Estimation Of Bladder Volume Research Articles

Handheld Ultrasound Bladder Volume Assessment Compared to Standard Technique.

Urinary retention is a common complaint encountered in the emergency department (ED).Current tools for the assessment of urinary retention are either bladder volume estimation with a bladder scanner performed by nursing staff or direct visualization and measurement via bedside ultrasound performed by an emergency physician. Newer handheld ultrasound devices such as the Butterfly iQ have been brought to the market to bring ultrasound more conveniently to the bedside.A recently released handheld auto-calculation tool produces a 3D image of the bladder and instant bladder volume measurement in milliliters. However, there is a paucity of data assessing the validity of the new Butterfly iQ at the bedside. This study sought to compare the diagnostic accuracy and rated user convenience of the nursing bladder scanner, the cart-based ultrasound machine, and the Butterfly iQ auto-bladder volume tool. ED patients were prospectively enrolled and underwent bladder measurements in a randomized, pre-determined order with each modality. Measurements were subsequently compared to the gold standard of catheterization. Cart-based ultrasound had the highest agreement to catheterization when compared to the RN scanner and the Butterfly iQ.However, the Butterfly iQ and RN scanner were both considered more convenient measurement modalities than the cart-based ultrasound. The Butterfly iQ serves as a cost-effective alternative to cart-based ultrasound while providing greater general utility compared to bladder scanners.

Intelligent Bladder Volume Monitoring for Wearable Ultrasound Devices: Enhancing Accuracy Through Deep Learning-Based Coarse-to-Fine Shape Estimation.

Accurate and continuous bladder volume monitoring is crucial for managing urinary dysfunctions. Wearable ultrasound (US) devices offer a solution by enabling noninvasive and real-time monitoring. Previous studies have limitations in power consumption and computation cost or quantitative volume estimation capability. To alleviate this, we present a novel pipeline that effectively integrates conventional feature extraction and deep learning (DL) to achieve continuous quantitative bladder volume monitoring efficiently. Particularly, in the proposed pipeline, bladder shape is coarsely estimated by a simple bladder wall detection algorithm in wearable devices, and the bladder wall coordinates are wirelessly transferred to an external server. Subsequently, a roughly estimated bladder shape from the wall coordinates is refined in an external server with a diffusion-based model. With this approach, power consumption and computation costs on wearable devices remained low, while fully harnessing the potential of DL for accurate shape estimation. To evaluate the proposed pipeline, we collected a dataset of bladder US images and RF signals from 250 patients. By simulating data acquisition from wearable devices using the dataset, we replicated real-world scenarios and validated the proposed method within these scenarios. Experimental results exhibit superior improvements, including +9.32% of IoU value in 2-D segmentation and -22.06 of RMSE in bladder volume regression compared to state-of-the-art (SOTA) performance from alternative methods, emphasizing the potential of this approach in continuous bladder volume monitoring in clinical settings. Therefore, this study effectively bridges the gap between accurate bladder volume estimation and the practical deployment of wearable US devices, promising improved patient care and quality of life.

A-Mode Ultrasound Bladder Volume Estimation Algorithm Based on Wavelet Energy Ratio Adaptive Denoising.

Assessing bladder function is pivotal in urological health, with bladder volume a critical indicator. Traditional devices, hindered by high costs and cumbersome sizes, are being increasingly supplemented by portable alternatives; however, these alternatives often fall short in measurement accuracy. Addressing this gap, this study introduces a novel A-mode ultrasound-based bladder volume estimation algorithm optimized for portable devices, combining efficient, precise volume estimation with enhanced usability. Through the innovative application of a wavelet energy ratio adaptive denoising method, the algorithm significantly improves the signal-to-noise ratio, preserving critical signal details amidst device and environmental noise. Ultrasonic echoes were employed to acquire positional information on the anterior and posterior walls of the bladder at several points, with an ellipsoid fitted to these points using the least squares method for bladder volume estimation. Ultimately, a simulation experiment was conducted on an underwater porcine bladder. The experimental results indicate that the bladder volume estimation error of the algorithm is approximately 8.3%. This study offers a viable solution to enhance the accuracy and usability of portable devices for urological health monitoring, demonstrating significant potential for clinical application.

