timely intervention and care of stroke patients.

Cardiac eigen imaging: a novel method to isolate cardiac activity in thoracic electrical impedance tomography.

OBJECTIVE: As the global burden of cardiovascular disease increases, proactive cardiovascular healthcare by means of accurate, precise, continuous, and non-invasive monitoring is becoming crucial. However, no current device is able to provide cardiac hemodynamic monitoring with the aforementioned criterion. Electrical impedance tomography (EIT) is an inexpensive, non-invasive imaging modality that can provide real-time images of internal conductivity distributions that describe physiological activity. This work explores and compares a standard approach of regular cardiac gated averaging (RCGA) and a newly developed method, cardiac eigen-imaging (CEI), based on the singular value decomposition (SVD) to isolate cardiac activity in thoracic EIT. APPROACH: EIT and heart-rate (HR) data were collected from 20 heart-failure patients preceding echocardiography. Features from RCGA and CEI images were correlated with stroke volume (SV) from echocardiography and image reconstruction parameters were optimized using leave-one-out (LOO) cross-validation. MAIN RESULTS: CEI per-pixel-based features achieved a Pearson correlation coefficient of 0.80 with SV relative to 0.72 with RCGA. CEI had 33 high-correlating pixels while RCGA had 8. High-correlating pixels tend to concentrate in the right-ventricle (RV) when referenced to a general chest model. SIGNIFICANCE: While both RCGA and CEI images had high-correlating pixels, CEI had higher correlations, a larger number of high-correlating pixels, and unlike RCGA is not dependent on the quality of the HR data collected. The observed performance of the CEI approach represents a promising step forward for EIT-based cardiac monitoring in either clinical or ambulatory settings.

Bioimpedance Sensing Surgical Drill - Computational Modelling and Experimental Validation.

Surgical drilling to fixate dental implants is associated with high risk of injury to the inferior alveolar nerve (IAN) and the maxillary sinus. Current common practice is to use pre-operative radiographs to plan and drill with no real-time feedback of drill tip position with respect to these critical structures. Real-time proximity sensing of the IAN and maxillary sinus by measuring the electrical impedance properties of tissues, directly from the drill tip, while drilling may reduce and eventually eliminate this risk. Sensing impedance to detect tissue boundaries needs sensor geometry optimization for maximum detection distance. We have created a finite element method (FEM) based simulation platform that yields accurately impedances for different conductivities, frequencies and sensor geometries.

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.

A 1 MHz Miniaturized Electrical Impedance Tomography System for Prostate Imaging.

An ASIC for a high frequency electrical impedance tomography (EIT) imaging system for prostate cancer screening is presented. The ASIC enables a small form-factor architecture, which ensures high signal-to-noise ratio (SNR) at MHz frequencies. The 4-channel ASIC was designed and fabricated in a standard CMOS 0.18- µm technology and integrates a novel current driver for current stimulus, instrumentation amplifier to interface with the tissue, VGA to provide variable gain and ADC with SPI interface for digitization. A prototype miniaturized EIT system was built and it was evaluated using a model transrectal imaging probe immersed into a tank filled with saline and a metal inclusion that demonstrated the open-domain problem of imaging prostate cancer lesion. The system maintained an SNR between 66 and 76 dB over the frequency range of 500 Hz to 1 MHz. Also, it produced reconstructed EIT images that depicted the presence of the small metal inclusion that modeled a prostate cancer imaging application.

A robust and novel electrical impedance metric of pulmonary function in ALS patients.

OBJECTIVE: Pulmonary function tests (PFTs) are important for assessing respiratory function in amyotrophic lateral sclerosis (ALS) patients. However, weakness of oral and glottal closure, due to concomitant bulbar dysfunction, may result in unreliable PFT values stemming from leakage of air around the breathing tube and through the glottis. In this study, we assessed whether standard thoracic electrical impedance tomography (EIT) could serve as a surrogate measure for PFTs. APPROACH: Thoracic EIT was performed simultaneously with standard PFTs on seven ALS patients without clinical bulbar weakness (six men and one woman, mean age of 63 years) and ten healthy volunteers (seven men and three women, mean age of 57 years). A raw impedance metric along with more standard EIT measures were computed and correlated with the normalized forced vital capacity (FVC). Additionally, test/re-test metrics and EIT images were analyzed. MAIN RESULTS: The impedance metric was found to be robust and sensitive to lung activity. We also identified qualitative EIT differences between healthy volunteers and ALS patients, with the ALS images showing greater heterogeneity. Significant correlations with FVC were found for both impedance and EIT metrics in ALS patients (r2 = 0.89) and for the impedance metric only in healthy volunteers (r2 = 0.49). SIGNIFICANCE: This suggests that EIT, using our novel impedance metric, has the potential to serve as an alternative technology to standard PFTs for assessing pulmonary function in patients with ALS, offering new metrics of disease status for those with bulbar weakness.

