Small-Bowel Capsule Endoscopy—Optimizing Capsule Endoscopy in Clinical Practice

Abstract

The small bowel is the longest organ within the gastrointestinal tract. The emergence of small bowel capsule endoscopy (SBCE) over the last 20 years has revolutionized the investigation and diagnosis of small bowel pathology. Its utility as a non-invasive and well-tolerated procedure, which can be performed in an outpatient setting, has made it a valuable diagnostic tool. The indications for SBCE include obscure gastrointestinal bleeding, small bowel Crohn’s disease, and, less frequently for screening in polyposis syndromes, celiac disease, or other small bowel pathology. Currently, there are several small bowel capsules on the market from different manufacturers; however, they share many technological features. The European Society of Gastrointestinal Endoscopy (ESGE) only recently developed a set of key quality indicators to guide quality standards in this area. Many of the technical aspects of capsule endoscopy still feature a degree of uncertainty in terms of optimal performance. Incomplete studies due to slow transit through the bowel, poor imaging secondary to poor preparation, and the risk of capsule retention remain frustrations in its clinical utility. Capsule review is a time-consuming process; however, artificial intelligence and machine learning offer opportunities to improve this. This narrative review examines our current standing in a number of these aspects and the potential to further the application of SBCE in order to maximize its diagnostic utility.

Magnetic Micro and Nano Sensors for Continuous Health Monitoring

“…The typical parameters of endoscopic capsules are as follows: an image registration speed of 1-30 frames/s using a CMOS sensor and VGA or HD resolutions, a camera focal length from 30 mm up to 100 mm, a power consumption of about 1-20 mW, a standard supply voltage of 3 V, a carrier frequency > 100 MHz and a data transfer rate of approx. 10 Mb/s [80][81][82][83][84]. It is worth mentioning that recently developed artificial intelligence (AI) methods play a key role in real-life data analysis and interpretation [85][86][87].…”

Videocapsular endoscopy in the diagnosis of gastrointestinal diseases

“…По мере совершенствования технологии это позволяет ускорить время считывания за счет исключения обычных изображений, удаления почти идентичных изображений и, в будущем, распознавания и идентификации патологии. Использование машинного обучения для выявления множественной патологии и локализации также находится в стадии изучения, что существенным образом совершенствуют технологию [45].…”