Imaging Manifestations and Evaluation of Postoperative Complications of Bone and Joint Infections under Deep Learning.

Wei Mao,Fengyuan Man,Xiantao Chen

doi:10.1155/2021/6112671

Abstract

To explore and evaluate the imaging manifestations of postoperative complications of bone and joint infections based on deep learning, a retrospective study was performed on 40 patients with bone and joint infections in the Department of Orthopedics of Orthopedics Hospital of Henan Province of Luoyang City. Sensitivity and Dice similarity coefficient (DSC) were used to evaluate the image results by convolutional neural network (CNN) algorithm. Imaging features of postoperative complications in 40 patients were analyzed. Then, three imaging methods were used to diagnose the features. Sensitivity and specificity were used to evaluate the diagnostic performance of three imaging methods for imaging features. Compared with professional doctors and biomarker algorithms, the sensitivity of CNN algorithm proposed was 90.6%, and DSC was 84.1%. Compared with traditional methods, the CNN algorithm has higher image resolution and wider and more accurate lesion area recognition and division. The three manifestations of soft tissue abscess, periosteum swelling, and bone damage were postoperative imaging features of bone and joint infections. In addition, compared with X-ray, CT examination and MRI examination were better for the examination of imaging characteristics. CT and MRI had higher sensitivity and specificity than X-ray. The experimental results show that CNN algorithm can effectively identify and divide pathological images and assist doctors to diagnose the images more efficiently in clinic.

Highlights

Bone and joint infection is a single bone and joint infectious disease, and bone and joint infection is osteoarthritis caused by pathogenic microorganisms such as bacteria or viruses invading bone tissue and bone joint cavity. e biological cause of bone and joint infections is the invasion of pathogenic bacteria
Since the clinical symptoms of complications lag behind the imaging manifestations, imaging examination is often used in treatment to improve the diagnostic accuracy of complications [11]. ere are a variety of commonly used imaging methods, including X-ray examination, computed tomography (CT), and magnetic resonance imaging (MRI)
Bone joint infection refers to the infection of bone tissue and bone joint structure by bacteria and other pathogenic microorganisms

Summary

Introduction

Bone and joint infection is a single bone and joint infectious disease, and bone and joint infection is osteoarthritis caused by pathogenic microorganisms such as bacteria or viruses invading bone tissue and bone joint cavity. e biological cause of bone and joint infections is the invasion of pathogenic bacteria. Suppurative bone and joint infections are classified into blood-borne and exogenous, and their pathogenic bacteria are mainly Staphylococcus aureus. Suppurative osteomyelitis usually occurs as complications of open fracture, internal fixation of fracture, diabetic foot, joint prosthesis replacement, and contaminated fracture [4]. It occurs in the tibia and femur, most of which are boils and carbuncles or purulent exudates from other parts of the body that reach bone tissue through the blood system, causing inflammatory symptoms of bone joints or bone tissue. Erefore, this study intended to conduct imaging examination on patients with common postoperative complications of bone and joint infections through retrospective analysis to summarize their imaging characteristics. Deep learning algorithm was used to evaluate their imaging, so as to provide reference for better assisting doctors and utilizing the advantages of image-assisted diagnosis

Methods

Results

Discussion

Method classification

Conclusion