Evolution of the treatment of esophageal cancer: artificial intelligence and the role of sentinel lymph node assessment in esophageal cancer

Sentinel lymph node (SLN) biopsy has revolutionized the staging and prognosis of breast cancer and melanoma. Because of the complicated lymphatic network around the esophagus, the utility of SLN biopsy for esophageal cancer is less clear. The accuracy of SLN mapping in esophageal cancer depends on tumor site, disease stage, use of neoadjuvant therapy, and patient characteristics. SLN biopsy may improve staging and result in less morbidity in patients with early esophageal cancer, compared with radical lymphadenectomy and esophagectomy. A recent study that investigated hybrid tracers in sentinel node navigation surgery (SNNS) demonstrated promising results for the detection of peritumoral SLNs. However, evidence that firmly establishes the concept of the SLN for esophageal cancer is still lacking. Big data analytics and artificial intelligence have been associated with improvements in the detection and prognosis of esophageal cancer. This review considers the roles of the evolving technologies of SLN biopsy and artificial intelligence, which together have the potential to further improve prognoses and outcomes for patients with esophageal cancer. Additional investigation is necessary to establish standardized protocols and to determine the long-term effectiveness of these approaches in settings involving neoadjuvant therapy and advanced-stage disease.