Urodynamics (UDS) is a standard urologic procedure for the evaluation of lower urinary tract disorders. The clinical utility of UDS, however, is limited due to subjective interpretation. Objective quantification of bladder characteristics such as pressure dynamics remains in its infancy. Numerous studies have demonstrated the application of Fast Fourier Transform (FFT)-based algorithms to quantify bladder pressure signals as a measure of spectral density, in both preclinical and clinical models [1,2]. These algorithms have successfully identificated autonomous non-voiding contractions (NVCs) which are potentially implicated in detrusor overactivity (DO) pathogenesis [3]. In this study, we demonstrate a novel FFT-based algorithm for quantifying fill-related changes in bladder spectral density in UDS datasets to differentiate between DO and Stress Urinary Incontinence patients without DO (NDO) groups. Additionally, we compared the diagnostic potential of spectral measurements to identify DO patients. This method and related technology development can be used for future investigation of pathophysiologic differences and disease severity across lower urinary tract disorders.

Retrospective UDS data and related patient records from 184 patients over one year period were identified. Inclusion required a clear SUI or DO diagnosis (but not mixed incontinence) and at least 400 seconds of pre-void UDS pressure data. 28 UDS datasets were finally included in our study of 18 DO and 10 NDO (SUI) patients. DO or SUI determination was based on urologist postprocedural diagnosis. UDS data were exported from a Laborie Aquarius XTTM multichannel UDS system (Laborie Medical Technologies, Toronto, Canada) that captured data at a rate of 10 samples per second. UDS data was transferred into MATLAB (MathWorks, Natwick, MA) and smoothed using a 10-point moving average function. We removed suspected coughs and movement artifacts by sensing these brief high-amplitude peaks, removing them and interpolating missing data. Pre-void vesical and abdominal pressure tracings (Pves & Pabd) were then equally divided into two segments (Early Fill and Late Fill) and FFT was applied to both signals. FFT abdominal spectra (FFTabd) were subtracted from FFT vesical spectra (FFTves) wherever FFTves > FFTabd to isolate bladder-specific signals. The Spectral Power (SP) and Weighted Average Frequency (WAF) of the spectral distribution were calculated for Early and Late Fill segments within the frequency range of 1 – 6 cycles per minute (cycles min-1). A multivariate logistic regression model was generated using SP and WAF values to predict either a DO or NDO diagnosis. Receiver Operator Characteristic (ROC) curves were produced using the model for Early and Late Fill segments. Student’s T-test was used for statistical analysis and statistical significance was determined as P<0.05.

The DO patient group contained 7 females and 11 males (mean age = 47y) with 13 patients reporting neurogenic DO. The NDO group contained 7 Females and 3 Men (mean age = 59y) with 3 patients reporting a neurologic indication for UDS. Bladder filling was associated with an increase in mean SP values across both groups, but we did not test the significance of this reported filling-related increase. The average SP of DO patients was significantly larger than that of NDO patients for Early Fill (13.02±3.90 vs 1.09±0.19 relative units (r.u.), mean ± SEM, P<0.05) and Late Fill (16.82±2.60 vs 8.00±3.77 r.u., P<0.05) (Fig 1 A&C). Additionally, the average WAF in DO patients was significantly less than in NDO patients for both Early Fill (2.56±0.17 vs 3.28±0.23 cycles min-1, P<0.05) and Late Fill (2.63±0.17 vs 3.20±0.24 cycles min-1, P<0.05) (Fig 1 B&D). ROC curves were created from the multivariate logistic regression with SP and WAF values to predict DO diagnosis (Fig 2). The area under the ROC curve (AUC) for Early Fill data was larger than that of Late Fill data (0.9 vs 0.8). The AUC for an ROC based upon combined Early and Late Fill, SP and WAF was 0.92 (data not shown).

Using data captured during UDS, bladder pressure spectra (range 1-6 cycles min-1) differ significantly for DO and NDO patients across filling segments. Spectral parameters, SP and WAF, can be used to differentiate and potentially diagnose patients with DO. The ROC curves and corresponding AUCs demonstrated the utility of these parameters as diagnostic markers. Furthermore, the greater AUC value of Early Fill ROC, compared to the AUC of the Late Fill ROC, suggests that the initial portion of UDS data may possess greater potential to diagnose DO. However, considering our small sample size, our model requires additional testing with larger datasets. While our measurements include the frequency range of NVCs, spectral density changes, which we quantified here, cannot be attributed to them yet. Further work is also needed to understand the relationship between SP and WAF and these NVCs and high amplitude detrusor contractions. Taken together, bladder pressure spectra parameters may offer novel insights regarding functional bladder changes related to bladder overactivity and underactivity.

Our study demonstrates that UDS derived spectral parameters, SP and WAF can quantify, distinguish, and identify DO patients. These parameters may be leveraged to improve clinical evaluation of bladder pathophysiology and patient outcomes. Future studies will use retrospective and prospective UDS data to rigorously assess the diagnostic utility of our method and its ability to quantify DO severity.

Ravishankar B, Elliott SP, Nakib NA, Timm GW, Nelson DE. Retrospective clinical study of spectral power and frequency in urodynamics pressure data: Workflow and preliminary tests of fill-dependence. Neurourol Urodyn. 2020. https://www.ics.org/2020/abstract/583.
Cullingsworth ZE, Kelly BB, Deebel NA, Colhoun AF, Nagle AS, Klausner AP, et al. Automated quantification of low amplitude rhythmic contractions (LARC) during realworld urodynamics identifies a potential detrusor overactivity subgroup. PLoS One. 2018;13.
Drake MJ, Kanai A, Bijos DA, Ikeda Y, Zabbarova I, Vahabi B, et al. The potential role of unregulated autonomous bladder micromotions in urinary storage and voiding dysfunction; overactive bladder and detrusor underactivity. BJU International. 2017;119:22–9.