A Novel Three-Point Localization Method for Bladder Volume Estimation.

The measurement of bladder volume is crucial for the diagnosis and treatment of urinary system diseases. Ultrasound imaging, with its non-invasive, radiation-free, and repeatable scanning capabilities, has become the preferred method for measuring residual urine volume. Nevertheless, it still faces some challenges, including complex imaging methods leading to longer measurement times and lower spatial resolution. Here, we propose a novel three-point localization method that does not require ultrasound imaging to calculate bladder volume. A corresponding triple-element ultrasound probe has been designed based on this method, enabling the ultrasound probe to transmit and receive ultrasound waves in three directions. Furthermore, we utilize the Hilbert Transform algorithm to extract the envelope of the ultrasound signal to enhance the efficiency of bladder volume measurements. The experiment indicates that bladder volume estimation can be completed within 5 s, with a relative error rate of less than 15%. These results demonstrate that this novel three-point localization method offers an effective approach for bladder volume measurement in patients with urological conditions.

Noninvasive Urinary Bladder Volume Estimation With Artifact-Suppressed Bioimpedance Measurements

Noninvasive Urinary Bladder Volume Estimation With Artifact-Suppressed Bioimpedance Measurements

Management of medically unresponsive detrusor urethral dyssynergia in three dogs by perineal urethrostomy

AbstractThree male dogs were referred with chronic dysuria. A presumptive diagnosis of idiopathic detrusor urethral dyssynergia was made based on a characteristic pattern of urination (a ‘spurting’ interrupted urine stream, dribbling urine following failed attempts at urination), normal clinical and neurological examination, absence of physical obstruction on urethral catheterisation and absence of abnormalities on plain and contrast radiography and ultrasonography. Medical management failed to resolve clinical signs, and all dogs therefore underwent perineal urethrostomy as a salvage procedure. There were no major postoperative complications, and all dogs urinated with a normal uninterrupted stream of urine at their first urination postoperatively. Urinary function was assessed before and after perineal urethrostomy by observation of urination and estimation of residual bladder volume using ultrasound. No recurrence of dysuria was reported during long‐term follow‐up, with urination reported to be normal in all cases.

A whale optimization detection (WOD) method for bladder volume estimation with bioelectrical impedance spectroscopy (BIS)

A whale optimization detection (WOD) method is presented for rapid bladder volume estimation with bioelectrical impedance spectroscopy (BIS). Firstly, the WOD method for bladder volume estimation is established, which includes a bladder volume estimation electrical equivalent circuit (EEC) model and a rapid fitting strategy. Secondly, an abdominal phantom is constructed, which consists of an abdominal cavity shell and four bladders with volumes of V b = 30 ml, 100 ml, 200 ml, and 300 ml. Next, BIS experiments are conducted using the phantom with the WOD method fitted to the obtained data. The results demonstrated a high linear correlation coefficient R 2 > 0.987 between the experimental and WOD results. Finally, in vivo testing is performed using both the Caresono HD-5 ultrasonic bladder scanner and the proposed WOD method. The EEC parameters obtained by the WOD method form a mathematical formula that accurately describes the subject’s bladder volume, with a detection correlation coefficient r = 98.71%, and the maximum relative error δ = 5.88% between WOD and ultrasound testing results. In conclusion, the proposed method is expected to be applied for rapid monitoring of patients’ bladder volume.

Memory-efficient low-compute segmentation algorithms for bladder-monitoring smart ultrasound devices

Post-operative urinary retention is a medical condition where patients cannot urinate despite having a full bladder. Ultrasound imaging of the bladder is used to estimate urine volume for early diagnosis and management of urine retention. Moreover, the use of bladder ultrasound can reduce the need for an indwelling urinary catheter and the risk of catheter-associated urinary tract infection. Wearable ultrasound devices combined with machine-learning based bladder volume estimation algorithms reduce the burdens of nurses in hospital settings and improve outpatient care. However, existing algorithms are memory and computation intensive, thereby demanding the use of expensive GPUs. In this paper, we develop and validate a low-compute memory-efficient deep learning model for accurate bladder region segmentation and urine volume calculation. B-mode ultrasound bladder images of 360 patients were divided into training and validation sets; another 74 patients were used as the test dataset. Our 1-bit quantized models with 4-bits and 6-bits skip connections achieved an accuracy within 3.8% and 2.6%, respectively, of a full precision state-of-the-art neural network (NN) without any floating-point operations and with an 11.5times and 9.0times reduction in memory requirements to fit under 150 kB. The means and standard deviations of the volume estimation errors, relative to estimates from ground-truth clinician annotations, were 5.0pm 33 ml and 6.8pm 29 ml, respectively. This lightweight NN can be easily integrated on the wearable ultrasound device for automated and continuous monitoring of urine volume. Our approach can potentially be extended to other clinical applications, such as monitoring blood pressure and fetal heart rate.

