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Noninvasive Diagnosis of Bladder Outlet Obstruction in Patients with Lower Urinary Tract Symptoms Using Ultrasound Decorrelation Analysis
Author's Accepted Manuscript Non-invasive diagnosis of urinary bladder outlet obstruction in patients with lower urinary tract symptoms using ultrasound decorrelation analysis Muhammad Arif , Jan Groen , Egbert R Boevé , Chris L. de Korte , Tim Idzenga , Ron van Mastrigt
PII: DOI: Reference:
S0022-5347(16)03353-X 10.1016/j.juro.2016.02.2966 JURO 13533
To appear in: The Journal of Urology Accepted Date: 23 February 2016 Please cite this article as: Arif M, Groen J, Egbert Boevé R, de Korte CL, Idzenga T, van Mastrigt R, Non-invasive diagnosis of urinary bladder outlet obstruction in patients with lower urinary tract symptoms using ultrasound decorrelation analysis, The Journal of Urology® (2016), doi: 10.1016/ j.juro.2016.02.2966. DISCLAIMER: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our subscribers we are providing this early version of the article. The paper will be copy edited and typeset, and proof will be reviewed before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to The Journal pertain.
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ACCEPTED MANUSCRIPT Title: Non-invasive diagnosis of urinary bladder outlet obstruction in patients with lower urinary tract symptoms using ultrasound decorrelation analysis.
Authors:
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Muhammad Arif1, Jan Groen1, Egbert R.Boevé3, Chris L. de Korte2 , Tim Idzenga1,4 and Ron van Mastrigt1
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Institute:
Department of Urology, Sector Furore, Erasmus Medical Centre, Rotterdam, The Nederlands
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Medical UltraSound Imaging Center (MUSIC) Department of Radiology and Nuclear Medicine, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands. 3
Dept. Urology, Sint Franciscus Gasthuis, Dept. Urology Havenziekenhuis Rotterdam, The Netherlands 4
Dept. Urology, Academic Medical Center, Amsterdam, the Netherlands
Muhammad Arif Dr. Molewaterplein 50
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Correspondence to:
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Room EE1630 Erasmus MC,
3015 GE Rotterdam, The Netherlands
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Email: [email protected] phone : +31 10 7043379 fax : +31 10 7044726
www.erasmusmc.nl/urologie/research/Furore/ Required disclosures This research was supported by the Dutch Technology Foundation STW (NIG 10896).
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Abstract
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Aim: To develop a non-invasive method for diagnosing Bladder Outlet Obstruction (BOO),
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an ultrasound based decorrelation method was applied in male patients with Lower Urinary
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Tract Symptoms (LUTS).
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Materials and Methods: In 60 patients ultrasound data were acquired transperineally while
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they were voiding in sitting position. Each patient also underwent a standard invasive
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pressure-flow study (PFS).
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Results: High frequent sequential ultrasound images were successfully recorded during
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voiding in 45 patients. The decorrelation (decrease in correlation) between subsequent
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ultrasound images was higher in patients with BOO than in unobstructed patients and healthy
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volunteers. Receiver Operating Characteristic (ROC) analysis resulted in an area under the
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curve (AUC) of 0.96, a 95% specificity and 88% sensitivity. A linear relationship was fitted
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to the decorrelation values as a function of the degree of obstruction represented by the
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Bladder Outlet Obstruction Index (BOOI), measured in the separate PFS .
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Conclusion: It is possible to non-invasively diagnose BOO using the ultrasound decorrelation
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technique.
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Keywords: Decorrelation, Urinary bladder outlet obstruction, Ultrasound, Non-invasive
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diagnosis.
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Introduction Benign prostatic enlargement often leads to Bladder Outlet Obstruction (BOO) in
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elderly men. Nocturia, low urinary flow rate, post-void dribbling and post-void residual
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volume are common symptoms of BOO. Urodynamic pressure-flow studies (PFS) are used as
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the standard procedure to diagnose BOO (1). A major disadvantage of this method is the
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urethral catheterization, which causes partial obstruction during micturition and may alter the
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diagnostic results. The invasive nature of the procedure also causes discomfort and pain to the
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patients and might result in infection. Therefore, the development of a non-invasive
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alternative method of diagnosing BOO is needed. A variety of non-invasive and more patient
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friendly diagnostic methods for BOO, such as the condom catheter method, the penile cuff
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method, perineal sound recording, ultrasonic measurement of bladder wall thickness and
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Doppler flowmetry (2-6) have been proposed. All of these techniques have some drawbacks
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and none of them has been applied routinely in clinical practice.
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To develop an accurate clinical urodynamic method to diagnose BOO, we applied a
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non-invasive ultrasound (US) decorrelation based technique to quantify flow velocity and
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turbulence in silica gel urethra models (7, 8). This technique is based on comparing the scatter
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pattern in a group of images constructed from sequentially acquired ultrasound
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radiofrequency (RF) signals due to reflections from small scattering particles. If the particles
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move slowly the images will be similar, that is, they will be highly correlated. If the particles
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move fast, then the images will be less similar and the correlation will be less, that is, there
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will be a higher decorrelation. In urine various types of crystals such as calcium oxalate, uric
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acid and amorphous urates have been identified (9, 10). These crystalline structures can act as
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small ultrasound scattering particles. In a previous study (11) we showed that morning urine
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contains a sufficient concentration of these scattering materials to be suitable for US imaging
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of urinary flow using the decorrelation method. We subsequently tested and applied the
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velocity (12). In a phantom with increasing severity of obstruction we found higher
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decorrelation values than in the unobstructed urethra models at the same flow velocity. This
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was due to turbulent flow as a result of an obstruction (8). On this basis we hypothesized that
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in patients suffering from BOO we could find higher decorrelation values than in the healthy
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volunteers at the same flow velocity and it might be possible to develop a practical method for
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noninvasively diagnosing BOO in male patients with lower urinary tract symptoms (LUTS).
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In the present study, we applied the decorrelation method in patients with LUTS to diagnose
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BOO and compared the results with conventional PFS.
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Materials & Methods
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Population
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Following institutional research ethics board approval (MEC-2013-419), we recruited 60 male
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patients with LUTS, suggestive of BOO in the period January – October 2015. All patients
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gave their informed consent. Completing an International Prostate Symptom Score (IPSS)
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form to quantify their urological condition was part of routine practice.
