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Bladder Biomechanics and Shape Characterization: Comparison Study of Healthy vs BPH using Uro-Dynamic MRI

Juan Pablo Gonzalez-Pereira^1,2, Shane Wells², Matthew Grimes³, Wade Bushman³, and Alejandro Roldan-Alzate^1,2,4
¹Mechanical Engineering, University of Wisconsin-Madison, Madison, WI, United States, ²Radiology, University of Wisconsin-Madison, Madison, WI, United States, ³Urology, University of Wisconsin-Madison, Madison, WI, United States, ⁴Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States

Synopsis

Keywords: Urogenital, Bladder, Uro-Dynamic MRI

Motivation: Current standards for assessing the lower urinary tract (LUT) provide limited anatomical information. Uro-Dynamic MRI proves to be a valuable non-invasive tool for LUT biomechanics analysis. Bladder shape has been studied in static imaging but not in dynamic imaging.

Goal(s): Build a comprehensive, non-invasive framework to study bladder biomechanics in healthy and diseased subjects.

Approach: Uro-Dynamic MRI was implemented and used in five healthy and five BPH subjects. Novel MRI-derived bladder shape metrics were developed and quantified in all subjects.

Results: We observe quantifiable differences on correlation coefficients of flowrates and calculated bladder shape metrics between healthy and patients with benign prostatic hyperplasia.

Impact: Uro-Dynamic MRI allows biomechanical and shape analysis of the lower urinary tract(LUT), allowing comparisons between healthy and diseased subjects. Higher correlation values with flowrates observed on healthy subjects. Coupled Bladder biomechanical and shape analysis allows potential characterization of LUT disease.

Introduction

Multichannel uro-dynamic studies (UDS) with or without fluoroscopic imaging and/or urethral pressure profilometry have been the gold standard for assessment of the lower urinary tract (LUT) by taking measurements of voiding pressures and flow but provide limited assessment of lower urinary tract anatomy¹. Assessment of bladder biomechanics using magnetic resonance imaging has been reported in the past^1–3 but lacks detailed analysis of bladder shape as it has only been analyzed volumetrically. Bladder shape analysis has been analyzed using ultrasound during filling⁴ and MRI statically⁵. Benign prostatic hyperplasia (BPH)⁶ has been studied non-invasively using ultrasound⁷ and non-invasively using MRI by looking at the prostate⁸. Links have been determined between static urinary metrics and BPH^9–11. The purpose of this study was to comprehensively and non-invasively characterize bladder biomechanics in patients with BPH/LUTS and healthy subjects by using a recently developed Uro-Dynamic MRI¹ method.

Methods

Image Acquisition
In this an IRB-approved, HIPAA compliant study. 5 healthy volunteers (37±9 years of age) and 5 subjects diagnosed with BPH (65±6 years of age) were recruited. A single weight-based dose (0.1 mmol/kg) of gadolinium-based contrast was prepared and 1/3 of the dose was hand injected 15 minutes prior to MRI. Subjects were later equipped with a condom catheter and instructed to void in the MRI scanner in a supine position where urine was collected in a 1L bag attached to the subject’s leg. Acquired images were collected in a 3T MRI scanner (Premier, GE Healthcare, Waukesha, WI) using a high-density flexible array coil (AIR Coil, GE Healthcare) protocol developed in the past¹ for most of the subjects. Healthy 5 was imaged using a new, contrast-less acquisition sequence that was developed based on a balance steady state free precession (bSSFP) sequence. This allows us to keep the same spatial resolution in the sagittal direction (1mmx1mmx2mm) while increasing our temporal resolution to obtain one complete bladder volume from an average of 4.3s to 1.65 seconds (TR=2.552, TE=0.944, Flip Angle=20°).
Bladder Segmentation
Images are imported into MIMICS (Materialise, Belgium) where we reconstruct one 3D rendering per time point within each void (17±4 time steps per subject) shown in Fig.1 and 2. Volumetric metrics like sphericity index, bladder neck angle (BNA) and external BNA (EBNA) were measured for all subjects throughout the void (Fig3)¹.
Bladder Shape Analysis
From the acquired images we determined metrics that could aid in the characterization of the bladder shape throughout the void shown in Fig3. These metrics are based on anatomical references like the pubic symphysis (PS) and the trigone.

Results

The results are summarized on Fig.4. Fig.5 contains one characteristic subject of each group (highlighted in yellow in of Fig.4B) was selected to display a complete analysis of the correlations between urine flow rate and the calculated metrics.

Discussion

Healthy volunteers exhibited a larger range of motion across all metrics, lower wall tension and stretch indices. Linear correlation coefficients (R²) between these metrics and urinary flow rate were found to be higher in the healthy volunteers in most of the cases. In Fig.4, highlighted in green, shows two BPH subjects without lower urinary tract symptoms (LUTS) that have high correlation values with flow, corresponding the behavior of healthy subjects. Because of this most of the maximum and minimum metrics are similar but in the case of LAN and CAS, SD values show large disparity in the metrics. Therefore, the table with the correlation coefficients was included to show information that might be hidden due to patient-to-patient variability in the Min/Max table. In Fig.4 the largest differences are highlighted in orange. In addition, measurements taken in the sagittal plane and its derivatives show higher correlation coefficients than metrics taken in the coronal plane

Conclusions

Uro-Dynamic MRI has proven to be able to capture bladder biomechanics non-invasively both in healthy controls and patients with BPH/LUTS. By adding bladder shape analysis, we have created a robust framework that could characterize bladder biomechanics and shape and quantify differences between healthy subjects and subjects with LUTS in a more comprehensive way. We are aware this framework is still contingent to limitations like the orientation of the subject during the study and the inability to take more than one void per scanning session. In addition, to increase the scope of this framework we are currently adding more subjects to both cohorts, performing a comparison between sequences, adding studies in women and adding different cohorts including overactive bladder (OAB) and neurogenic bladder.