Comparative Effectiveness of Two Models of Point-of-Care Ultrasound for Detection of Post-Void Residual Urine during Acute Ischemic Stroke: Preliminary Findings of Real-World Clinical Application.

We conducted a comparative study of two models of point-of-care ultrasound devices for measuring post-void residual urine (PVRU). We prospectively enrolled 55 stroke inpatients who underwent both real-time B-mode ultrasound (Device A) and automated three-dimensional (3D) scanning ultrasound (Device B), with a total of 108 measurements. The median PVRU volume of Device B was 40 mL larger than that of Device A. The PVRU difference between the devices was positively and linearly correlated with PVRU. The correlation of PVRU volume between the devices was strong, but the agreement level was only moderate. Measurement deviations were observed in 43 (40%) and 11 (10%) measurements with Device B and Device A, respectively. The PVRU volume was low in spherical bladder shapes but sequentially increased in triangular, undefined, ellipsoid, and cuboid bladder shapes. Further comparison of 60 sets of PVRU without measurement deviations revealed higher agreements between the devices at correction coefficients of 0.52, 0.66, and 0.81 for PVRU volumes of <100, 100-200, and >200 mL, respectively. The automated 3D scanning ultrasound is more convenient for learning and scanning, but it exhibits larger measurement deviations. Real-time B-mode ultrasound accurately visualizes the urinary bladder but tends to underestimate the urinary bladder when the PVRU volume is large. Hence, real-time B-mode ultrasound with automated PVRU-based adjustment of calculation formulas may be a better solution for estimating bladder volume.

First in Human Subjects Testing of the UroMonitor: A Catheter-free Wireless Ambulatory Bladder Pressure Monitor.

Urodynamics is the standard method of diagnosing bladder dysfunction, but involves catheters and retrograde bladder filling. With these artificial conditions, urodynamics cannot always reproduce patient complaints. We have developed a wireless, catheter-free intravesical pressure sensor, the UroMonitor, which enables catheter-free telemetric ambulatory bladder monitoring. The purpose of this study was twofold: to evaluate accuracy of UroMonitor pressure data, and assess safety and feasibility of use in humans. Eleven adult female patients undergoing urodynamics for overactive bladder symptoms were enrolled. After baseline urodynamics, the UroMonitor was transurethrally inserted into the bladder and position was confirmed cystoscopically. A second urodynamics was then performed with the UroMonitor simultaneously transmitting bladder pressure. Following removal of urodynamics catheters, the UroMonitor transmitted bladder pressure during ambulation and voiding in private. Visual analogue pain scales (0-5) were used to assess patient discomfort. The UroMonitor did not significantly alter capacity, sensation, or flow during urodynamics. The UroMonitor was also easily inserted and removed in all subjects. The UroMonitor reproduced bladder pressure, capturing 98% (85/87) of voiding and nonvoiding urodynamic events. All subjects voided with only the UroMonitor in place with low post-void residual volume. Median ambulatory pain score with the UroMonitor was rated 0 (0-2). There were no post-procedural infections or changes to voiding behavior. The UroMonitor is the first device to enable catheter-free telemetric ambulatory bladder pressure monitoring in humans. The UroMonitor appears safe and well tolerated, does not impede lower urinary tract function, and can reliably identify bladder events compared to urodynamics.

A Lightweight Deep Learning Network on a System-on-Chip for Wearable Ultrasound Bladder Volume Measurement Systems: Preliminary Study.