Noise-robust bioimpedance approach for cardiac output measurement.

OBJECTIVE: Congestive heart failure is a problem affecting millions of Americans. A continuous, non-invasive, telemonitoring device that can accurately monitor cardiac metrics could greatly help this population, reducing unnecessary hospitalizations and cost. APPROACH: Machine learning (ML) algorithms trained on electrical-impedance tomography (EIT) data are presented for portable cardiac monitoring. The approach was validated on a simulated thorax and a measured tank experiment. A highly detailed 4D chest model (finite element method mesh and conductivity profiles) was developed utilizing the 4D XCAT phantom to provide realistic data. The ML algorithms were trained using databases that assumed the presence of poorly contacting electrodes without any assumptions of knowing which electrodes would be bad in the experiment. The trained ML algorithms were compared to EIT evaluated with and without removing bad electrodes. MAIN RESULTS: A regression support vector machine and a deep neural network (DNN) were found to be the most accurate and robust to poorly contacting electrodes while not needing to know which electrodes were in poor contact in the simulated and measured experiments, respectively. SIGNIFICANCE: Although the ML algorithms are not always better than EIT (with bad electrodes removed), the comparable results without needing a priori knowledge of which electrodes are bad is seen as a very promising feature. An evaluation of computational costs showed that the DNN required comparable computational power to the other methods while requiring less memory, which could make the DNNs an attractive algorithm for a low-power, portable system. This work represents an important validation of the method using measured data, and model development, which is needed to apply this method on real clinical data. Additionally, the developed 4D simulated thorax model could be an important tool within the EIT community.

Toward Electrical Impedance Tomography Coupled Ultrasound Imaging for Assessing Muscle Health.

This paper establishes for the first time that a coupled ultrasound (US) and electrical impedance tomography (EIT) system can serve as a non-invasive, spatially localized approach to extract clinically relevant muscle properties. The US/EIT system represents a potential enhancement to electrical impedance myography (EIM), which has shown promise as a non-invasive technology that may have important clinical use in indicating neuromuscular disease status and as a diagnostic tool. A 2.5D EIT algorithm evaluated on simulation, measured phantoms, and measured patient data was studied to evaluate US/EIT's ability to distinguish different aspects of muscle tissue. Simulated and phantom experiments revealed the depths of distinguishability of 3.2 and 4.2 mm in simulation for 10% and 20% changes in muscle properties, respectively, and 3.6 mm in measured phantom experiments assuming a 12% muscle conductivity change. Reconstructions from the patient data established that there were consistent differences 1) between longitudinal (along) and transverse (across) muscle conductivity reconstructions at frequencies of 40 and 80 kHz and 2) side-by-side comparison between healthy and diseased tissue in terms of conductivity, permittivity, and phase at 40 and 80 kHz. Comparisons were made between the EIT reconstructed values and electrical impedance spectroscopy (EIS) measurements (an available surrogate in place of standard EIM measurements) made with the US/EIT system, wherein 1) EIS and EIT show similar sensitivity to longitudinal and transverse differences and 2) EIT showed a more consistent ability to differentiate healthy and diseased tissue. These results suggest that US/EIT appears very promising for non-invasive and spatially localized diagnosis of muscle health.

An Analog Front End ASIC for Cardiac Electrical Impedance Tomography.

