The future of endoscopy: Advances in endoscopic image innovations

Abstract

The latest state of the art technological innovations have led to a palpable progression in endoscopic imaging and may facilitate standardisation of practice. One of the most rapidly evolving modalities is artificial intelligence with recent studies providing real-time diagnoses and encouraging results in the first randomised trials to conventional endoscopic imaging. Advances in functional hypoxia imaging offer novel opportunities to be used to detect neoplasia and the assessment of colitis. Three-dimensional volumetric imaging provides spatial information and has shown promise in the increased detection of small polyps. Studies to date of self-propelling colonoscopes demonstrate an increased caecal intubation rate and possibly offer patients a more comfortable procedure. Further development in robotic technology has introduced ex vivo automated locomotor upper gastrointestinal and small bowel capsule devices. Eye-tracking has the potential to revolutionise endoscopic training through the identification of differences in experts and non-expert endoscopist as trainable parameters. In this review, we discuss the latest innovations of all these technologies and provide perspective into the exciting future of diagnostic luminal endoscopy.

Standing‐type magnetically guided capsule endoscopy versus gastroscopy for gastric examination: multicenter blinded comparative trial

“…With the application of artificial intelligence, SMCE system has been able to screen 80–90% of similar images, greatly reducing the burden on doctors. Similar to published studies, doctor's reading time will further shorten with the application of computer‐assisted diagnosis. Image‐processing technologies have also been applied to CE .…”

Can image‐enhanced endoscopy improve the diagnosis of Kyoto classification of gastritis in the clinical setting?

“…Computer‐aided diagnosis (CAD) is rapidly developing to help endoscopists improve detection and diagnosis of gastrointestinal disease . CAD is also currently used for endoscopic diagnosis of H. pylori infection.…”

“…C OMPUTER -AIDED DIAGNOSIS (CAD) is rapidly developing to help endoscopists improve detection and diagnosis of gastrointestinal disease. [58][59][60][61] CAD is also currently used for endoscopic diagnosis of H. pylori infection. Recent advances in the development of deep learning (DL) algorithm, which autonomously extracts and learns discriminative features of the image, and convolutional neural networks (CNN) can analyze complex features of images including shapes, colors, and textures.…”

Next generation of endoscopy: Harmony with artificial intelligence and robotic‐assisted devices

“…The authors have also illustrated hypoxia imaging, roboticassisted devices to enable automated endoscopy, and eye tracking technology. 1 Thus, an intellectual review is beneficial in disseminating the knowledge on how endoscopic imaging is being developed and enabling the readers to foreseeably imagine the future of diagnostic luminal endoscopy.…”

“…Otherwise, WavSTAT4 (Spectra Science, San Diego, CA, USA) was approved by the US Food and Drug Administration as a CAD optical biopsy system. 1 Both the AI systems under regulatory approval for optical biopsy have potential limitation of external validity in the earlier stages; selection bias has still not been eliminated. Extrapolating these findings obtained in the promising academic settings to community-based hospitals cannot be fully implemented in real practice.…”