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Experimental setup
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Each patient voided in a sitting position with an ultrasound transducer gently placed
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against the perineum using a specially designed chair with a mechanical transducer
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manipulator (Fig 1(A)). Each patient was asked before voiding to void without straining. To
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adequately visualize the urethra, the transducer was manually moved in angular and sidewise
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directions by the investigator using the vertical handle (Figure 1(B)). To acquire RF US data
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of the urinary stream a BK-Medical system (Pro Focus UltraView 2202) with a custom
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designed RF interface was used. The US data acquisition was synchronized with the flow rate
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signal. The voided volume was measured at each voiding using a measuring jug.
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Data acquisition From each patient we acquired four measurements. The 1st measurement was a free
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flow measurement, that is, a flow measurement without transurethral catheter, with US data
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acquisition. The following two were conventional invasive PFS done by the Andromeda
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urodynamic system (Medizinische Systeme GmbH, Potzdam Germany) without US data
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acquisition. Finally, the bladder of the patient was refilled with a saline solution to which we
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added approximately 4x105 microbubbles/litter (SonoVue, Braco International B.V.
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Amsterdam, the Netherlands) to enhance the US reflection by the scattering particles.
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catheter was then removed and again a free flow measurement with US data acquisition was
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recorded. We acquired 5 seconds of US data at different flow rates (maximum and sub-
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maximum) during a complete voiding cycle. Each US frame contained 10 sequential US RF
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data sets. Every RF data set consisted of 142 RF-signals acquired at a Pulse Repetition
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Frequency (PRF) of 0.5 kHz. Each RF-signal yielded a single image-line in an US B mode
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image.
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Correlation coefficients: To calculate the correlation between two sequential images in a US
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frame, two corresponding image lines were selected from two sequential images and the
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correlation coefficient was calculated (13). This process was repeated for all consecutive 142
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image lines and one correlation image was constructed from two sequential US images as
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shown in Figure 3(B) & 3(D). For each US frame, consisting of 10 US RF-data sets, 6
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correlation images were thus constructed. In each correlation image a Region of Interest (ROI
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= length 1.8 cm) was manually selected and the mean correlation value was calculated (see
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Figure 3). Next we calculated the average (ρ ) of these ρ values over the 6 correlation
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images of each US frame. The calculated average correlation values ρ were plotted as a
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function of the flow velocity. (a more detailed description of the correlation coefficients calculation can be found in Arif et al. (7)). Relationship between decorrelation and degree of obstruction
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To define a relationship between the decorrelation and the degree of obstruction we
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fitted a curve through the decorrelation and flow velocity data acquired in healthy volunteers
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using Equation 1 (see Appendix). Next we calculated the differences between the correlation
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values of equation 1 and the patients correlation values at the same flow velocity
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(experimental quantification parameter of BOO). We plotted these as a function of Bladder
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Outlet Obstruction Index (BOOI), which was used as the gold standard quantification
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parameter for the degree of BOO (14). In each patient the BOOI, was calculated by the
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Andromeda urodynamic system (Medizinische Systeme GmbH, Potzdam Germany). A linear
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relation was fitted to the data (see Appendix).
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From Equation 1, we subtracted the correlation difference calculated using equation 2 at
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BOOI values of 20 and 40, thus creating correlation-velocity boundary curves for these values
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in a correlation-velocity nomogram. We also calculated the Receiver Operating Characteristic
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(ROC) curve to test the diagnostic value of the method (see Figure 6). To this end, patients
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were stratified in two groups on the basis of invasive PFS. Patients with BOOI of 40 or less
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were labelled unobstructed ( i.e. equivocal or unobstructed according to the standard BOOI
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nomogram) and those with higher BOOI were labelled obstructed. The area under the curve
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(AUC) shows the percentage of the patients that are correctly diagnosed by the method. The
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specificity and sensitivity of the decorrelation method were also calculated.
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Results
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Population
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We included 60 patients. Five patients were not able to void during the complete
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examination. From these 5 patients, 3 patients had an indwelling catheter. Five patients were
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US data was not usable due to a wrong positioning of the transducer or due to movement of
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the patient during voiding. In the remaining 45 (75%) patients, at least one US urinary flow
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data was recorded. The voided volume, maximum free flow rate, age, IPSS and BOOI of
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these 45 patients are shown in Table 1. The pressure-flow nomogram of the patients is shown
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in Figure 4(B).
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In-vivo Results
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A typical urinary flow rate curve of a volunteer and a patient are shown in Figure
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2(A) & 2(C). The flow rate values corresponding to the 50 acquired US frames are shown in
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Figure 2(B) & 2(D). An example of an in vivo US B-mode image of the urethra of a healthy
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volunteer and an obstructed patient during voiding is shown in Figure 3(A) & 3(C). The
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correlation images constructed from the 1st and 5th US RF-data set are overlaid on the B-mode
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images (see Figure 3(B) & 3(D)). The ROI distal to the prostatic urethra is also visible. A plot
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of the calculated values as a function of flow velocity for volunteers and patients is
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shown in Figure 4(A). The diagram shows that the correlation coefficients of the obstructed
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patients were lower than those of the healthy volunteers at the same flow velocity, that is, the
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decorrelation was higher in these patients.
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Decorrelation-Degree of obstruction relationship In Figure 5 (A), we plotted the difference in of patients and the model fitted to
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the healthy volunteers data as a function of BOOI. The difference between the correlation
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values increased with the degree of obstruction. The R-square value of the fitted linear model
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was 0.55 with parameters = 0.0041 and = -0.074. In Figure 5(B), we constructed the
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nomogram to categorize the patients in different obstruction levels based on the US
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correlation data values. It illustrates that 86%, that is, 39 out of 45 patients could be classified
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correctly. In ROC analysis, an AUC value of 0.96 signified a diagnostic accuracy of 96% (See
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Figure 6). The specificity and sensitivity of the method were 95% and 88%. Discussion
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The standard procedure to diagnose BOO involves urethral catheterization which is
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uncomfortable to patients and may also cause infections of the urinary tract. Therefore a non-
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invasive urodynamic method to diagnose BOO is desirable. In this study we applied US
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decorrelation analysis on patients with LUTS to diagnose BOO and compared the results with
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standard PFS.