Bladder volume assessments are crucial for managing urinary disorders. Ultrasound imaging (US) is a preferred noninvasive, cost-effective imaging modality for bladder observation and volume measurements. However, the high operator dependency of US is a major challenge due to the difficulty in evaluating ultrasound images without professional expertise. To address this issue, image-based automatic bladder volume estimation methods have been introduced, but most conventional methods require high-complexity computing resources that are not available in point-of-care (POC) settings. Therefore, in this study, a deep learning-based bladder volume measurement system was developed for POC settings using a lightweight convolutional neural network (CNN)-based segmentation model, which was optimized on a low-resource system-on-chip (SoC) to detect and segment the bladder region in ultrasound images in real time. The proposed model achieved high accuracy and robustness and can be executed on the low-resource SoC at 7.93 frames per second, which is 13.44 times faster than the frame rate of a conventional network with negligible accuracy drawbacks (0.004 of the Dice coefficient). The feasibility of the developed lightweight deep learning network was demonstrated using tissue-mimicking phantoms.

Assessment of bladder function for stabilizing urinary volume overnight with recording of brain waves (ABSORB study)

AbstractObjectivesThe bladder urothelium is not always impermeable. During sleep, the bladder might absorb urine in healthy individuals who sleep through the night. This study aimed to determine whether the bladder absorbs urine by using a method other than ultrasonic scanning and to simultaneously evaluate sleeping conditions.MethodsEleven participants (five males, six females) aged 20 to 49 years without lower urinary tract symptoms or urination while sleeping were enrolled. Bladder volume was estimated by studying the relationship between dilution and absorbance of indigo carmine dissolved in urine. A 12F Foley catheter was inserted into the bladder before sleep. Urine samples (5 mL) were extracted at 2, 3, 4, 5, and 6 am sleep stages were monitored with a single‐channel portable electroencephalograph device.ResultsThe estimated bladder volume at 6 am and voided volume immediately after rising were significantly correlated (Spearman's ρ = 0.62, P = .046). Eight participants (three males, five females) showed an absorption pattern of the estimated bladder volume change. In a male participant, the blue dye's strength gradually decreased until 4 am (estimated 859 mL) and increased from 5 am (estimated 455 mL). In another, the blue dye's strength increased at 4 am (estimated 449 mL) vs at 3 am (estimated 757 mL). In all participants, electroencephalograph data demonstrated that sleep was maintained despite having a full bladder.ConclusionsThe bladder absorbs urine and maintains an approximate volume of functional bladder capacity during sleep to avoid incontinence and maintain sleep in adults due to an urge to void urine during the sleep cycle.

Forward-Looking Ultrasound Wearable Scanner System for Estimation of Urinary Bladder Volume.

Accurate measurement of bladder volume is an important tool for evaluating bladder function. In this study, we propose a wearable bladder scanner system that can continuously measure bladder volume in daily life for urinary patients who need urodynamic studies. The system consisted of a 2-D array, which included integrated forward-looking piezoelectric transducers with thin substrates. This study aims to estimate the volume of the bladder using a small number of piezoelectric transducers. A least-squares method was implemented to optimize an ellipsoid in a quadratic surface equation for bladder volume estimation. Ex-vivo experiments of a pig bladder were conducted to validate the proposed system. This work presents the potential of the approach for wearable bladder monitoring, which has similar measurement accuracy compared to the commercial bladder imaging system. The wearable bladder scanner can be improved further as electronic voiding diaries by adding a few more features to the current function.

High prevalence of lower urinary tract dysfunction in patients with Prader-Willi syndrome.

To report the first noninvasive urodynamic screening of lower urinary tract dysfunction (LUTD) in children, adolescents, and young adults with Prader-Willi Syndrome (PWS). We recruited 37 PWS patients with/without lower urinary tract symptoms (LUTS) from our hospital. Uroflowmetry was performed in 36 patients. In addition, 20 patients underwent postvoid residual urine (PVR) measurement by transabdominal ultrasound. LUTD is defined as abnormal uroflow patterns, low peak flow rate (Qmax ), or elevated PVR by age. Videourodynamic study (VUDS) was performed in selected cases. Mean and median age of the patients were 17.7 ± 7.8 years and 16 years. Male to female ratio was 15/22. Two patients were excluded from the following analysis because of voided volume less than or equal to 50 ml. Of the remaining 34 uroflowmetry examination, normal voiding pattern (bell shape) was observed in 22 (64.7%) patients. Abnormal uroflowmetry pattern were obstructive in 6 (17.6%), staccato in 3 (8.8%), intermittent in 2 (5.8%), tower in 1 (2.9%), and plateau in 0 patients. Ten (29.4%) patients had a Qmax less than 15 ml/s. Of 20 patients undergoing PVR tests 10 (50%) had elevated PVR by age ( > 6% of estimated bladder volume). In all, 17/34 (50.0%) PWS patients had at least one abnormality of the noninvasive tests. Of the three cases undergoing VUDS all showed detrusor sphincter dyssynergia. Half of PWS patients with/without LUTS had LUTD. Noninvasive study such as uroflowmetry and postvoid residual urine by ultrasound is recommended to all patients with PWS.

