Clin Endosc.  2024 Jan;57(1):24-35. 10.5946/ce.2023.036.

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?

• Li JW
• Wang LM
• Ichimasa K
• Lin KW
• Ngu JCY
• Ang TL

• KMID: 2551187
• DOI: http://doi.org/10.5946/ce.2023.036

Abstract

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.

Keyword

Artificial intelligence; Deep learning; Lymph node metastasis; T1 colorectal cancer

Figure

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  Fig. 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses diagram of the literature search. AI, artificial intelligence; CRC, colorectal cancer.

• 

  Fig. 2. Schematic diagram illustrating varied sources of input and differing outputs to reach a clinical decision on lymph node metastasis (LNM) in T1 colorectal cancer (CRC). AI, artificial intelligence; ML, machine learning; NLP, natural language processing; WSI, whole slide imaging; CT, computed tomography; MRI, magnetic resonance imaging; LVI, lymphovascular invasion.

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