Bladder volume measurement with electrical impedance analysis in spinal cord-injured patients

Detrusor pressure monitoring by electrical bioimpedance in the neurogenic bladder of adult patients

PURPOSE

Detrusor pressure-volume relationship evaluation by urodynamics provides useful clinical information; however, it is invasive, and requires specific installations. An alternative technique proposed by our research group is the electrical bioimpedance (BI) which is an easily performed and non-invasive method. In this work, we assess the relationship between BI and detrusor bladder pressure in adults with neurogenic lower urinary tract dysfunction.

METHODS

A prospective observational study was conducted. 20 patients (11 females and 9 male) previously diagnosed with neurogenic bladder were included. All participants underwent simultaneously a urodynamic evaluation (UDS) and BI determination, and both examination signals were recorded and subjected to Shapiro-Wilks statistical test. A correlational statistical test was used to compare the pressure parameters (detrusor, vesical and abdominal) with their respective BI determinations. Subsequently, a linear regression test was performed to evaluate the concordance between BI and their respective pressure values.

RESULTS

From the 20 correlations, between detrusor bladder pressure (PDET) and abdominal bioimpedance determinations (ZABD), obtained for all participants, 16 evidenced significant results over 90% (p < 0.05).

CONCLUSIONS

A significantly high correlation between abdominal bioimpedance determinations and the detrusor bladder pressures was evidenced. These results should be confirmed in a larger group of participants.

A deep neural network for estimating the bladder boundary using electrical impedance tomography

OBJECTIVE

Accurate bladder size estimation is an important clinical parameter that assists physicians, enabling them to provide better treatment for patients who are suffering from urinary incontinence. Electrical impedance tomography (EIT) is a non-invasive medical imaging method that estimates organ boundaries assuming that the electrical conductivity values of the background, bladder, and adjacent tissues inside the pelvic domain are known a priori. However, the performance of a traditional EIT inverse algorithm such as the modified Newton-Raphson (mNR) for shape estimation exhibits severe convergence problems as it heavily depends on the initial guess and often fails to estimate complex boundaries that require greater numbers of Fourier coefficients to approximate the boundary shape. Therefore, in this study a deep neural network (DNN) is introduced to estimate the urinary bladder boundary inside the pelvic domain.

APPROACH

We designed a five-layer DNN which was trained with a dataset of 15 subjects that had different pelvic boundaries, bladder shapes, and conductivity. The boundary voltage measurements of the pelvic domain are defined as input and the corresponding Fourier coefficients that describe the bladder boundary as output data. To evaluate the DNN, we tested with three different sizes of urinary bladder.

MAIN RESULTS

Numerical simulations and phantom experiments were performed to validate the performance of the proposed DNN model. The proposed DNN algorithm is compared with the radial basis function (RBF) and mNR method for bladder shape estimation. The results show that the DNN has a low root mean square error for estimated boundary coefficients and better estimation of bladder size when compared to the mNR and RBF.

SIGNIFICANCE

We apply the first DNN algorithm to estimate the complex boundaries such as the urinary bladder using EIT. Our work provides a novel efficient EIT inverse solver to estimate the bladder boundary and size accurately. The proposed DNN algorithm has advantages in that it is simple to implement, and has better accuracy and fast estimation.

Analysis of measurement electrode location in bladder urine monitoring using electrical impedance

Purpose

The aim of this study was to document more appropriate electrode location of a four-electrode-based electrical impedance technology in the monitoring of bladder filling, and to characterize the relationship between bladder filling duration and the measured electrical impedances.

Methods

A simulation study, based on a 2-dimension computational model, was conducted to determine the preferable locations of excitation and measurement electrodes in a conventional four-electrode setup. A human observation study was subsequently performed on eight healthy volunteers during natural bladder urine accumulation to validate the result of the simulation study. The correlation between the bladder filling time and the measured electrical impedance values was evaluated.

Results

The preferable location of measurement electrodes was successively validated by the model simulation study and human observation study. Result obtained via the selected electrodes location revealed a significant negative correlation (R = 0.916 ± 0.059, P < 0.001) between the measured electrical impedance and the urine accumulation time, which was consistent with the result of simulation study.

Conclusions

The findings in this study not only documented the desirable electrodes location to monitor the process of bladder urine accumulation using four-electrode measurement, but also validated the feasibility of utilizing electrical impedance technique to monitor and estimate the bladder urine volume for those with urological disorders.