Three-dimensional bladder ultrasound for estimation of urine volume in dogs compared with traditional 2-dimensional ultrasound methods.

BackgroundAlthough point‐of‐care volumetric assessments of the urinary bladder are not routinely performed in dogs, urine volume quantification can provide important clinical information including noninvasive urine output estimation.Hypothesis/ObjectiveUse of 3‐dimensional (3D) ultrasound for determination of urinary bladder volume (UBV) in dogs will be accurate for different bladder volumes and will decrease the need for operator skill in measuring UBV compared to 2‐dimensional (2D) ultrasound evaluation.AnimalsTen laboratory‐bred Beagle dogs.MethodsProspective, experimental study. Urinary bladders were infused with a calculated amount of sterile saline to represent small, medium, and large volumes. Each UBV was estimated and calculated by a board‐certified veterinary radiologist using 3 different 2D ultrasound formulas followed by use of a 3D ultrasound device by a novice. Measured UBVs were compared to the instilled UBV for both 2D and 3D ultrasound methods. Time from start to end of examination was recorded for both ultrasound methods in a subset of dogs.ResultsThe 3D ultrasound device underestimated UBV with a mean difference of −9.8 mL compared with 2D ultrasound that overestimated UBV with a difference of +4.2 to 20.3 mL dependent on the 2D formula used. The 3D ultrasound method took less time to measure UBV (mean of 80 seconds per measurement) compared to the 2D method (165 seconds per measurement; P = .02).Conclusions and Clinical ImportanceThe tested 3D ultrasound device was found to be an accurate and rapid point‐of‐care tool for measuring UBV in dogs, providing a noninvasive method to estimate bladder volume in real time.

Simple calculation using anatomical features on pre-treatment verification CT for bladder volume estimation during radiation therapy for rectal cancer

BackgroundDespite detailed instruction for full bladder, patients are unable to maintain consistent bladder filling during a 5-week pelvic radiation therapy (RT) course. We investigated the best bladder volume estimation procedure for verifying consistent bladder volume.MethodsWe reviewed 462 patients who underwent pelvic RT. Biofeedback using a bladder scanner was conducted before simulation and during treatment. Exact bladder volume was calculated by bladder inner wall contour based on CT images (Vctsim). Bladder volume was estimated either by bladder scanner (Vscan) or anatomical features from the presacral promontory to the bladder base and dome in the sagittal plane of CT (Vratio). The feasibility of Vratio was validated using daily megavoltage or kV cone-beam CT before treatment.ResultsMean Vctsim was 335.6 ± 147.5 cc. Despite a positive correlation between Vctsim and Vscan (R2 = 0.278) and between Vctsim and Vratio (R2 = 0.424), Vratio yielded more consistent results than Vscan, with a mean percentage error of 26.3 (SD 19.6, p < 0.001). The correlation between Vratio and Vctsim was stronger than that between Vscan and Vctsim (Z-score: − 7.782, p < 0.001). An accuracy of Vratio was consistent in megavoltage or kV cone-beam CT during treatment. In a representative case, we can dichotomize for clinical scenarios with or without bowel displacement, using a ratio of 0.8 resulting in significant changes in bowel volume exposed to low radiation doses.ConclusionsBladder volume estimation using personalized anatomical features based on pre-treatment verification CT images was useful and more accurate than physician-dependent bladder scanners.Trial registrationRetrospectively registered.

Advances in Ambulatory Urodynamics.

