FPGA Based High Speed Data Acquisition System for Electrical Impedance Tomography

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.

Prostate Cancer Detection Using Composite Impedance Metric

Prostate cancer (PCa) recurrences are often predicted by assessing the status of surgical margins (SM)- positive surgical margins (PSM) increase the chances of biochemical recurrence by 2-4 times which may lead to PCa recurrence. To this end, an electrical impedance acquisition system with a microendoscopic probe was employed in an ex-vivo study of human prostates. This system measures the tissue bioimpedance over a range of frequencies (1 kHz to 1MHz), and computes a number of Composite Impedance Metrics (CIM). A classifier trained using CIM data can be used to classify tissue as benign or cancerous. The system was used to collect the impedance spectra from 14 excised prostates, which were obtained from men undergoing radical prostatectomy, for a total of 23 cancerous and 53 benign measurements. The data revealed statistically significant (p < 0.05) differences in the impedance properties of the benign and tumorous tissues, and among the measurements taken on the apical, base, and lateral surface of the prostate. Further, in the leave-one-patient-out cross validation, a maximum predictive accuracy of 90.79% was achieved by combining high frequency CIM phase data to train a support vector machine classifier with a radial basis function kernel. The observations are consistent with the physiology and morphology of benign and malignant prostate tissue. CIMs were found to be an effective tool in distinguishing benign from cancerous tissues.

3D Microendoscopic Electrical Impedance Tomography for Margin Assessment During Robot-Assisted Laparoscopic Prostatectomy

Radially configured microendoscopic electrical impedance probes intended for intraoperative surgical margin assessment during robot-assisted laparoscopic prostatectomy (RALP) were examined through simulation, bench-top experimentation, and ex vivo tissue studies. Three probe designs with 8, 9, and 17 electrodes, respectively, were analyzed through finite element method based simulations. One mm diameter spherical inclusions ( σinclusion = 1 S/m) are positioned at various locations within a hemispherical background ( σbackground = 0.1 S/m) of radius 5 mm. An 8-electrode configuration is not able to localize the inclusion at these positions while 9 and 17-electrode configurations are able to accurately reconstruct the inclusion at maximum depth of 1 mm and 3 mm, respectively. All three probe designs were constructed and evaluated using saline phantoms and ex vivo porcine and human prostate tissues. The 17-electrode probe performed best in saline phantom studies, accurately reconstructing high contrast, 1-mm-diameter metal cylindrical inclusions in a saline bath ( σsaline = 0.1 S/m) with a position and area error of 0.46 mm and 0.84 mm2, respectively. Additionally, the 17-electrode probe was able to adequately distinguish cancerous from benign tissues in three ex vivo human prostates. Simulations, bench-top saline experiments, and ex vivo tissue sampling suggest that for intraoperative surgical margin assessment during RALP, the 17-electrode probe (as compared to an 8 and 9 electrode probe) will be necessary to provide sufficient accuracy and sensitivity.

FPGA-based voltage and current dual drive system for high frame rate electrical impedance tomography

Electrical impedance tomography (EIT) is used to image the electrical property distribution of a tissue under test. An EIT system comprises complex hardware and software modules, which are typically designed for a specific application. Upgrading these modules is a time-consuming process, and requires rigorous testing to ensure proper functioning of new modules with the existing ones. To this end, we developed a modular and reconfigurable data acquisition (DAQ) system using National Instruments' (NI) hardware and software modules, which offer inherent compatibility over generations of hardware and software revisions. The system can be configured to use up to 32-channels. This EIT system can be used to interchangeably apply current or voltage signal, and measure the tissue response in a semi-parallel fashion. A novel signal averaging algorithm, and 512-point fast Fourier transform (FFT) computation block was implemented on the FPGA. FFT output bins were classified as signal or noise. Signal bins constitute a tissue's response to a pure or mixed tone signal. Signal bins' data can be used for traditional applications, as well as synchronous frequency-difference imaging. Noise bins were used to compute noise power on the FPGA. Noise power represents a metric of signal quality, and can be used to ensure proper tissue-electrode contact. Allocation of these computationally expensive tasks to the FPGA reduced the required bandwidth between PC, and the FPGA for high frame rate EIT. In 16-channel configuration, with a signal-averaging factor of 8, the DAQ frame rate at 100 kHz exceeded 110 frames s (-1), and signal-to-noise ratio exceeded 90 dB across the spectrum. Reciprocity error was found to be for frequencies up to 1 MHz. Static imaging experiments were performed on a high-conductivity inclusion placed in a saline filled tank; the inclusion was clearly localized in the reconstructions obtained for both absolute current and voltage mode data.

