Bladder wall micromotion measured by non-invasive ultrasound: initial results in women with and without overactive bladder

Abstract

Objective: Rhythmic contractions of the bladder wall during filling result from the synchronization of bladder wall micromotion and are often observed in the urodynamic tracings of individuals with urinary overactive bladder (OAB). This study's objective was to develop a novel, non-invasive method to measure bladder wall micromotion and to conduct an initial study to test the hypothesis that elevated micromotion is associated with OAB.

Methods: This prospective study enrolled women with OAB and asymptomatic volunteers as measured by the ICIQ-OAB survey. After filling the bladder to 40% cystometric capacity, 85 second cine-loops were obtained using a GE Voluson E8 ultrasound system with an 8 MHz curved, abdominal probe. A custom correlation-based texture tracking MATLAB algorithm was used to measure changes in the bladder wall thickness over time and correlate with changes in vesical pressure. Significant bladder wall micromotion was defined as changes in wall thickness with amplitudes higher than 0.1 mm in the frequency range of 1.75-6 cycles/minute as calculated from Fast Fourier Transform (FFT) analysis. The micromotion algorithm was tested on 30 women including 17 with OAB and 13 asymptomatic volunteers.

Results: Micromotion was identified in 41% of subjects with OAB and 0% of asymptomatic volunteers, indicating a significant association of micromotion with OAB (Fisher's exact test, P=0.010). Micromotion was also found to have a significant association with a clinical diagnosis of detrusor overactivity (Fisher's exact test, P=0.031). Frequencies with elevated micromotion correlated with frequencies of vesical pressure fluctuations.

Conclusions: The feasibility of a non-invasive method to measure bladder wall micromotion was demonstrated using transabdominal anatomical motion mode (M-mode) ultrasound. Presence of micromotion was significantly associated with OAB and with urodynamic-identified rhythm.

Keywords: Ultrasonography; detrusor overactivity; diagnostic imaging; fast Fourier transform analysis; image analysis; lower urinary tract symptoms; non-invasive; overactive bladder; texture tracking; urodynamics.

Figure 1

(A) The initial frame of an anatomical M-mode ultrasound cine-loop showing a 2D image of the bladder with red (perpendicular) and green (parallel) 1D lines tracked over time. Labels indicate the outer and luminal anterior bladder walls. (B) Tracking of the 1D red line over time during acquisition of 10.8 s of the 85 s cine loop. (C) Tracking of the 1D green line over time. (D) Zoomed view of the anterior bladder wall from (B) showing the locations of tracked regions of interest (ROI) with center points highlighted with asterisks on the outer (ROI1) and luminal (ROI2) edges of the bladder wall.

Figure 2

Fast Fourier transform (FFT) analysis shown from a participant with micromotion. (A) The wall thickness as measured by the ultrasound algorithm is shown in black. Zoomed in views of the ultrasound cine loop show the locations of the tracked regions of interest in time ranges with high wall thickness and low wall thickness. The top five peaks from the FFT analysis were transformed back into the time domain to create the waveform model (magenta) which was optimally time-shifted and overlaid on the smoothed data (black). (B) The intravesical pressure (P_ves) as measured by urodynamics is shown in black and the model constructed by the FFT is overlaid in magenta. (C) The wall thickness data in the frequency domain calculated by the FFT and (D) P_ves data in the frequency domain calculated by the FFT with zoomed insets of the frequency range of interest for micromotion.

Figure 3

Fast Fourier transform (FFT) analysis shown from a participant without significant micromotion. (A) The wall thickness as measured by the ultrasound algorithm is shown in black. Zoomed in views of the ultrasound cine loop show the locations of the tracked regions of interest in time ranges with high wall thickness and low wall thickness. The top five peaks from the FFT analysis were transformed back into the time domain to create the waveform model (magenta) which was optimally time-shifted and overlaid on the smoothed data (black). (B) The intravesical pressure (P_ves) as measured by urodynamics is shown in black and the model constructed by the FFT is overlaid in magenta. (C) The wall thickness data in the frequency domain calculated by the FFT and (D) P_ves data in the frequency domain calculated by the FFT with zoomed insets of the frequency range of interest for micromotion.

Figure 4

Numbers of overactive bladder (OAB) and asymptomatic participants with and without micromotion. The asterisk indicates that micromotion was significantly associated with OAB (P=0.010).