Evaluation of electrical impedance tomography for determination of urinary bladder volume: comparison with standard ultrasound methods in healthy volunteers

Background

Continuous non-invasive urinary bladder volume measurement (cystovolumetry) would allow better management of urinary tract disease. Electrical impedance tomography (EIT) represents a promising method to overcome the limitations of non-continuous ultrasound measurements. The aim of this study was to compare the measurement accuracy of EIT to standard ultrasound in healthy volunteers.

Methods

For EIT of the bladder a commercial device (Goe MF II) was used with 4 different configurations of 16 standard ECG electrodes attached to the lower abdomen of healthy participants. To estimate maximum bladder capacity (BCmax) and residual urine (RU) two ultrasound methods (US-Ellipsoid and US-L × W × H) and a bedside bladder scanner (BS), were performed at the point of urgency and after voiding. For volume reference, BCmax and RU were validated by urine collection in a weight measuring pitcher. The global impedance method was used offline to estimate BCmax and RU from EIT.

Results

The mean error of US-Ellipsoid (37 ± 17%) and US-L × W × H (36 ± 15%) and EIT (32 ± 18%) showed no significant differences in the estimation of BCmax (mean 743 ± 200 ml) normalized to pitcher volumetry. BS showed significantly worse accuracy (55 ± 9%). Volumetry of RU (mean 152.1 ± 64 ml) revealed comparable higher errors for both EIT (72 ± 58%) and BS (63 ± 24%) compared to US-Ellipsoid (54 ± 25%). In case of RU, EIT accuracy is dependent on electrode configuration, as the Stripes (41 ± 25%) and Matrix (38 ± 27%) configurations revealed significantly superior accuracy to the 1 × 16 (116 ± 62%) configuration.

Conclusions

EIT-cystovolumetry compares well with ultrasound techniques. For estimation of RU, the selection of the EIT electrode configuration is important. Also, the development of an algorithm should consider the impact of movement artefacts. Finally, the accuracy of non-invasive ultrasound accepted as gold standard of cystovolumetry should be reconsidered.

Supervised Learning Classifiers for Electrical Impedance-based Bladder State Detection

Urinary Incontinence affects over 200 million people worldwide, severely impacting the quality of life of individuals. Bladder state detection technology has the potential to improve the lives of people with urinary incontinence by alerting the user before voiding occurs. To this end, the objective of this study is to investigate the feasibility of using supervised machine learning classifiers to determine the bladder state of ‘full’ or ‘not full’ from electrical impedance measurements. Electrical impedance data was obtained from computational models and a realistic experimental pelvic phantom. Multiple datasets with increasing complexity were formed for varying noise levels in simulation. 10-Fold testing was performed on each dataset to classify ‘full’ and ‘not full’ bladder states, including phantom measurement data. Support vector machines and k-Nearest-Neighbours classifiers were compared in terms of accuracy, sensitivity, and specificity. The minimum and maximum accuracies across all datasets were 73.16% and 100%, respectively. Factors that contributed most to misclassification were the noise level and bladder volumes near the threshold of ‘full’ or ‘not full’. This paper represents the first study to use machine learning for bladder state detection with electrical impedance measurements. The results show promise for impedance-based bladder state detection to support those living with urinary incontinence.

A realistic pelvic phantom for electrical impedance measurement

OBJECTIVE

To design and fabricate an anatomically and conductively accurate phantom for electrical impedance studies of non-invasive bladder volume monitoring.

APPROACH

A modular pelvic phantom was designed and fabricated, consisting of a mechanically and conductively stable boundary wall, a background medium, and bladder phantoms. The wall and bladders are made of conductive polyurethane. The background material is an ultrasound gel-based mixture, with conductivity matched to a weighted average of the pelvic cavity organs, bone, muscle and fat. The phantom boundary is developed using a computer tomography model of a male human pelvis. The bladder phantoms were designed to correlate with human bladder dimensions. Electrical impedance measurements of the phantom were recorded, and images produced using six different bladder phantoms and a realistic finite element model.

MAIN RESULTS

Five different bladder volumes were successfully imaged using an empty bladder as a reference. The average conductivity index from the reconstructed images showed a strong positive correlation with the bladder phantom volumes.