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In 45 out of 60 patients we successfully recorded the US urinary flow data. The
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principle finding of the study is that in patients with BOO the correlation values are decreased
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with respect to the healthy volunteers as shown in Figure 3 and Figure 4(A). The reason for
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this higher decorrelation could be that the narrowing in the urinary flow channel due to the
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urethral obstruction results in a disturbed (turbulent) urinary flow. The correlation difference
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plotted as a function of BOOI shows that the decorrelation is significantly correlated with
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BOOI. By measuring the decorrelation using US it might be possible to estimate BOOI in
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patients with voiding symptoms. Categorization of patients in different obstruction levels
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using BOOI is illustrated in Figure 5(B). In an ideal situation all the obstructed patients
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should have correlation values below the BOOI=40 curve, however the fitted relation to
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estimate BOOI from the decorrelation could be a source of error.
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In a previous study in healthy volunteers (12) US data during voiding were acquired in
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the standing position. In the present study patients urinary flow US data were acquired in the
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sitting position. In a meta-analysis by De Jong et al. (15) no difference in urinary flow rate of
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healthy men in sitting or standing position was found. Therefore the correlation data of
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healthy volunteers in standing position can be compared to the data of the patients acquired in
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the sitting position. We preferred to do the measurement in the sitting position for patients,
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often elderly, as it was easier to void sitting while also preventing motion artefacts. The study
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including the adjustment of the transducer and US data acquisition for each patient took 5
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minute maximum. In some other non-invasive techniques, such as the cuff method, a minimum voided
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bladder volume (≥ 150ml) has been reported (16). However, a thorough statistical analysis of
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the volume dependence of the reliability of the method was not possible as only two patients
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voided less than 100 ml. Considering our method we had no indication that a small voided
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volume made the method unreliable. In Table 1, for patient 29 the voided volume was 30ml
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and the US data was successfully acquired.
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To check the reproducibility of the method, we acquired US data in 5 patients at two
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different times. The average calculated correlation (ρ ) values for each patient are shown in
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table 2. The data shows that the correlation coefficient values acquired at different times are
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almost similar at similar flow velocity values, but it decreased with an increase in flow
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velocity. However, the US diagnostic status of the patient remained the same.
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Ozawa et al. (2010) used color Doppler US to measure urinary flow velocity in BOO
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patients and compared their results with those of a pressure flow study. They measured the
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urine flow velocity transperineally in the distal prostatic urethra just above the external
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sphincter and in the sphincteric urethra. However, urethral obstruction can create turbulence
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in the flow and lead to an aliasing effect in the color Doppler signals. This makes Doppler
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ultrasound less suitable for estimating the urine flow velocity. To solve this problem we
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measured the cross-sectional area from the images that were also used for the decorrelation
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analysis. From this the flow velocity was calculated at the same flow rate that was used to
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perform the decorrelation analysis.
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bladder can be refilled and the diagnostic process can be repeated. In addition, with a catheter
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present, information on the storage phase of the micturition cycle can be obtained. In the non-
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invasive decorrelation method, patients are not catheterized and repeating the study can only
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be done after natural refilling of the bladder which takes time. Additionally, the decorrelation
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method depends on particle concentration (11). A high fluid intake with subsequent dilution
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of urine could therefore affect the results. Future studies should address this aspect of the
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decorrelation method. However, these disadvantages are more than compensated by the non-
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invasive nature of the method.
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The results show that the decorrelation based analysis of US data could be used clinically to
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diagnose BOO. However, the method needs to be tested with more optimized and more easily
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controllable equipment. The urologist or technician needs to be trained to get good US data
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during voiding. Real time software which performs the decorrelation analysis and calculates a
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BOOI value based on the correlation-velocity nomogram could make the technique more
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readily and easily applicable.
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Conclusion
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Decorrelation based analysis of urinary flow US data showed that the decorrelation
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was higher in obstructed patients than in unobstructed patients and healthy volunteers at the
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same flow velocity. The relationship between BOOI and differences in correlation values of
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patients and the fitted curve of healthy volunteers showed that the degree of BOO can be non-
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invasively estimated using US decorrelation analysis and the measured correlation values can
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be used to diagnose BOO in male patients with high specificity (95%), sensitivity (88%) and
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a diagnostic accuracy of 96%.
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Appendix Relationship between decorrelation and degree of obstruction
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The function fitted curve to the decorrelation and flow velocity data acquired in healthy
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volunteers was:
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() = () + c
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(1)
where a, b and c are parameters and k is volunteer number (1,2 …18) (12).
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The difference in correlation between healthy subjects and patients as a function of the
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Bladder Outlet Obstruction Index (BOOI) was defined as:
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where = 0.0041 and = -0.074 are parameters.