This manuscript reviews recent technological advances in ambulatory urodynamics. Ambulatory urodynamics is currently recommended by the International Continence Society as a second-line diagnostic tool in patients with nondiagnostic traditional urodynamics. Novel techniques involving telemetric monitoring are in development, which utilize catheter-free wireless systems to address several recognized shortcomings of inoffice urodynamic studies. Current research in catheter-free bladder pressure measurements involves either an intravesical, intradetrusor, or transdetrusor approach. Real-time bladder volume estimation may be performed using ultrasonography, near-infrared spectroscopy, or bladder volume conductance measurement. Ambulatory urodynamics can measure bladder function in the "real world" setting, capturing physiological bladder filling and emptying and allowing patients to reproduce the activities that may trigger their symptoms. Telemetric devices being developed represent further advances in this field and focus upon improving diagnostic capabilities, evaluating patient response to treatment, and facilitating closed-loop bladder control with neuroprosthetic integration.

Urinary Bladder Test Device to Integrate Basic Ultrasound Training for Nurses

Ultrasound is a useful tool for integrating clinical assessment with a bedside reliable imaging technique, but it requires adequate training. Ultrasonographic training involves examination performed on human models, in which many pathologic findings are not always readily available for the trainee to observe. The possibility of creating test objects that reproduce pathologic images allows the provision of training courses with those elements that are not always available. Our aims were to describe how to create a urinary bladder test object and to test its image quality and usefulness. Thus, we compared computed volume with the actual filling volume for five different devices to assess their reliability in volume estimation. Moreover, we evaluated the image quality and teaching utility using a 5-point Likert-type questionnaire among a group of learners. Computed bladder volume had excellent correlation with actual filling volume (p < 0.001, R2 = 0.9874). Trainees judged the ultrasound exploration realistic and considered the device useful in understanding ultrasound images and improving ultrasound skills. In conclusion, our device contributes to ultrasound training by providing a realistic ultrasound image, improving image understanding and skill development and allowing reliable bladder volume estimation.

Robustness of focused and global impedance estimates of bladder volumes against uncertainty of urine conductivity

Bioimpedance measurements are currently used to monitor various biological processes and are potentially useful for studies of urodynamics. Global impedance (GI) and focused impedance measurements (FIM) can be used to monitor bladder volumes, but these are subject to varying conductivity of urine. To address this, we emulated a human bladder using an agar phantom filled with saline solutions of varying conductivities and estimated volumes using a modified FIM-based approach. Using this novel strategy, electrical potentials did not change significantly with constant liquid volumes, even when the conductivity of the saline solutions was varied between 1.027 to 1.877 and 2.610 S/m. Conversely, GI and classic FIM measurements of constant liquid volumes varied with conductivity. These observations suggest that the proposed FIM approach is suitable for bladder volume estimation due to its robustness against uncertainties of conductivity. The bioimpedance hardware used in our experiments comprised 8 electrodes and a a small and low cost impedance measurement system based on an AFE4300 direct impedance measurement device.

Estimation of Bladder Pressure and Volume from the Neural Activity of Lumbosacral Dorsal Horn Using a Long-Short-Term-Memory-based Deep Neural Network

In this paper, we propose a deep recurrent neural network (DRNN) for the estimation of bladder pressure and volume from neural activity recorded directly from spinal cord gray matter neurons. The model was based on the Long Short-Term Memory (LSTM) architecture, which has emerged as a general and effective model for capturing long-term temporal dependencies with good generalization performance. In this way, training the network with the data recorded from one rat could lead to estimating the bladder status of different rats. We combined modeling of spiking and local field potential (LFP) activity into a unified framework to estimate the pressure and volume of the bladder. Moreover, we investigated the effect of two-electrode recording on decoding performance. The results show that the two-electrode recordings significantly improve the decoding performance compared to single-electrode recordings. The proposed framework could estimate bladder pressure and volume with an average normalized root-mean-squared (NRMS) error of 14.9 ± 4.8% and 19.7 ± 4.7% and a correlation coefficient (CC) of 83.2 ± 3.2% and 74.2 ± 6.2%, respectively. This work represents a promising approach to the real-time estimation of bladder pressure/volume in the closed-loop control of bladder function using functional electrical stimulation.