1.Risk Stratification of T1 Colorectal Cancer Metastasis to Lymph Nodes: Current Status and Perspective
Katsuro ICHIMASA ; Shin-ei KUDO ; Hideyuki MIYACHI ; Yuta KOUYAMA ; Masashi MISAWA ; Yuichi MORI
Gut and Liver 2021;15(6):818-826
With the widely spreading population-based screening programs for colorectal cancer and recent improvements in endoscopic diagnosis, the number of endoscopic resections in subjects with T1 colorectal cancer has been increasing. Some reports suggest that endoscopic resection prior to surgical resection of T1 colorectal cancer has no adverse effect on prognosis and contributes to this tendency. The decision on the need for surgical resection as an additional treatment after endoscopic resection of T1 colorectal cancer should be made according to the metastasis risk to lymph nodes based on histopathological findings. Because lymph node metastasis occurs in approximately 10% of patients with T1 colorectal cancer according to current international guidelines, the remaining 90% of patients may be at an increased risk of surgical resection and associated postoperative mortality, with no clinical benefit derived from unnecessary surgical resection. Although a more accurate prediction system for lymph node metastasis is needed to solve this problem, risk stratification for lymph node metastasis remains controversial. In this review, we focus on the current status of risk stratification of T1 colorectal cancer metastasis to lymph nodes and outline future perspectives.
2.Use of artificial intelligence in the management of T1 colorectal cancer: a new tool in the arsenal or is deep learning out of its depth?
James Weiquan LI ; Lai Mun WANG ; Katsuro ICHIMASA ; Kenneth Weicong LIN ; James Chi-Yong NGU ; Tiing Leong ANG
Clinical Endoscopy 2024;57(1):24-35
The field of artificial intelligence is rapidly evolving, and there has been an interest in its use to predict the risk of lymph node metastasis in T1 colorectal cancer. Accurately predicting lymph node invasion may result in fewer patients undergoing unnecessary surgeries; conversely, inadequate assessments will result in suboptimal oncological outcomes. This narrative review aims to summarize the current literature on deep learning for predicting the probability of lymph node metastasis in T1 colorectal cancer, highlighting areas of potential application and barriers that may limit its generalizability and clinical utility.
3.Challenges in Implementing Endoscopic Resection for T2Colorectal Cancer
Katsuro ICHIMASA ; Shin-ei KUDO ; Ker-Kan TAN ; Jonathan Wei Jie LEE ; Khay Guan YEOH
Gut and Liver 2024;18(2):218-221
The current standard treatment for muscularis propria-invasive (T2) colorectal cancer is surgical colectomy with lymph node dissection. With the advent of new endoscopic resection techniques, such as endoscopic full-thickness resection or endoscopic intermuscular dissection, T2 colorectal cancer, with metastasis to 20%-25% of the dissected lymph nodes, may be the next candidate for endoscopic resection following submucosal-invasive (T1) colorectal cancer. We present a novel endoscopic treatment strategy for T2 colorectal cancer and suggest further study to establish evidence on oncologic and endoscopic technical safety for its clinical implementation.