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1. Griffiths D, Hofner K, van Mastrigt R, Rollema HJ, Spangberg A, Gleason D. Standardization of terminology of lower urinary tract function: pressure-flow studies of voiding, urethral resistance, and urethral obstruction. International Continence Society Subcommittee on Standardization of Terminology of Pressure-Flow Studies. Neurourol Urodyn. 1997;16(1):1-18. 2. Pel JJ, van Mastrigt R. Non-invasive measurement of bladder pressure using an external catheter. Neurourol Urodyn. 1999;18(5):455-69; discussion 69-75. 3. Idzenga T, Pel JJM, Baldewsing RA, Mastrigt Rv. Perineal noise recording as a noninvasive diagnostic method of urinary bladder outlet obstruction: a study in polyvinyl alcohol and silicone model urethras. Neurourol Urodyn. 2005;24(4):381-8. 4. Griffiths CJ, Rix D, MacDonald AM, Drinnan MJ, Pickard RS, Ramsden PD. Noninvasive measurement of bladder pressure by controlled inflation of a penile cuff. J Urol. 2002 Mar;167(3):1344-7. 5. Manieri C, Carter SS, Romano G, Trucchi A, Valenti M, Tubaro A. The diagnosis of bladder outlet obstruction in men by ultrasound measurement of bladder wall thickness. J Urol. 1998 Mar;159(3):761-5. 6. Ozawa H, Igarashi T, Uematsu K, Watanabe T, Kumon H. The future of urodynamics: Non-invasive ultrasound videourodynamics. Int J Urol. 2010;17(3):241-9. 7. Arif M, Idzenga T, van Mastrigt R, de Korte CL. Estimation of Urinary Flow Velocity in Models of Obstructed and Unobstructed Urethras by Decorrelation of Ultrasound Radiofrequency Signals. Ultrasound Med Biol. 2014 Jan 9:938-46. 8. Arif M, Idzenga T, de Korte CL, van Mastrigt R. Development of a noninvasive method to diagnose bladder outlet obstruction based on decorrelation of sequential ultrasound images. Urology. 2015 Mar;85(3):648-52. 9. Verdesca S, Fogazzi GB, Garigali G, Messa P, Daudon M. Crystalluria: prevalence, different types of crystals and the role of infrared spectroscopy. Clin Chem Lab Med. 2011 Mar;49(3):515-20. 10. Elliot JS, Rabinowitz IN. Calcium-Oxalate Crystalluria - Crystal Size in Urine. J Urology. 1980;123(3):324-7. 11. Arif M, Idzenga T, de Korte CL, van Mastrigt R. Dependence of ultrasound decorrelation on urine scatter particle concentration for a non-invasive diagnosis of bladder outlet obstruction. Neurourol Urodyn. 2015 Nov;34(8):781-6. 12. Arif M, Idzenga T, van Mastrigt R, de Korte CL. Diagnosing Bladder Outlet Obstruction Using Non-invasive Decorrelation-Based Ultrasound Imaging: A Feasibility Study in Healthy Male Volunteers. Ultrasound in Medicine & Biology Vol. 41, No. 12, pp. 3163–3171, 2015. 13. Lupotti FA, van der Steen AF, Mastik F, de Korte CL. Decorrelation-based blood flow velocity estimation: effect of spread of flow velocity, linear flow velocity gradients, and parabolic flow. IEEE Trans Ultrason Ferroelectr Freq Control. 2002 Jun;49(6):705-14. 14. Abrams P. Bladder outlet obstruction index, bladder contractility index and bladder voiding efficiency: three simple indices to define bladder voiding function. BJU Int. 1999 Jul;84(1):14-5. 15. de Jong Y, Pinckaers JHFM, ten Brinck RM, Nijeholt AABLA, Dekkers OM. Urinating Standing versus Sitting: Position Is of Influence in Men with Prostate Enlargement. A Systematic Review and Meta-Analysis. Plos One. 2014 Jul 22;9(7). 16. McIntosh S, Pickard RS, Drinnan M, et al. Non invasive measurement of bladder pressure: minimum voided volume and test/retest reproducibility. Paper presented at: Annual Meeting of the International Continence Society; August 27–29, 2002; Heidelberg, Germany.
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Legends Figure 1: (A) Schematic drawing and (B) picture of the experimental setup. The US transducer position was controlled by a specially designed manual probe manipulator.
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Figure 2: A typical flow rate curve of a healthy volunteer (A & B) and an obstructed patient (C & D) as a function of time. Figure 3:
(A) Example of in vivo US B-mode image and (B) Correlation coefficient
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distribution overlaid on the US B-mode image of the urethra during voiding of a healthy volunteer. (C) Example of in vivo US B-mode image and (D) Correlation coefficient
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distribution overlaid on the US B-mode image of the urethra during voiding of an obstructed patient (BOOI = 75 ). The Region of Interest (ROI) and the measured urethra diameter are also shown. 1 represents to high correlation and 0 to low correlation.
Figure 4: (A) The calculated average correlation coefficients and fitted function of 18
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healthy volunteers and correlation values of 45 patients plotted as a function flow velocity. The patients were categorized as obstructed/unobstructed or equivocal based on a standard pressure-flow studies. (B) A pressure flow nomogram to classify the 45 patients as
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obstructed/unobstructed or equivocal based on pressure-flow studies.
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Figure 5: (A) Difference in correlation between healthy subjects and patients plotted as a function of BOOI. (B) Correlation-velocity nomogram to diagnose BOO in LUTS patients. The patients were categorized as obstructed/unobstructed or equivocal based on a standard pressure-flow studies.
Figure 6: Receiver Operating Characteristic curve (ROC) of the non-invasive decorrelation method with an area under the curve (AUC) of 0.96.
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Voided Urine Volume (ml) 760 150 425 470 155 250 325 295 280 290 472 300 160 180 156 250 255 170 265 490 220 200 290 170 220 200 260 250 30 240 710 300 160 360 240 340 390 200 325 150 100 200 175 300 230
BOOI
13 11 10 12 3 12 5 5 5 5 10 7 5 13 12 15 14 5 4 16 13 13 13 5 5 14 10 10 11 9 15 14 7 20 10 7 8 12 8 11 3 14 6 5 8
29 54 19 6 53 75 92 63 68 45 27 28 22 81 40 45 5 161 116 -21 72 5 33 54 99 69 42 18 -2 42 1 31 66 63 93 57 33 8 111 29 35 -16 34 104 50
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1 50 15 2 77 10 3 70 23 4 65 22 5 65 27 6 55 11 7 80 18 8 72 18 9 74 15 10 66 24 11 61 22 12 53 23 13 90 No 14 80 17 15 76 21 16 83 18 17 51 24 18 68 23 19 54 20 20 61 16 21 59 18 22 70 13 23 64 10 24 74 10 25 64 No 26 78 14 27 68 18 28 77 33 29 59 19 30 50 31 31 54 11 32 72 25 33 67 8 34 70 No 35 72 No 36 77 18 37 72 No 38 79 No 39 65 17 40 78 No 41 80 7 42 72 No 43 51 No 44 65 No 45 67 No No = IPSS of the patients were not recorded.
Maximum Flow rate (ml/s)
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flow velocity (cm/s) 13 5 30 12 20
Correlation values (ૉ) ܞ܉ 0.8781 0.9820 0.7976 0.9504 0.7914
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Decorrelation method
Pressureflow study
Obstructed Obstructed Unobstructed Unobstructed Obstructed
Obstructed Obstructed Equivocal Equivocal Obstructed
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Correlation values (ૉ) ܞ܉ 0.8881 0.9903 0.6875 0.9683 0.8617
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2 5 11 12 15
flow velocity (cm/s) 11 2 44 12 15
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ACCEPTED MANUSCRIPT BOO
= Bladder Outlet Obstruction
US
= Ultrasound
RF
= Radiofrequency
PFS
= pressure-flow studies
ROI = Region Of Interest
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BOOI = Bladder Outlet Obstruction Index
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LUTS = Lower Urinary Tract Symptoms
PII: DOI: Reference:
S0022-5347(16)03353-X 10.1016/j.juro.2016.02.2966 JURO 13533
To appear in: The Journal of Urology Accepted Date: 23 February 2016 Please cite this article as: Arif M, Groen J, Egbert Boevé R, de Korte CL, Idzenga T, van Mastrigt R, Non-invasive diagnosis of urinary bladder outlet obstruction in patients with lower urinary tract symptoms using ultrasound decorrelation analysis, The Journal of Urology® (2016), doi: 10.1016/ j.juro.2016.02.2966. DISCLAIMER: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our subscribers we are providing this early version of the article. The paper will be copy edited and typeset, and proof will be reviewed before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to The Journal pertain.
