Gastrointestinal endoscopy has undergone significant transformation since its first introduction in the early 20th century. Despite advances in modern endoscopy, its precision in detecting and removing colorectal cancer (CRC) varies; colorectal polyps or cancer are still missed in 2.1-5.9% of cases. Additionally, post-colonoscopy CRC occurs in 30% of patients who have undergone incomplete polyp resection. When biopsies are taken, only 11.4% are found to be malignant, rendering 88.6% of tissue removal unnecessary. To address these shortcomings, modern endoscopy is evolving. Current endoscopic modalities include wide-field and microscopic-field endoscopy. Wide-field view endoscopy remains the most frequently used type and includes the current standard of practice—white light endoscopy—as well as other modalities such as virtual and dye-based chromoendoscopy, ultrathin endoscopy, and capsule endoscopy. Microscopic field endoscopy encompasses several new emerging modalities that can provide microscopic resolution capable of diagnosing lesions in vivo (optical biopsy), thus reducing the number of unnecessary biopsies. However, the emerging technology comes with a learning curve and requires time for endoscopists to master and achieve interobserver agreement. Consequently, there is a growing opportunity to develop machine learning technology to assist with the learning process. We review current modalities available for the diagnosis of CRC, including the current standard of practice, new enhanced imaging modalities, and optical biopsy.
