How to read small bowel capsule endoscopy: a practical guide for everyday use

Abstract

Small bowel (SB) capsule endoscopy (SBCE) is often perceived by both patients and physicians as a "lightweight," noninvasive, comfortable procedure that is easily performed with little more than swallowing a pill and a glass of water. However, "easy to carry out" does not translate to ease of reading or interpretation. A SB capsule acquires thousands of images and generates a long video; however, clinically relevant findings are often seen in only a few frames. There is no way to direct or focus the camera, the capsule's lens cannot be cleaned or luminal debris removed, and perhaps most importantly, the capsule cannot take tissue samples. Therefore, the rate of missed lesions in the SB has been quoted as high as 10 % [1]. Despite various SB imaging modalities offering similar diagnostic yield (DY) and miss rates, SBCE is one of the few endoscopic procedures open to immense scrutiny, as the data recorded are readily accessible for further on-demand review. This may expose clinicians to additional litigation but conversely, also provides a unique learning platform for new generations of SBCE readers. This is certainly fertile ground for virtual artificial neural network (ANN) training systems and even artificial intelligence (AI) diagnosis [2]. Currently, several different SBCE platforms exist. They differ in technical features and specifications such as size and weight, number and position of cameras, frame rate acquisition, and battery duration, as well as in several functions of proprietary reading software. In this editorial, we aim to provide general principles for SBCE reading, which are only partially addressed in recent technical reviews or guidelines [3-9]. We would also like to suggest tips and tricks to reduce common deficiencies in SBCE.

Artificial intelligence in small bowel capsule endoscopy ‐ current status, challenges and future promise

“…The first leap forward was done with in 2019, when a large multicenter Chinese study confirmed that a CNN‐based algorithm was able to accurately identify abnormalities in CE images and able to drastically reduce the CE reading times to around 6 min per video 24 . Recently, we alluded to the fact that CE is open to a high level of scrutiny and medicolegal challenge, as the recorded video data can be readily accessible for further on‐demand review 3 . AI solutions are not immune from such audits.…”

“…24 Recently, we alluded to the fact that CE is open to a high level of scrutiny and medicolegal challenge, as the recorded video data can be readily accessible for further on-demand review. 3 AI solutions are not immune from such audits.…”

“…Gastroenterologists spend 30–120 min to review and interpret full‐length small‐bowel capsule endoscopy (SBCE) recordings encompassing tens of thousands of images 2 . This task is tedious, often monotonous and demanding, as reading requires the physician to find a dedicated time slot without unwanted distractions 3 . Artificial intelligence (AI), on the other hand, affects every aspect of our life, including multiple health‐care domains.…”

“…2 This task is tedious, often monotonous and demanding, as reading requires the physician to find a dedicated time slot without unwanted distractions. 3 Artificial intelligence (AI), on the other hand, affects every aspect of our life, including multiple health-care domains. It has therefore become obvious to caregivers, academic researchers, medical, and information technology (IT) companies that computer-aided diagnosis solutions are needed for medical imaging, for example, GI endoscopy and more specifically SBCE.…”

Ileal neuroendocrine tumor: diagnosis by endoscopic capsule

“…We report the case of a patient with episodes of obscure intestinal hemorrhage. Being uncommon, with nonspecific symptoms, SINETs cause diagnostic pitfalls, but images by capsule endoscopy (CE) and enteroscopy allow early diagnosis (Kim et al, 2020;Perez-Cuadrado-Robles et al, 2020;Rondonotti et al, 2020;Vasilakakis et al, 2020;Yoo et al, 2020). Intestinal bleeding of unknown origin is a common symptom of adenocarcinoma and gastrointestinal stromal tumors (GISTs), which may propitiate diagnostic challenges or misdiagnosis with NETs (Yoo et al, 2020).…”