Embargo Policy All article content is under embargo until uncorrected proof of the article becomes available online. We will provide journalists and editors with full-text copies of the articles in question prior to the embargo date so that stories can be adequately researched and written. The standard embargo time is 12:01 AM ET on that date. Questions regarding embargo should be directed to [email protected].
ACCEPTED MANUSCRIPT Title: Non-invasive diagnosis of urinary bladder outlet obstruction in patients with lower urinary tract symptoms using ultrasound decorrelation analysis.
Authors:
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Muhammad Arif1, Jan Groen1, Egbert R.Boevé3, Chris L. de Korte2 , Tim Idzenga1,4 and Ron van Mastrigt1
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Institute:
Department of Urology, Sector Furore, Erasmus Medical Centre, Rotterdam, The Nederlands
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Medical UltraSound Imaging Center (MUSIC) Department of Radiology and Nuclear Medicine, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands. 3
Dept. Urology, Sint Franciscus Gasthuis, Dept. Urology Havenziekenhuis Rotterdam, The Netherlands 4
Dept. Urology, Academic Medical Center, Amsterdam, the Netherlands
Muhammad Arif Dr. Molewaterplein 50
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Correspondence to:
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Room EE1630 Erasmus MC,
3015 GE Rotterdam, The Netherlands
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Email: [email protected] phone : +31 10 7043379 fax : +31 10 7044726
www.erasmusmc.nl/urologie/research/Furore/ Required disclosures This research was supported by the Dutch Technology Foundation STW (NIG 10896).
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Abstract
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Aim: To develop a non-invasive method for diagnosing Bladder Outlet Obstruction (BOO),
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an ultrasound based decorrelation method was applied in male patients with Lower Urinary
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Tract Symptoms (LUTS).
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Materials and Methods: In 60 patients ultrasound data were acquired transperineally while
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they were voiding in sitting position. Each patient also underwent a standard invasive
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pressure-flow study (PFS).
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Results: High frequent sequential ultrasound images were successfully recorded during
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voiding in 45 patients. The decorrelation (decrease in correlation) between subsequent
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ultrasound images was higher in patients with BOO than in unobstructed patients and healthy
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volunteers. Receiver Operating Characteristic (ROC) analysis resulted in an area under the
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curve (AUC) of 0.96, a 95% specificity and 88% sensitivity. A linear relationship was fitted
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to the decorrelation values as a function of the degree of obstruction represented by the
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Bladder Outlet Obstruction Index (BOOI), measured in the separate PFS .
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Conclusion: It is possible to non-invasively diagnose BOO using the ultrasound decorrelation
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technique.
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Keywords: Decorrelation, Urinary bladder outlet obstruction, Ultrasound, Non-invasive
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diagnosis.
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Introduction Benign prostatic enlargement often leads to Bladder Outlet Obstruction (BOO) in
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elderly men. Nocturia, low urinary flow rate, post-void dribbling and post-void residual
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volume are common symptoms of BOO. Urodynamic pressure-flow studies (PFS) are used as
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the standard procedure to diagnose BOO (1). A major disadvantage of this method is the
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urethral catheterization, which causes partial obstruction during micturition and may alter the
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diagnostic results. The invasive nature of the procedure also causes discomfort and pain to the
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patients and might result in infection. Therefore, the development of a non-invasive
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alternative method of diagnosing BOO is needed. A variety of non-invasive and more patient
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friendly diagnostic methods for BOO, such as the condom catheter method, the penile cuff
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method, perineal sound recording, ultrasonic measurement of bladder wall thickness and
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Doppler flowmetry (2-6) have been proposed. All of these techniques have some drawbacks
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and none of them has been applied routinely in clinical practice.
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To develop an accurate clinical urodynamic method to diagnose BOO, we applied a
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non-invasive ultrasound (US) decorrelation based technique to quantify flow velocity and
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turbulence in silica gel urethra models (7, 8). This technique is based on comparing the scatter
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pattern in a group of images constructed from sequentially acquired ultrasound
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radiofrequency (RF) signals due to reflections from small scattering particles. If the particles
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move slowly the images will be similar, that is, they will be highly correlated. If the particles
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move fast, then the images will be less similar and the correlation will be less, that is, there
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will be a higher decorrelation. In urine various types of crystals such as calcium oxalate, uric
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acid and amorphous urates have been identified (9, 10). These crystalline structures can act as
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small ultrasound scattering particles. In a previous study (11) we showed that morning urine
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contains a sufficient concentration of these scattering materials to be suitable for US imaging
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of urinary flow using the decorrelation method. We subsequently tested and applied the
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velocity (12). In a phantom with increasing severity of obstruction we found higher
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decorrelation values than in the unobstructed urethra models at the same flow velocity. This
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was due to turbulent flow as a result of an obstruction (8). On this basis we hypothesized that
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in patients suffering from BOO we could find higher decorrelation values than in the healthy
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volunteers at the same flow velocity and it might be possible to develop a practical method for
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noninvasively diagnosing BOO in male patients with lower urinary tract symptoms (LUTS).
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In the present study, we applied the decorrelation method in patients with LUTS to diagnose
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BOO and compared the results with conventional PFS.
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Materials & Methods
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Population
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Following institutional research ethics board approval (MEC-2013-419), we recruited 60 male
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patients with LUTS, suggestive of BOO in the period January – October 2015. All patients
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gave their informed consent. Completing an International Prostate Symptom Score (IPSS)
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form to quantify their urological condition was part of routine practice.
