Artificial Intelligence (AI) and Liquid Biopsy Transforming Early Detection of Liver Metastases in Gastrointestinal Cancers.

Abstract

Liver metastases from Gastrointestinal (GI) cancers present significant challenges in oncology, often signaling poor prognosis. Traditional detection methods like imaging and tissue biopsies have limitations in sensitivity, specificity, and tumor heterogeneity represen-tation. The advent of artificial intelligence (AI) in healthcare, driven by advancements in ma-chine learning, algorithms, and data science, offers a promising frontier for early detection and management of liver metastases. This review explores the integration of AI and liquid biopsy technologies as transformative tools in the proactive detection of liver metastases aris-ing from GI malignancies. Liquid biopsy, a non-invasive method, analyzes circulating tumor cells (CTCs), cell-free DNA (cfDNA), and circulating tumor DNA (ctDNA) in bodily fluids. It provides a compre-hensive overview of tumor heterogeneity and enables real-time monitoring of tumor evolu-tion and treatment response. Despite its advantages, liquid biopsy faces challenges such as low sensitivity for early-stage metastases, reduced detectability due to liver filtration, and technical limitations. AI enhances the potential of liquid biopsies by improving diagnostic accuracy through ad-vanced algorithms like Convolutional Neural Networks (CNNs) and Natural Language Pro-cessing (NLP). These AI models analyze complex biomedical data, offering higher sensitivity and specificity in cancer detection. The synergy between AI and liquid biopsies promises early detection, better disease monitoring, and personalized treatment strategies. This review underscores the significant advancements AI and liquid biopsy technologies bring to oncological precision medicine, particularly in improving overall survival (OS) and disease-free survival (DFS) for patients with GI cancer metastases. As we transition into the era of precision medicine, the integration of these technologies holds the potential to redefine cancer care and patient management.