SIGNIFICANCE

A conductively and anatomically accurate pelvic phantom was developed for non-invasive bladder volume monitoring using electrical impedance measurements. Several bladders were designed to correlate with actual human bladder volumes, allowing for accurate volume estimation. The conductivity of the phantom is accurate over 50-250 kHz. This phantom can allow changeable electrode location, contact and size; multi-layer electrodes configurations; increased complexity by addition of other organ or bone phantoms; and electrode movement and deformation. Overall, the pelvic phantom enables greater scope for experimentation and system refinement as a precursor to in-man clinical studies.

A Phase-Based Electrical Plethysmography Approach to Bladder Volume Measurement

Neuromodulation approaches to treating lower urinary tract dysfunction could be substantially improved by a sensor able to detect when the bladder is full. A number of approaches to this problem have been proposed, but none has been found entirely satisfactory. Electrical plethysmography approaches attempt to relate the electrical impedance of the bladder to its volume, but have previously focused only on the amplitudes of the measured signals. We investigated whether the phase relationships between sinusoidal currents applied through a pair of stimulating electrodes and measured through a pair of recording electrodes could provide information about bladder volume. Acute experiments in a rabbit model were used to investigate how phase-to-volume or amplitude-to-volume regression models could be used to predict bladder volumes in future recordings, with and without changes to the saline conductivity. Volume prediction errors were found to be 6.63 ± 1.12 mL using the phase information and 8.32 ± 3.88 mL using the amplitude information (p = 0.44 when comparing the phase and amplitude results, n = 6), where the volume of the filled bladder was about 25 mL. When a full/empty binary decision rule was applied based on the regression model, the difference between the actual threshold that would result from this rule and the desired threshold was found to be 4.24 ± 0.65 mL using the phase information and 106.92 ± 189.82 mL using the amplitude information (p = 0.03, n = 6). Our results suggest that phase information can form the basis for more effective and robust electrical plethysmography approaches to bladder volume measurement.

Bladder volume estimation from electrical impedance tomography

Non-invasive estimation of bladder volume is required to progress from scheduled voiding to a demand-driven emptying scheme for patients with impaired bladder volume sensation. Electrical impedance tomography (EIT) is a promising candidate for the non-invasive monitoring of bladder volume. This article focuses on four estimation algorithms used to map recorded EIT data to a volume estimate. Two different approaches are presented: the tomographic algorithms (one based on global impedance, the other on equivalent circular diameter) rely on the reconstruction of a tomographic image and then extract a volume estimate, whereas the parametric algorithms (one based on neural networks, the other on the singular value difference method) directly map the raw data to a volume estimate. The four algorithms presented here are evaluated for volume estimation error, noise tolerance and suppression of varying urine conductivity based on finite element simulation data.

Noninvasive electrical impedance analysis to measure human urinary bladder volume

AIM

To assess urinary bladder volume in a noninvasive manner using a portable and modified device that measures electrical impedance.

METHODS

A novel method was attempted to measure electrical impedance and indirect bladder volume, and these data were used to calculate the actual bladder volume.

RESULTS

An increase of 0.01 V in the abdominal voltage was observed with every 50 mL increase in the amount of physiological saline infused into the bladder.

CONCLUSIONS

It is a simple procedure and can be used by technical staff or the patients themselves to obtain continuous, real-time urinary bladder volume data.

Surface fluids effects on the bladder tissue characterisation using electrical impedance spectroscopy

The electrical impedance of the human urinary bladder in both benign and malignant areas can be measured using an electrical impedance spectroscopy system (EIS). Glycine is usually used in the bladder surgery in the theatre to make an insulation medium for electro-surgery and the extension of the mucosa. In addition, a saline solution is usually used to wash the inside of the bladder after bladder surgery and it is used to extend the bladder tissue mucosa. Therefore, the effect of glycine and the saline solution that fills the bladder is important, because it was expected that the application of common surface fluids (air, saline solution and glycine solution) in the bladder epithelium would affect the measured electrical impedance of the urothelium, to differentiate the malignant area from the normal bladder tissue. In this study, bladders were removed from the patients' bodies and then were moved from theatre to the histopathology department immediately after excision. These bladder samples were then opened and pinned to a corkboard to take the impedance readings, using the impedance spectroscopy system. Following this, the bladder and corkboard were completely submerged in a saline solution and readings were taken at about 1cm from the sutures. Subsequently, this procedure was repeated with the bladder submerged in glycine and then air, respectively. According to the statistical work, these fluids were found to have a significant effect on the measured impedance of the bladder tissue in benign and malignant areas. Furthermore, the best fluid between air, glycine and saline, to measure the impedance of the urinary bladder, is air (P<0.0001).