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Experimental setup
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Each patient voided in a sitting position with an ultrasound transducer gently placed
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against the perineum using a specially designed chair with a mechanical transducer
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manipulator (Fig 1(A)). Each patient was asked before voiding to void without straining. To
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adequately visualize the urethra, the transducer was manually moved in angular and sidewise
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directions by the investigator using the vertical handle (Figure 1(B)). To acquire RF US data
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of the urinary stream a BK-Medical system (Pro Focus UltraView 2202) with a custom
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designed RF interface was used. The US data acquisition was synchronized with the flow rate
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signal. The voided volume was measured at each voiding using a measuring jug.
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Data acquisition From each patient we acquired four measurements. The 1st measurement was a free
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flow measurement, that is, a flow measurement without transurethral catheter, with US data
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acquisition. The following two were conventional invasive PFS done by the Andromeda
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urodynamic system (Medizinische Systeme GmbH, Potzdam Germany) without US data
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acquisition. Finally, the bladder of the patient was refilled with a saline solution to which we
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added approximately 4x105 microbubbles/litter (SonoVue, Braco International B.V.
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Amsterdam, the Netherlands) to enhance the US reflection by the scattering particles.
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catheter was then removed and again a free flow measurement with US data acquisition was
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recorded. We acquired 5 seconds of US data at different flow rates (maximum and sub-
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maximum) during a complete voiding cycle. Each US frame contained 10 sequential US RF
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data sets. Every RF data set consisted of 142 RF-signals acquired at a Pulse Repetition
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Frequency (PRF) of 0.5 kHz. Each RF-signal yielded a single image-line in an US B mode
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image.
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Correlation coefficients: To calculate the correlation between two sequential images in a US
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frame, two corresponding image lines were selected from two sequential images and the
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correlation coefficient was calculated (13). This process was repeated for all consecutive 142
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image lines and one correlation image was constructed from two sequential US images as
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shown in Figure 3(B) & 3(D). For each US frame, consisting of 10 US RF-data sets, 6
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correlation images were thus constructed. In each correlation image a Region of Interest (ROI
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= length 1.8 cm) was manually selected and the mean correlation value was calculated (see
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Figure 3). Next we calculated the average (ρ ) of these ρ values over the 6 correlation
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images of each US frame. The calculated average correlation values ρ were plotted as a
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function of the flow velocity. (a more detailed description of the correlation coefficients calculation can be found in Arif et al. (7)). Relationship between decorrelation and degree of obstruction
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To define a relationship between the decorrelation and the degree of obstruction we
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fitted a curve through the decorrelation and flow velocity data acquired in healthy volunteers
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using Equation 1 (see Appendix). Next we calculated the differences between the correlation
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values of equation 1 and the patients correlation values at the same flow velocity
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(experimental quantification parameter of BOO). We plotted these as a function of Bladder
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Outlet Obstruction Index (BOOI), which was used as the gold standard quantification
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parameter for the degree of BOO (14). In each patient the BOOI, was calculated by the
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Andromeda urodynamic system (Medizinische Systeme GmbH, Potzdam Germany). A linear
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relation was fitted to the data (see Appendix).
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From Equation 1, we subtracted the correlation difference calculated using equation 2 at
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BOOI values of 20 and 40, thus creating correlation-velocity boundary curves for these values
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in a correlation-velocity nomogram. We also calculated the Receiver Operating Characteristic
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(ROC) curve to test the diagnostic value of the method (see Figure 6). To this end, patients
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were stratified in two groups on the basis of invasive PFS. Patients with BOOI of 40 or less
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were labelled unobstructed ( i.e. equivocal or unobstructed according to the standard BOOI
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nomogram) and those with higher BOOI were labelled obstructed. The area under the curve
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(AUC) shows the percentage of the patients that are correctly diagnosed by the method. The
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specificity and sensitivity of the decorrelation method were also calculated.
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Results
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Population
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We included 60 patients. Five patients were not able to void during the complete
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examination. From these 5 patients, 3 patients had an indwelling catheter. Five patients were
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US data was not usable due to a wrong positioning of the transducer or due to movement of
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the patient during voiding. In the remaining 45 (75%) patients, at least one US urinary flow
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data was recorded. The voided volume, maximum free flow rate, age, IPSS and BOOI of
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these 45 patients are shown in Table 1. The pressure-flow nomogram of the patients is shown
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in Figure 4(B).
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In-vivo Results
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A typical urinary flow rate curve of a volunteer and a patient are shown in Figure
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2(A) & 2(C). The flow rate values corresponding to the 50 acquired US frames are shown in
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Figure 2(B) & 2(D). An example of an in vivo US B-mode image of the urethra of a healthy
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volunteer and an obstructed patient during voiding is shown in Figure 3(A) & 3(C). The
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correlation images constructed from the 1st and 5th US RF-data set are overlaid on the B-mode
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images (see Figure 3(B) & 3(D)). The ROI distal to the prostatic urethra is also visible. A plot
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of the calculated values as a function of flow velocity for volunteers and patients is
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shown in Figure 4(A). The diagram shows that the correlation coefficients of the obstructed
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patients were lower than those of the healthy volunteers at the same flow velocity, that is, the
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decorrelation was higher in these patients.
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Decorrelation-Degree of obstruction relationship In Figure 5 (A), we plotted the difference in of patients and the model fitted to
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the healthy volunteers data as a function of BOOI. The difference between the correlation
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values increased with the degree of obstruction. The R-square value of the fitted linear model
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was 0.55 with parameters = 0.0041 and = -0.074. In Figure 5(B), we constructed the
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nomogram to categorize the patients in different obstruction levels based on the US
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correlation data values. It illustrates that 86%, that is, 39 out of 45 patients could be classified
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correctly. In ROC analysis, an AUC value of 0.96 signified a diagnostic accuracy of 96% (See
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Figure 6). The specificity and sensitivity of the method were 95% and 88%. Discussion
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The standard procedure to diagnose BOO involves urethral catheterization which is
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uncomfortable to patients and may also cause infections of the urinary tract. Therefore a non-
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invasive urodynamic method to diagnose BOO is desirable. In this study we applied US
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decorrelation analysis on patients with LUTS to diagnose BOO and compared the results with
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standard PFS.