Methods for specific electrode resistance measurement during transcranial direct current stimulation

BACKGROUND

Monitoring of electrode resistance during tDCS is considered important for tolerability and safety. Conventional resistance measurement methods do not isolate individual electrode resistance and for HD-tDCS devices, cross talk across electrodes makes concurrent resistance monitoring unreliable.

OBJECTIVE

We propose a novel method to monitor individual electrode resistance during tDCS, using a super-position of direct current with a test-signal (low intensity and low frequency sinusoids with electrode-specific frequencies) and a sentinel electrode (not used for DC).

METHODS

We developed and solved lumped-parameter models of tDCS electrodes with or without a sentinel electrode to validate this methodology. Assumptions were tested and parameterized in participants using forearm stimulation combining tDCS (2 mA) and test-signals (38 and 76 μA pk-pk at 1 Hz, 10 Hz, & 100 Hz) and an in vitro test (creating electrode failure modes). DC and AC component voltages across the electrodes were compared and participants were asked to rate subjective pain.

RESULTS

A sentinel electrode is required to isolate electrode resistance in a two-electrode tDCS system. Cross talk aggravated with electrode proximity and resistance mismatch in multi-electrode resistance tracking could be corrected using proposed approaches. Average voltage and pain scores were not significantly different across test current intensities and frequencies.

CONCLUSION

Using our developed method, a test signal can predict DC electrode resistance. Since unique test frequencies can be used at each tDCS electrode, specific electrode resistance can be resolved for any number of stimulating channels - a process made still more robust by the use of a sentinel electrode.

Electrical impedance imaging system using FPGAs for flexibility and interoperability

BACKGROUND

Modern EIT systems require simultaneously operating multiple functions for flexibility, interoperability, and clinical applicability. To implement versatile functions, expandable design and implementation tools are needed. On the other hand, it is necessary to develop an ASIC-based EIT system to maximize its performance. Since the ASIC design is expensive and unchangeable, we can use FPGAs as a prior step to the digital ASIC design and carefully classify which functions should be included in the ASIC. In this paper, we describe the details of the FPGA design adopted in the KHU Mark2.5 EIT system.

METHODS

We classified all functions of the KHU Mark2.5 EIT system into two categories. One is the control and processing of current injection and voltage measurement. The other includes the collection and management of the multi-channel data with timing controls for internal and external interconnections. We describe the implementation of these functions in two kinds of FPGAs called the impedance measurement module (IMM) FPGA and the intra-network controller FPGA.

RESULTS

We present functional and timing simulations of the key functions in the FPGAs. From phantom and animal imaging experiments, we show that multiple functions of the system are successfully implemented in the FPGAs. As examples, we demonstrate fast multi-frequency imaging and ECG-gated imaging.

CONCLUSION

Given an analog design of a parallel EIT system, it is important to optimize its digital design to minimize systematic artifacts and maximize performance. This paper described technical details of the FPGA-based fully parallel EIT system called the KHU Mark2.5 with numerous functions needed for clinical applications. Two kinds of FPGAs described in this paper can be used as a basis for future EIT digital ASIC designs for better application-specific human interface as well as hardware performance.