Particle Swarm Algorithm-Based Analysis of Pelvic Dynamic MRI Images in Female Stress Urinary Incontinence.

Dongfang Su,Qing Lin,Yufang Wen,Yuvaraja Teekaraman

doi:10.1155/2021/8233511

Abstract

This work aimed to study the application of pelvic floor dynamic images of magnetic resonance imaging (MRI) based on the particle swarm optimization (PSO) algorithm in female stress urinary incontinence (SUI). 20 SUI female patients were selected as experimental group, and another 20 healthy females were taken as controls. PSO algorithm, K-nearest neighbor (KNN) algorithm, and back propagation neural network (BPNN) algorithm were adopted to construct the evaluation models for comparative analysis, which were then applied to 40 cases of female pelvic floor dynamic MRI images. It was found that the model proposed had relatively high prediction accuracy in both the training set (87.67%) and the test set (88.46%). In contrast to the control group, there were considerable differences in abnormal urethral displacement, urethral length changes, bladder prolapse, and uterine prolapse in experimental patients (P < 0.05). After surgery, the change of urethral inclination angle was evidently reduced (P < 0.05). To sum up, MRI images can be adopted to assess the occurrence of female SUI with abnormal urethral displacement, shortening of urethra length, bladder prolapse, and uterine prolapse. After surgery, the abnormal urethral movement was slightly improved, but there was no obvious impact on bladder prolapse and uterine prolapse.

Highlights

stress urinary incontinence (SUI) refers to the involuntary leakage of urine from the external urethra when the abdominal pressure increases after sneezing or coughing [1]
E model proposed had relatively high prediction accuracy in both the training set (87.67%) and the test set (88.46%), indicating that the particle swarm optimization (PSO) algorithm can accurately improve the accuracy of training samples and test samples
magnetic resonance imaging (MRI) was adopted to observe in sagittal position, and it was found that the pubic urethral ligament was divided into proximal, middle, and distal ends. e support structure of the urethra of SUI patients would undergo significant changes. e typical manifestation was ligament laxity and abnormalities in multiple groups of ligaments

Summary

Introduction

SUI refers to the involuntary leakage of urine from the external urethra when the abdominal pressure increases after sneezing or coughing [1]. From a clinical point of view, the pelvic floor covers a wide range, including all muscle fascia layers from the pelvic peritoneum to the perineum skin. There are peritoneum, pelvic fascia, pelvic diaphragm, urogenital septum, external anal sphincter, and superficial urogenital muscles [3]. In the early stage of the search, to improve the global search capability of the particle swarm and enable the particle swarm to find the optimal solution range area as quickly as possible, the inertia weight is set to a relatively large value. In the later stage of the search, to control the speed of the particle swarm, the inertia weight value is reduced, so that the particle swarm can be accurately searched locally [8]

Methods

Results

Discussion

Conclusion