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In 45 out of 60 patients we successfully recorded the US urinary flow data. The
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principle finding of the study is that in patients with BOO the correlation values are decreased
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with respect to the healthy volunteers as shown in Figure 3 and Figure 4(A). The reason for
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this higher decorrelation could be that the narrowing in the urinary flow channel due to the
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urethral obstruction results in a disturbed (turbulent) urinary flow. The correlation difference
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plotted as a function of BOOI shows that the decorrelation is significantly correlated with
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BOOI. By measuring the decorrelation using US it might be possible to estimate BOOI in
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patients with voiding symptoms. Categorization of patients in different obstruction levels
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using BOOI is illustrated in Figure 5(B). In an ideal situation all the obstructed patients
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should have correlation values below the BOOI=40 curve, however the fitted relation to
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estimate BOOI from the decorrelation could be a source of error.
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In a previous study in healthy volunteers (12) US data during voiding were acquired in
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the standing position. In the present study patients urinary flow US data were acquired in the
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sitting position. In a meta-analysis by De Jong et al. (15) no difference in urinary flow rate of
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healthy men in sitting or standing position was found. Therefore the correlation data of
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healthy volunteers in standing position can be compared to the data of the patients acquired in
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the sitting position. We preferred to do the measurement in the sitting position for patients,
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often elderly, as it was easier to void sitting while also preventing motion artefacts. The study
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including the adjustment of the transducer and US data acquisition for each patient took 5
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minute maximum. In some other non-invasive techniques, such as the cuff method, a minimum voided
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bladder volume (≥ 150ml) has been reported (16). However, a thorough statistical analysis of
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the volume dependence of the reliability of the method was not possible as only two patients
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voided less than 100 ml. Considering our method we had no indication that a small voided
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volume made the method unreliable. In Table 1, for patient 29 the voided volume was 30ml
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and the US data was successfully acquired.
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To check the reproducibility of the method, we acquired US data in 5 patients at two
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different times. The average calculated correlation (ρ ) values for each patient are shown in
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table 2. The data shows that the correlation coefficient values acquired at different times are
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almost similar at similar flow velocity values, but it decreased with an increase in flow
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velocity. However, the US diagnostic status of the patient remained the same.
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Ozawa et al. (2010) used color Doppler US to measure urinary flow velocity in BOO
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patients and compared their results with those of a pressure flow study. They measured the
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urine flow velocity transperineally in the distal prostatic urethra just above the external
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sphincter and in the sphincteric urethra. However, urethral obstruction can create turbulence
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in the flow and lead to an aliasing effect in the color Doppler signals. This makes Doppler
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ultrasound less suitable for estimating the urine flow velocity. To solve this problem we
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measured the cross-sectional area from the images that were also used for the decorrelation
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analysis. From this the flow velocity was calculated at the same flow rate that was used to
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perform the decorrelation analysis.
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bladder can be refilled and the diagnostic process can be repeated. In addition, with a catheter
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present, information on the storage phase of the micturition cycle can be obtained. In the non-
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invasive decorrelation method, patients are not catheterized and repeating the study can only
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be done after natural refilling of the bladder which takes time. Additionally, the decorrelation
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method depends on particle concentration (11). A high fluid intake with subsequent dilution
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of urine could therefore affect the results. Future studies should address this aspect of the
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decorrelation method. However, these disadvantages are more than compensated by the non-
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invasive nature of the method.
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The results show that the decorrelation based analysis of US data could be used clinically to
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diagnose BOO. However, the method needs to be tested with more optimized and more easily
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controllable equipment. The urologist or technician needs to be trained to get good US data
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during voiding. Real time software which performs the decorrelation analysis and calculates a
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BOOI value based on the correlation-velocity nomogram could make the technique more
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readily and easily applicable.
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Conclusion
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Decorrelation based analysis of urinary flow US data showed that the decorrelation
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was higher in obstructed patients than in unobstructed patients and healthy volunteers at the
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same flow velocity. The relationship between BOOI and differences in correlation values of
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patients and the fitted curve of healthy volunteers showed that the degree of BOO can be non-
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invasively estimated using US decorrelation analysis and the measured correlation values can
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be used to diagnose BOO in male patients with high specificity (95%), sensitivity (88%) and
