RESUMEN
Purse-string suture with nylon cords and metal clips under the endoscope is a novel therapeutic technique which is minimally invasive and it is particularly indicated for the closure and repair of gastrointestinal fistula or perforations such as duodenal fistulae. Duodenal fistulae are often caused by medical manipulation, disease progression or trauma. Once this occurs, it leads to a series of pathophysiologic changes and a variety of complications. In most cases, these complications will exacerbate the damage to the organism, and the complications are difficult to treat and can lead to infections, nutrient loss, multi-organ dysfunction and many other adverse effects. In this case report, the use of endoscopic nylon cords combined with purse-string suture and metal clips in the treatment of duodenal fistula is presented and discussed. The patient was treated with endoscopic purse-string suture and the duodenal fistula was significantly improved. The results indicate that endoscopic purse-string suture is an effective strategy for the treatment of duodenal fistulae.
RESUMEN
BACKGROUND: Deep learning provides an efficient automatic image recognition method for small bowel (SB) capsule endoscopy (CE) that can assist physicians in diagnosis. However, the existing deep learning models present some unresolved challenges. AIM: To propose a novel and effective classification and detection model to automatically identify various SB lesions and their bleeding risks, and label the lesions accurately so as to enhance the diagnostic efficiency of physicians and the ability to identify high-risk bleeding groups. METHODS: The proposed model represents a two-stage method that combined image classification with object detection. First, we utilized the improved ResNet-50 classification model to classify endoscopic images into SB lesion images, normal SB mucosa images, and invalid images. Then, the improved YOLO-V5 detection model was utilized to detect the type of lesion and its risk of bleeding, and the location of the lesion was marked. We constructed training and testing sets and compared model-assisted reading with physician reading. RESULTS: The accuracy of the model constructed in this study reached 98.96%, which was higher than the accuracy of other systems using only a single module. The sensitivity, specificity, and accuracy of the model-assisted reading detection of all images were 99.17%, 99.92%, and 99.86%, which were significantly higher than those of the endoscopists' diagnoses. The image processing time of the model was 48 ms/image, and the image processing time of the physicians was 0.40 ± 0.24 s/image (P < 0.001). CONCLUSION: The deep learning model of image classification combined with object detection exhibits a satisfactory diagnostic effect on a variety of SB lesions and their bleeding risks in CE images, which enhances the diagnostic efficiency of physicians and improves the ability of physicians to identify high-risk bleeding groups.
Asunto(s)
Aprendizaje Profundo , Humanos , Intestino Delgado/diagnóstico por imagen , Intestino Delgado/patologíaRESUMEN
Albumin is derived from human or animal blood, and its ability to bind to a large number of endogenous or exogenous biomolecules makes it an ideal drug carrier. As a result, albumin-based drug delivery systems are increasingly being studied. With these in mind, detailed studies of the transport mechanism of albumin-based drug carriers are particularly important. As albumin receptors, glycoprotein 60 (GP60) and secreted protein acidic and rich in cysteine (SPARC) play a crucial role in the delivery of albumin-based drug carriers. GP60 is expressed on vascular endothelial cells and enables albumin to cross the vascular endothelial cell layer, and SPARC is overexpressed in many types of tumor cells, while it is minimally expressed in normal tissue cells. Thus, this review supplements existing articles by detailing the research history and specific biological functions of GP60 or SPARC and research advances in the delivery of antitumor drugs using albumin as a carrier. Meanwhile, the deficiencies and future perspectives in the study of the interaction of albumin with GP60 and SPARC are also pointed out.