Background And Aims: Following ileocolonic resection for Crohn's disease (CD), early endoscopic recurrence predicts recurrence of symptoms. The aim of the study was to compare ileocolonoscopy and wireless capsule endoscopy (WCE) for the detection of postoperative recurrence in CD.
Methods: WCE and ileocolonoscopy were performed within six months following surgery in 32 prospectively enrolled patients. Two independent observers interpreted the results of WCE. Recurrence in the neoterminal ileum was defined by a Rutgeerts score>or=1. When observers at WCE did not concur, WCE results were considered as either true negative or true positive and sensitivity and specificity were calculated according to both assumptions.
Results: Recurrence occurred in 21 patients (68%) and was detected by ileocolonoscopy in 19 patients. Sensitivity was 90% and specificity 100%. Sensitivity of WCE was 62% and 76% and specificity was 100% and 90%, respectively, depending on assumptions. There was a correlation between the severity of the lesions measured by both methods (p<0.05). Lesions located outside the scope of conventional endoscopy were detected by WCE in two thirds of patients with excellent interobserver agreement (kappa>0.9) for all lesions with the exception of ulceration (kappa=0.7).
Conclusions: The sensitivity of WCE in detecting recurrence in the neoterminal ileum was inferior to that of ileocolonoscopy. In contrast, WCE detected lesions outside the scope of ileocolonoscopy in more than two thirds of patients. Additional follow up studies are needed to assess the clinical relevance of such lesions. At the present time, it seems that WCE cannot systematically replace ileocolonoscopy in the regular management of patients after surgery.
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http://dx.doi.org/10.1136/gut.2005.081851 | DOI Listing |
Sensors (Basel)
January 2025
Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, VIC 3800, Australia.
Conventional endoscopy is limited in its ability to examine the small bowel and perform long-term monitoring due to the risk of infection and tissue perforation. Wireless Capsule Endoscopy (WCE) is a painless and non-invasive method of examining the body's internal organs using a small camera that is swallowed like a pill. The existing active locomotion technologies do not have a practical localization system to control the capsule's movement within the body.
View Article and Find Full Text PDFWorld J Gastroenterol
December 2024
School of Computer Science Technology, Changchun University, Changchun 130022, Jilin Province, China.
Background: Wireless capsule endoscopy (WCE) has become an important noninvasive and portable tool for diagnosing digestive tract diseases and has been propelled by advancements in medical imaging technology. However, the complexity of the digestive tract structure, and the diversity of lesion types, results in different sites and types of lesions distinctly appearing in the images, posing a challenge for the accurate identification of digestive tract diseases.
Aim: To propose a deep learning-based lesion detection model to automatically identify and accurately label digestive tract lesions, thereby improving the diagnostic efficiency of doctors, and creating significant clinical application value.
Curr Med Res Opin
December 2024
Atherosclerosis and Vascular Biology Laboratory (Aterolab), Division of Cardiology, State University of Campinas (Unicamp), Sao Paulo, Brazil.
Background: White coat effect (WCE) is a phenomenon linked to increased cardiovascular risk, where office blood pressure readings exceed home or ambulatory measurements. Excess weight and elevated blood pressure or glucose are associated with WCE in type 2 diabetes (T2D). This study compared dapagliflozin and glibenclamide on WCE in T2D patients under equivalent blood pressure and glucose control.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Mathematics, Physics and Computing, University of Southern Queensland, Springfield, QLD 4300, Australia.
This work aims to develop a novel convolutional neural network (CNN) named ResNet50* to detect various gastrointestinal diseases using a new ResNet50*-based deep feature engineering model with endoscopy images. The novelty of this work is the development of ResNet50*, a new variant of the ResNet model, featuring convolution-based residual blocks and a pooling-based attention mechanism similar to PoolFormer. Using ResNet50*, a gastrointestinal image dataset was trained, and an explainable deep feature engineering (DFE) model was developed.
View Article and Find Full Text PDFHeliyon
December 2024
Department of Weed Science (360b), Institute of Phytomedicine, University of Hohenheim, 70599, Stuttgart-Hohenheim, Germany.
Ridge tillage (RT) is a conservation practice that provides several benefits such as enhanced root growth and reduced soil erosion. The objectives of this study were to develop an autosteered living mulch seeder and hoeing prototype for RT systems using RTK-GNSS (real-time kinematic global navigation satellite systems) created ridges as a guide. It was also aimed to compare weed control efficacy and crop response of ridge-hoeing compared to conventional hoeing in flat tillage (FT).
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