In this paper, an end-to-end CMOS application specific integrated circuit (ASIC) for readout channel in a cardiac electrical impedance tomography system is presented. The ASIC consists of an integrated current driver for current injection, an instrumentation amplifier, variable gain amplifier at the analog front end for voltage readout from electrodes, and an on-chip 10-bit successive approximation register analog to digital converter with serial peripheral interface. The ASIC is fabricated in the CMOS 0.18 $\mu$ m process with a supply voltage of 3.3 V. Amplitude and phase extraction of the voltages is performed in the digital domain with a matched filter. A fully integrated solution for use in multiple electrode system is demonstrated. The readout chain in the ASIC achieves a minimum signal-to-noise ratio of 71 dB over the frequency range of 500 Hz-700 kHz, while maintaining an average accuracy of 99.7 $\%$. Frame rates of 21 frames per second for a 32 electrode system is feasible, and the ASIC has an overall power consumption of 11.8 mW.

Fused-data transrectal EIT for prostate cancer imaging.

OBJECTIVE: Prostate cancer is a significant problem affecting 1 in 7 men. Unfortunately, the diagnostic gold-standard of ultrasound-guided biopsy misses 10%-30% of all cancers. The objective of this study was to develop an electrical impedance tomography (EIT) approach that has the potential to image the entire prostate using multiple impedance measurements recorded between electrodes integrated onto an end-fired transrectal ultrasound (TRUS) device and a biopsy probe (BP). APPROACH: Simulations and sensitivity analyses were used to investigate the best combination of electrodes, and measured tank experiments were used to evaluate a fused-data transrectal EIT (fd-TREIT) and BP approach. MAIN RESULTS: Simulations and sensitivity analysis revealed that (1) TREIT measurements are not sufficiently sensitive to image the whole prostate, (2) the combination of TREIT + BP measurements increases the sensitive region of TREIT-only measurements by 12×, and (3) the fusion of multiple TREIT + BP measurements collected during a routine or customized 12-core biopsy procedure can cover up to 76.1% or 94.1% of a nominal 50 cm3 prostate, respectively. Three measured tank experiments of the fd-TREIT + BP approach successfully and accurately recovered the positions of 2-3 metal or plastic inclusions. SIGNIFICANCE: The measured tank experiments represent important steps in the development of an algorithm that can combine EIT from multiple locations and from multiple probes-data that could be collected during a routine TRUS-guided 12-core biopsy. Overall, this result is a step towards a clinically deployable impedance imaging approach to scanning the entire prostate, which could significantly help to improve prostate cancer diagnosis.

Phantom experiments using soft-prior regularization EIT for breast cancer imaging.

OBJECTIVE: A soft-prior regularization (SR) electrical impedance tomography (EIT) technique for breast cancer imaging is described, which shows an ability to accurately reconstruct tumor/inclusion conductivity values within a dense breast model investigated using a cylindrical and a breast-shaped tank. APPROACH: The SR-EIT method relies on knowing the spatial location of a suspicious lesion initially detected from a second imaging modality. Standard approaches (using Laplace smoothing and total variation regularization) without prior structural information are unable to accurately reconstruct or detect the tumors. The soft-prior approach represents a very significant improvement to these standard approaches, and has the potential to improve conventional imaging techniques, such as automated whole breast ultrasound (AWB-US), by providing electrical property information of suspicious lesions to improve AWB-US's ability to discriminate benign from cancerous lesions. MAIN RESULTS: Specifically, the best soft-regularization technique found average absolute tumor/inclusion errors of 0.015 S m-1 for the cylindrical test and 0.055 S m-1 and 0.080 S m-1 for the breast-shaped tank for 1.8 cm and 2.5 cm inclusions, respectively. The standard approaches were statistically unable to distinguish the tumor from the mammary gland tissue. An analysis of false tumors (benign suspicious lesions) provides extra insight into the potential and challenges EIT has for providing clinically relevant information. SIGNIFICANCE: The ability to obtain accurate conductivity values of a suspicious lesion (>1.8 cm) detected from another modality (e.g. AWB-US) could significantly reduce false positives and result in a clinically important technology.

Comparative study of separation between ex vivo prostatic malignant and benign tissue using electrical impedance spectroscopy and electrical impedance tomography.