Acknowledgements

We would like to acknowledge support from NIIDK (R01 DK126850-01A1), the Wisconsin Partnership Program (WPP; AAM3497) and GE Healthcare which provides research support to University of Wisconsin-Madison.

References

1. Gonzalez-Pereira JP, Johnson CJ, Wells S, Bushman W, Roldan-Alzate A. Technical feasibility of uro-dynamic MRI study of voiding biomechanics: a pilot study. Int Urol Nephrol. Published online 2023. doi:10.1007/s11255-023-03823-7

2. Anzia LE, Johnson CJ, Mao L, et al. Comprehensive non-invasive analysis of lower urinary tract anatomy using MRI. Abdominal Radiology. 2021;46(4). doi:10.1007/s00261-020-02808-9

3. Pewowaruk R, Rutkowski D, Hernando D, Kumapayi BB, Bushman W, Roldán-Alzate A. A pilot study of bladder voiding with real-time MRI and computational fluid dynamics. PLoS One. 2020;15(11 November). doi:10.1371/journal.pone.0238404

4. Gray T, Phillips L, Li W, et al. Evaluation of bladder shape using transabdominal ultrasound: Feasibility of a novel approach for the detection of involuntary detrusor contractions. Ultrasound. 2019;27(3):167-175. doi:10.1177/1742271X19834062

5. Ateşçi YZ, Aydoǧdu Ö, Karaköse A, Pekedis M, Karal Ö, Şentürk U. Does urinary bladder shape affect urinary flow rate in men with lower urinary tract symptoms? The Scientific World Journal. 2014;2014. doi:10.1155/2014/846856

6. Bushman W. Etiology, epidemiology, and natural history of benign prostatic hyperplasia. Urol Clin North Am. 2009;36(4).

7. Ku JH, Ko DW, Cho JY, Oh SJ. Correlation Between Prostatic Urethral Angle and Bladder Outlet Obstruction Index in Patients With Lower Urinary Tract Symptoms. Urology. 2010;75(6):1467-1471. doi:10.1016/j.urology.2009.08.049

8. Guneyli S, Ward E, Peng Y, et al. MRI evaluation of benign prostatic hyperplasia: Correlation with international prostate symptom score. Journal of Magnetic Resonance Imaging. 2017;45(3). doi:10.1002/jmri.25418

9. Cho KS, Kim JH, Kim DJ, Choi YD, Kim JH, Hong SJ. Relationship Between Prostatic Urethral Angle and Urinary Flow Rate: Its Implication in Benign Prostatic Hyperplasia Pathogenesis. Urology. 2008;71(5):858-862. doi:10.1016/j.urology.2008.01.019

10. Li Y, Chen Z, Zeng R, Huang J, Zhuo Y, Wang Y. Bladder Neck Angle Associated with Lower Urinary Tract Symptoms and Urinary Flow Rate in Patients with Benign Prostatic Hyperplasia. Urology. Published online 2021. doi:10.1016/j.urology.2021.09.005

11. Kang M, Kim M, Choo MS, et al. Association of high bladder neck elevation with urodynamic bladder outlet obstruction in patients with lower urinary tract symptoms and benign prostatic hyperplasia. Urology. 2014;84(6):1461-1466. doi:10.1016/j.urology.2014.08.037

Figures

Figure 1: (Left) Sagittal view of acquired images of subject Healthy 4 (centered in the bladder neck) using DISCO Flex Sequence as stated in previous studies¹. Spatial Resolution: 1mmx1mmx2mm, TR=2.664, TE=1.116, Flip Angle=7°. (Right) 3D renderings generated from segmentations performed on images on the left.

Figure 2: (Left)Sagittal view of acquired images of BPH 5 (centered in the bladder neck) with an indication of a large prostatic protrusion. (Right) 3D renderings generated from segmentations performed on images on the left.

Figure 3: A) Sagittal view displaying the acquired metrics in this plane: N (Distance from the top of the trigone to the PS in black), LA (longest axis in yellow), LAN (angle between N and LA in green), CAS (curvature angle in light blue) and DS (curvature distance sagittal in red). B) Coronal view displaying the acquired metrics in this plane centered in the PS: CTB (top-bottom distance in blue), CRL (right left distance in purple) and DC (curvature distance coronal in red). C) Sagittal view showing measurement of BNA and EBNA.

Figure 4: A) Table summarizing the maximum and minimum values ± standard deviation (SD) for all the bladder shape metrics with key metrics highlighted. B) Table summarizing linear correlation coefficients of every metric when compared with each subjects’ flow rate. Highlighted in yellow are the characteristic subjects chosen to display these metrics in Fig.5.

Figure 5: (Top) Graph displaying flow rates for Healthy 4 (orange) and BPH 1 (blue). The rest of the graphs show correlation studies with their corresponding correlation coefficients between urine flowrate and each of the calculated bladder shape metrics shown in Fig.4.

Proc. Intl. Soc. Mag. Reson. Med. 32 (2024)

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DOI: https://doi.org/10.58530/2024/2902