Advances in optical gastrointestinal endoscopy: a technical review

Abstract

Optical endoscopy is the primary diagnostic and therapeutic tool for management of gastrointestinal (GI) malignancies. Most GI neoplasms arise from precancerous lesions; thus, technical innovations to improve detection and diagnosis of precancerous lesions and early cancers play a pivotal role in improving outcomes. Over the last few decades, the field of GI endoscopy has witnessed enormous and focused efforts to develop and translate accurate, user-friendly, and minimally invasive optical imaging modalities. From a technical point of view, a wide range of novel optical techniques is now available to probe different aspects of light-tissue interaction at macroscopic and microscopic scales, complementing white light endoscopy. Most of these new modalities have been successfully validated and translated to routine clinical practice. Herein, we provide a technical review of the current status of existing and promising new optical endoscopic imaging technologies for GI cancer screening and surveillance. We summarize the underlying principles of light-tissue interaction, the imaging performance at different scales, and highlight what is known about clinical applicability and effectiveness. Furthermore, we discuss recent discovery and translation of novel molecular probes that have shown promise to augment endoscopists' ability to diagnose GI lesions with high specificity. We also review and discuss the role and potential clinical integration of artificial intelligence-based algorithms to provide decision support in real time. Finally, we provide perspectives on future technology development and its potential to transform endoscopic GI cancer detection and diagnosis.

Keywords: gastrointestinal tract; machine learning; molecular probe; optical endoscopy.

Fig. 1

Optical endoscopic techniques for macroscopic and microscopic imaging of the GI mucosa. Existing macroscopic modalities include high‐definition endoscopy, ultrathin endoscopy, and capsule endoscopy. Microscopic resolution can be achieved using OCT, endocytoscopy, CLE, and HRME. Reproduced from [66, 81, 136] with permission from Elsevier (white light and chromoendoscope, capsule endoscope, and endocytoscopy, respectively), from [55] with permission from John Wiley and Sons (ultrathin endoscope), from [137] by permission from Springer Nature (OCT), from [69] with permission from © Georg Thieme Verlag KG (CLE).

Fig. 2

Examples of capsule‐, balloon‐, and probe‐based optical endoscopic systems. (A) Capsule endoscopes (MicroCam and PillCam). (B) VLE probe within an inflated balloon catheter. (C) Confocal laser endomicroscope through a biopsy channel. (D) A low‐cost HRME with integrated diagnostic software. Figure 2B–D reproduced from [97, 138, 139] with permission from Elsevier.

Fig. 3

Examples of computer‐aided algorithms for detection and diagnosis of colorectal polyps. (A) In microscopic images of polyps collected with endocytoscopy, clinically inspired nuclear morphology features were extracted and quantified for diagnosing advanced histology. (B) A data‐driven algorithm is trained using a convolutional neural network to highlight adenomatous CRC polyps in WLE images. Figure 3A reproduced from [134] with permission from Elsevier. Figure 3Breproduced from [125] with permission from BMJ Publishing Group Ltd.