Automated quantification of low amplitude rhythmic contractions (LARC) during real-world urodynamics identifies a potential detrusor overactivity subgroup

作者：Cullingsworth Zachary E; Kelly Brooks B; Deebel Nicholas A; Colhoun Andrew F; Nagle Anna S; Klausner Adam P; Speich John E^*

来源：PLos One, 2018, 13(8): e0201594.

DOI：10.1371/journal.pone.0201594

Objectives
Detrusor overactivity (DO) is characterized by non-voiding detrusor smooth muscle contrac-tions during the bladder filling phase and often contributes to overactive bladder. In some patients DO is observed as isolated or sporadic contractions, while in others DO is mani-fested as low amplitude rhythmic contractions (LARC). The aim of this study was to develop an objective method to quantify LARC frequencies and amplitudes in urodynamic studies (UDS) and identify a subgroup DO of patients with LARC.
Methods
An automated Fast Fourier Transform (FFT) algorithm was developed to analyze a 205-second region of interest of retrospectively collected "real-world" UDS ending 30 seconds before voiding. The algorithm was designed to identify the three largest rhythmic amplitude peaks in vesical pressure (P-ves) in the 1.75-6 cycle/minute frequency range. These peak eves amplitudes were analyzed to determine whether they were 1) significant (above base-line P-ves activity) and 2) independent (distinct from any in abdominal pressure (P-abd) rhythm).
Results
95 UDS met criteria for inclusion and were analyzed with the FFT algorithm. During a blinded visual analysis, a neurourologist/urodynamicist identified 52/95 (55%) patients as having DO. The FFT algorithm identified significant and independent (S&I) LARC in 14/52 (27%) patients with DO and 0/43 patients (0%) without DO, resulting in 100% specificity and a significant association (Fischer's exact test, p<0.0001). The average slowest S&I LARC frequency in this DO subgroup was 3.20 +/- 0.34 cycles/min with an amplitude of 8.40 +/- 1.30 cm-H2O. This algorithm can analyze individual UDS in under 5 seconds, allowing real-time interpretation.
Conclusions
An FFT algorithm can be applied to "real-world" UDS to automatically characterize the frequency and amplitude of underlying LARC. This algorithm identified a potential subgroup of DO patients with LARC.

• 出版日期2018-8-15