Design and evaluation of an ultrasound-based bladder volume monitor

Ultrasonic bladder volume monitors have successfully been used in the diagnosis and treatment of various urological disorders. Ultrasonic bladder monitors have been developed but they have either been too bulky or too simple and inaccurate. A new, wearable ultrasonic bladder volume monitor has been designed for urological patients. The instrument consists of seven phased-array ultrasonic transducers ergonomically arranged in a circular pattern to optimise detection of the bladder walls perpendicular to the abdominal wall. A Bluetooth radio link was used to transmit data to a laptop computer, where the main signal processing was performed. After detection of bladder surface points, a three-dimensional convex hull representing the bladder was generated, and the volume was estimated. Accuracy, precision, drift over time, temperature dependency and dynamic performance were evaluated using ultrasound phantoms. Furthermore, the system was tested on one volunteer using magnetic resonance imaging (MRI) as reference. The apparatus showed no significant drift, systematic error or temperature effects. Percentage error during static volume measurements had a 95% central prediction interval of +/-7.5% and mean absolute percentage error of 2.9%. The dynamic performance analysis showed linearity in the analysed volume interval. The in vivo study showed a high degree of correlation (R2= 0.99) between the volume measured using MRI and that measured with the apparatus.

Electrical impedance spectroscopy and the diagnosis of bladder pathology: a pilot study

PURPOSE

Carcinoma in situ is an aggressive form of bladder cancer with a high propensity for invasion if left untreated. On cystoscopy these flat lesions cannot be differentiated from other erythematous, potentially benign areas and they require biopsy for definitive diagnosis. Other methods of detecting carcinoma in situ remain experimental. We assessed the effectiveness of electrical impedance spectroscopy, a method that measures the variation of electrical current flow with frequency through the mucosa, for differentiating various pathological changes in the urothelium.

MATERIALS AND METHODS

We obtained 250 impedance measurements immediately after resection in 35 cystectomy specimens using a custom designed probe. Three consecutive readings were recorded per point to assess reproducibility and punch biopsy was done at the measurement site.

RESULTS

Changes in the urothelium were classified histologically into 7 subgroups according to the degree of edema and inflammation. Electrical impedance spectroscopy measurements were able to separate benign and malignant changes when tested as a group (p <0.001), although some individual points overlapped. Edema also had a significant effect on tissue impedance (p <0.001).

CONCLUSIONS

Using measurements we established patterns of electrical impedance in the human bladder. Early results suggest that this minimally invasive technique is able to differentiate benign and malignant bladder pathologies. However, it requires further refinement and evaluation at lower frequencies, where the greatest impedance difference in benign and malignant tissues is expected.

Electrical impedance spectroscopy and the diagnosis of bladder pathology: a pilot study

PURPOSE

Carcinoma in situ is an aggressive form of bladder cancer with a high propensity for invasion if left untreated. On cystoscopy these flat lesions cannot be differentiated from other erythematous, potentially benign areas and they require biopsy for definitive diagnosis. Other methods of detecting carcinoma in situ remain experimental. We assessed the effectiveness of electrical impedance spectroscopy, a method that measures the variation of electrical current flow with frequency through the mucosa, for differentiating various pathological changes in the urothelium.

MATERIALS AND METHODS

We obtained 250 impedance measurements immediately after resection in 35 cystectomy specimens using a custom designed probe. Three consecutive readings were recorded per point to assess reproducibility and punch biopsy was done at the measurement site.

RESULTS

Changes in the urothelium were classified histologically into 7 subgroups according to the degree of edema and inflammation. Electrical impedance spectroscopy measurements were able to separate benign and malignant changes when tested as a group (p <0.001), although some individual points overlapped. Edema also had a significant effect on tissue impedance (p <0.001).

CONCLUSIONS

Using measurements we established patterns of electrical impedance in the human bladder. Early results suggest that this minimally invasive technique is able to differentiate benign and malignant bladder pathologies. However, it requires further refinement and evaluation at lower frequencies, where the greatest impedance difference in benign and malignant tissues is expected.