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a diagnostic accuracy of 96%.
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Appendix Relationship between decorrelation and degree of obstruction
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The function fitted curve to the decorrelation and flow velocity data acquired in healthy
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volunteers was:
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(1)
where a, b and c are parameters and k is volunteer number (1,2 …18) (12).
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The difference in correlation between healthy subjects and patients as a function of the
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Bladder Outlet Obstruction Index (BOOI) was defined as:
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1. Griffiths D, Hofner K, van Mastrigt R, Rollema HJ, Spangberg A, Gleason D. Standardization of terminology of lower urinary tract function: pressure-flow studies of voiding, urethral resistance, and urethral obstruction. International Continence Society Subcommittee on Standardization of Terminology of Pressure-Flow Studies. Neurourol Urodyn. 1997;16(1):1-18. 2. Pel JJ, van Mastrigt R. Non-invasive measurement of bladder pressure using an external catheter. Neurourol Urodyn. 1999;18(5):455-69; discussion 69-75. 3. Idzenga T, Pel JJM, Baldewsing RA, Mastrigt Rv. Perineal noise recording as a noninvasive diagnostic method of urinary bladder outlet obstruction: a study in polyvinyl alcohol and silicone model urethras. Neurourol Urodyn. 2005;24(4):381-8. 4. Griffiths CJ, Rix D, MacDonald AM, Drinnan MJ, Pickard RS, Ramsden PD. Noninvasive measurement of bladder pressure by controlled inflation of a penile cuff. J Urol. 2002 Mar;167(3):1344-7. 5. Manieri C, Carter SS, Romano G, Trucchi A, Valenti M, Tubaro A. The diagnosis of bladder outlet obstruction in men by ultrasound measurement of bladder wall thickness. J Urol. 1998 Mar;159(3):761-5. 6. Ozawa H, Igarashi T, Uematsu K, Watanabe T, Kumon H. The future of urodynamics: Non-invasive ultrasound videourodynamics. Int J Urol. 2010;17(3):241-9. 7. Arif M, Idzenga T, van Mastrigt R, de Korte CL. Estimation of Urinary Flow Velocity in Models of Obstructed and Unobstructed Urethras by Decorrelation of Ultrasound Radiofrequency Signals. Ultrasound Med Biol. 2014 Jan 9:938-46. 8. Arif M, Idzenga T, de Korte CL, van Mastrigt R. Development of a noninvasive method to diagnose bladder outlet obstruction based on decorrelation of sequential ultrasound images. Urology. 2015 Mar;85(3):648-52. 9. Verdesca S, Fogazzi GB, Garigali G, Messa P, Daudon M. Crystalluria: prevalence, different types of crystals and the role of infrared spectroscopy. Clin Chem Lab Med. 2011 Mar;49(3):515-20. 10. Elliot JS, Rabinowitz IN. Calcium-Oxalate Crystalluria - Crystal Size in Urine. J Urology. 1980;123(3):324-7. 11. Arif M, Idzenga T, de Korte CL, van Mastrigt R. Dependence of ultrasound decorrelation on urine scatter particle concentration for a non-invasive diagnosis of bladder outlet obstruction. Neurourol Urodyn. 2015 Nov;34(8):781-6. 12. Arif M, Idzenga T, van Mastrigt R, de Korte CL. Diagnosing Bladder Outlet Obstruction Using Non-invasive Decorrelation-Based Ultrasound Imaging: A Feasibility Study in Healthy Male Volunteers. Ultrasound in Medicine & Biology Vol. 41, No. 12, pp. 3163–3171, 2015. 13. Lupotti FA, van der Steen AF, Mastik F, de Korte CL. Decorrelation-based blood flow velocity estimation: effect of spread of flow velocity, linear flow velocity gradients, and parabolic flow. IEEE Trans Ultrason Ferroelectr Freq Control. 2002 Jun;49(6):705-14. 14. Abrams P. Bladder outlet obstruction index, bladder contractility index and bladder voiding efficiency: three simple indices to define bladder voiding function. BJU Int. 1999 Jul;84(1):14-5. 15. de Jong Y, Pinckaers JHFM, ten Brinck RM, Nijeholt AABLA, Dekkers OM. Urinating Standing versus Sitting: Position Is of Influence in Men with Prostate Enlargement. A Systematic Review and Meta-Analysis. Plos One. 2014 Jul 22;9(7). 16. McIntosh S, Pickard RS, Drinnan M, et al. Non invasive measurement of bladder pressure: minimum voided volume and test/retest reproducibility. Paper presented at: Annual Meeting of the International Continence Society; August 27–29, 2002; Heidelberg, Germany.
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Legends Figure 1: (A) Schematic drawing and (B) picture of the experimental setup. The US transducer position was controlled by a specially designed manual probe manipulator.
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Figure 2: A typical flow rate curve of a healthy volunteer (A & B) and an obstructed patient (C & D) as a function of time. Figure 3:
(A) Example of in vivo US B-mode image and (B) Correlation coefficient
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distribution overlaid on the US B-mode image of the urethra during voiding of a healthy volunteer. (C) Example of in vivo US B-mode image and (D) Correlation coefficient
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distribution overlaid on the US B-mode image of the urethra during voiding of an obstructed patient (BOOI = 75 ). The Region of Interest (ROI) and the measured urethra diameter are also shown. 1 represents to high correlation and 0 to low correlation.
Figure 4: (A) The calculated average correlation coefficients and fitted function of 18
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healthy volunteers and correlation values of 45 patients plotted as a function flow velocity. The patients were categorized as obstructed/unobstructed or equivocal based on a standard pressure-flow studies. (B) A pressure flow nomogram to classify the 45 patients as
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obstructed/unobstructed or equivocal based on pressure-flow studies.
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Figure 5: (A) Difference in correlation between healthy subjects and patients plotted as a function of BOOI. (B) Correlation-velocity nomogram to diagnose BOO in LUTS patients. The patients were categorized as obstructed/unobstructed or equivocal based on a standard pressure-flow studies.
Figure 6: Receiver Operating Characteristic curve (ROC) of the non-invasive decorrelation method with an area under the curve (AUC) of 0.96.
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Voided Urine Volume (ml) 760 150 425 470 155 250 325 295 280 290 472 300 160 180 156 250 255 170 265 490 220 200 290 170 220 200 260 250 30 240 710 300 160 360 240 340 390 200 325 150 100 200 175 300 230
BOOI
13 11 10 12 3 12 5 5 5 5 10 7 5 13 12 15 14 5 4 16 13 13 13 5 5 14 10 10 11 9 15 14 7 20 10 7 8 12 8 11 3 14 6 5 8
29 54 19 6 53 75 92 63 68 45 27 28 22 81 40 45 5 161 116 -21 72 5 33 54 99 69 42 18 -2 42 1 31 66 63 93 57 33 8 111 29 35 -16 34 104 50
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1 50 15 2 77 10 3 70 23 4 65 22 5 65 27 6 55 11 7 80 18 8 72 18 9 74 15 10 66 24 11 61 22 12 53 23 13 90 No 14 80 17 15 76 21 16 83 18 17 51 24 18 68 23 19 54 20 20 61 16 21 59 18 22 70 13 23 64 10 24 74 10 25 64 No 26 78 14 27 68 18 28 77 33 29 59 19 30 50 31 31 54 11 32 72 25 33 67 8 34 70 No 35 72 No 36 77 18 37 72 No 38 79 No 39 65 17 40 78 No 41 80 7 42 72 No 43 51 No 44 65 No 45 67 No No = IPSS of the patients were not recorded.
Maximum Flow rate (ml/s)
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flow velocity (cm/s) 13 5 30 12 20
Correlation values (ૉ) ܞ܉ 0.8781 0.9820 0.7976 0.9504 0.7914
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Decorrelation method
Pressureflow study
Obstructed Obstructed Unobstructed Unobstructed Obstructed
Obstructed Obstructed Equivocal Equivocal Obstructed
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Correlation values (ૉ) ܞ܉ 0.8881 0.9903 0.6875 0.9683 0.8617
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flow velocity (cm/s) 11 2 44 12 15
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ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
ACCEPTED MANUSCRIPT
ACCEPTED MANUSCRIPT BOO
= Bladder Outlet Obstruction
US
= Ultrasound
RF
= Radiofrequency
PFS
= pressure-flow studies
ROI = Region Of Interest
AC C
EP
TE D
M AN U
SC
BOOI = Bladder Outlet Obstruction Index
RI PT
LUTS = Lower Urinary Tract Symptoms