The use of endoscopic ultrasonography in the detection and differentiation of pathology in the wall of the upper gastrointestinal tract

Practical approach to linear endoscopic ultrasound examination of the gallbladder

The gallbladder (GB) is a susceptible organ, prone to various pathologies that can be identified using different imaging techniques. Transabdominal ultrasound (TUS) is typically the initial diagnostic method due to its numerous well-established advantages. However, in cases of uncertainty or when a definitive diagnosis cannot be established, computed tomography (CT) or magnetic resonance imaging may be employed to provide more detailed information. Nevertheless, CT scans may sometimes offer inadequate spatial resolution, which can limit the differentiation of GB lesions, particularly when smaller yet clinically relevant abnormalities are involved. Conversely, endoscopic ultrasound (EUS) provides higher frequency compared to TUS, superior spatial resolution, and the option for contrast-enhanced harmonic imaging, enabling a more comprehensive examination. Thus, EUS can serve as a supplementary tool when conventional imaging methods are insufficient. This review will describe the standard EUS examination of the GB, focusing on its endosonographic characteristics in various GB pathologies.

Deep Learning-Based Ultrasound Combined with Gastroscope for the Diagnosis and Nursing of Upper Gastrointestinal Submucous Lesions

The study focused on the diagnostic value of deep learning-based ultrasound combined with gastroscope examination for upper gastrointestinal submucous lesions and nursing. A total of 104 patients with upper gastrointestinal submucous lesions diagnosed in hospital were selected as the research subjects. In this study, the feed forward denoising convulsive neural network (DnCNN) was improved, and the n-DnCNN model was designed and applied to ultrasonic image processing. The peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) of Gaussian filtering, NL-means, and DnCNN were then compared with n-DnCNN. Subsequently, the distribution and types of submucosal lesions in different parts of the upper digestive tract were analyzed by ultrasound combined with gastroscope and gastroscope examination alone, and the diagnostic performance of this method was evaluated. The results showed that the average PSNR and SSIM of the n-DnCNN model were 33.01 dB and 0.87, respectively, which were significantly higher than GF, NL-means, and DnCNN algorithms, and the difference was statistically significant ( $P<0.05$ ). Of the 116 lesions detected, 49 were located in the esophagus (42.24%), 52 in the stomach (44.83%), and 15 in the duodenum (12.93%). Of the 49 esophageal submucosal lesions, 6.12% were located in the upper esophagus, 55.1% in the middle esophagus, and 38.79% in the lower esophagus, and the difference was statistically significant ( $P<0.05$ ). Of the gastric submucosal lesions, the lesions in the gastric cardia were significantly less than in other parts, and the difference was statistically significant ( $P<0.05$ ). The accuracy of ultrasound combined with gastroscope in the diagnosis of upper gastrointestinal submucous episodes was 82.32%, higher than that of gastroscope examination, and the difference was statistically significant ( $P<0.05$ ). In conclusion, the n-DnCNN model has a good noise reduction effect, and the obtained image is of high quality. Ultrasound combined with gastroscope examination can effectively improve the accuracy of diagnosis of upper gastrointestinal submucous lesions.