Paper Info
Title
Application of Endoscopic Ultrasound Image Analysis in the Treatment of Digestive Tract Diseases and Nursing
Abstract
Objective: To study the diagnostic accuracy of microprobe endoscopic ultrasonography (mEUS) in the diagnosis of bulge of digestive tract, and to summarize and explore the characteristics of ultrasound images of gastrointestinal bulge in mEUS diagnosis, to comprehensively evaluate microprobe ultrasound. The ability of endoscope to diagnose gastrointestinal bulging lesions provides a certain clinical basis for later nursing. Methods: A retro-spective analysis of 302 cases of gastrointestinal bulging cases underwent microprobe ultrasound endoscopy from November 2011 to December 2015. The diagnosis of all cases was confirmed by endoscopic pathology, surgical pathology or follow-up. Microprobes were compared. The diagnostic accuracy of the results of ultrasound endoscopy and traditional endoscopy. Results: A total of 302 patients underwent microprobe ultra-sound endoscopy, including 274 upper gastrointestinal tract, 28 colorectal, 97 esophagi in upper gastrointestinal tract, 152 in stomach and 25 in duodenum. The coincidence rate of mEUS diagnosis of esophageal bulge lesions was 97.93% (95/97), and the coincidence rate of gastroscopy diagnosis was 68.04 (66/97). The coincidence rate of mEUS diagnosis in gastric elevated lesions was 94.07% (143/152), and the coincidence rate of gastroscopy diagnosis was 50.65% (77/152). Conclusion: Microprobe endoscopic ultrasound can clearly show the structure of each layer of the digestive tract wall, reflecting the origin of the lesion and the depth of infiltration. Therefore, it can make accurate diagnosis of most gastrointestinal bulging lesions.
Year
DOI
Venue
2020
10.1166/jmihi.2020.3159
JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS
Keywords
DocType
Volume
Microprobe Endoscopic Ultrasonography,Digestive Tract Disease,Nursing
Journal
10
Issue
ISSN
Citations 
9
2156-7018
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Yameng Qi100.34
Jinhua Ding200.34
Li Li37624.03
Meimei Ai400.34
Ye Zhang593.06
Xiufen Chen600.34
Kathe Rin700.34