OBJECTIVE: Currently no efficient and reliable technique exists to routinely assess surgical margins during a radical prostatectomy. Electrical impedance spectroscopy (EIS) has been reported as a potential technique to provide surgeons with real-time intraoperative margin assessment. In addition to providing a quantified measure of margin status, a co-registered electrical impedance tomography (EIT) image presented on a surgeon's workstation could add value to the margin assessment process. APPROACH: To investigate this, we conducted a comparative study between EIS and EIT to evaluate the potential these technologies might have for margin assessment. EIS and EIT data was acquired from ex vivo human prostates using a multi-electrode endoscopic impedance acquisition probe. MAIN RESULTS: EIS and EIT show good predictive performance with a 0.76 and 0.80 area-under-curve (AUC), respectively, when considering discrete frequencies only. A machine learning (ML) algorithm is implemented to combine features, which improves the AUCs of EIS and EIT to 0.84 and 0.85, respectively. Single-step EIT takes significantly less time to reconstruct than multi-step EIT, yet provides similarly accurate classification results, making the single-step approach a potential candidate for real-time margin assessment. While the ML-based approach clearly exhibits benefits as compared to the single feature assessment, the decision to use EIS versus EIT is unclear since each approach performs better for different subsets of tissue classifications. SIGNIFICANCE: The results presented in this paper corroborate our previous studies and present the strongest evidence yet that an intraoperative-capable impedance probe can be used to distinguish benign from malignant prostate tissues. An in vivo study with a large cohort will be necessary to definitively determine the preferred approach and to show the clinical effectiveness of using this technology for margin assessment.

Absolute Reconstructions Using Rotational Electrical Impedance Tomography for Breast Cancer Imaging.

A rotational Electrical Impedance Tomography (rEIT) methodology is described and shown to produce spatially accurate absolute reconstructions with improved image contrast and an improved ability to distinguish closely spaced inclusions compared to traditional EIT on data recorded from cylindrical and breast-shaped tanks. Rotations of the tank without altering the interior conductivity distribution are used to produce the rEIT data. Quantitatively, rEIT was able to distinguish two inclusions that were 1.5 cm closer together than traditional EIT could achieve for inclusions placed 2 to 3 cm from the center for the cylindrical tank, and rEIT was able to distinguish two tumor-like inclusions where traditional EIT could not reliably do so. Mathematical analysis showed that rEIT improves the number of stable singular vectors by up to 4.2 and 4.7 times than that of traditional EIT for the cylindrical and breast-shaped tanks, respectively, which is an indication of improved resolution. Direct investigations into measurements revealed minimum rotation angles that should yield data uncorrupted by noise. Two inverse approaches (one that inverts then fuses the data (I/DF) and one that fuses the data then inverts (DF/I)) and two mesh modeling approaches were considered. It was found that DF/I produces far better results compared to I/DF and a rotated-mesh approach produces further improvements. The ability to obtain improved absolute reconstructions using rEIT on a practical clinical scenario (breast-shaped tank experiment) is an important step towards using rEIT to improve previous EIT results in medical applications.

Signal-to-Noise Ratio Analysis of a Phase-Sensitive Voltmeter for Electrical Impedance Tomography.

In this paper, thorough analysis along with mathematical derivations of the matched filter for a voltmeter used in electrical impedance tomography systems are presented. The effect of the random noise in the system prior to the matched filter, generated by other components, are considered. Employing the presented equations allow system/circuit designers to find the maximum tolerable noise prior to the matched filter that leads to the target signal-to-noise ratio (SNR) of the voltmeter, without having to over-design internal components. A practical model was developed that should fall within 2 dB and 5 dB of the median SNR measurements of signal amplitude and phase, respectively. In order to validate our claims, simulation and experimental measurements have been performed with an analog-to-digital converter (ADC) followed by a digital matched filter, while the noise of the whole system was modeled as the input referred at the ADC input. The input signal was contaminated by a known value of additive white Gaussian noise (AWGN) noise, and the noise level was swept from 3% to 75% of the least significant bit (LSB) of the ADC. Differences between experimental and both simulated and analytical SNR values were less than 0.59 and 0.35 dB for RMS values ≥ 20% of an LSB and less than 1.45 and 2.58 dB for RMS values < 20% of an LSB for the amplitude and phase, respectively. Overall, this study provides a practical model for circuit designers in EIT, and a more accurate error analysis that was previously missing in EIT literature.