Caihong Wang, Wen Zhang, Hong Li, Wenyue Wu, Ziyan Pan, Ruoyu Gao, Haodong Ma, Qiushuang Ji, Zhi Chen, Wei Chen, Hong You
Early-stage liver fibrosis (F1-F2) constitutes a clinically silent yet pivotal phase during which therapeutic intervention may halt or reverse disease progression. However, its timely identification remains challenging given the limited sensitivity of currently non-invasive tests (NITs), including routine serological panels and elastography-based techniques. This review provides a comprehensive and systematic evaluation of the evolving diagnostic landscape aimed at addressing this unmet need. Established approaches are critically appraised alongside emerging next-generation NITs, including ultrasensitive serum biomarkers, molecular imaging probes targeting fibrogenic activity, and artificial intelligence (AI)-driven analysis of conventional imaging modalities. In addition, this review examines innovative diagnostic strategies based on alternative biofluids, including urine, exhaled breath, and saliva, as well as gut microbiota-derived biomarkers and multiomics-integrated models, all of which offer distinct pathophysiological insights and potential advantages in large-scale screening. Despite their considerable promise for improving the precision of early-stage fibrosis detection, these approaches face substantial barriers to clinical implementation, including challenges related to validation, standardization, and integration into existing diagnostic pathways. Addressing these limitations will be essential for establishing a robust, multidimensional diagnostic framework capable of enabling early detection, guiding timely intervention, and advancing the paradigm of hepatology toward effective disease prevention.