Advances in In Vitro Diagnostics for Cholangiocarcinoma: From Biomarker Discovery to Artificial Intelligence

Cholangiocarcinoma (CCA) is a highly aggressive malignancy that is difficult to diagnose early and carries a poor prognosis. Conventional serological diagnostics are limited by inadequate sensitivity and the risks of invasive procedures, resulting in most patients being diagnosed at an advanced stage. In recent years, liquid biopsy has emerged as a novel approach for non-invasive and dynamic molecular tumor monitoring by detecting biomarkers such as circulating tumor cells (CTCs), extracellular vesicles (EVs), circulating tumor DNA (ctDNA) and clusterin (CLU). Furthermore, artificial intelligence (AI) has demonstrated strong potential in aiding diagnosis through medical image analysis, pathological pattern recognition, and multi-omics data integration, significantly improving the precision of early detection, risk stratification, and treatment response monitoring in CCA. This review systematically summarizes recent advances in liquid biopsy and AI for CCA diagnosis, discusses their clinical potential and current challenges, and offers perspectives on how their integration can propel the field toward earlier and more precise management of the disease.