Radiomics in liver research: A paradigm shift in disease detection and staging

This narrative review explores radiomics in the broader context of liver disease research, an interdisciplinary field bridging medical imaging, oncology, and data science. It begins with an introduction to data analysis techniques, from foundational methods like descriptive statistics, comparative and regression analysis, and survival analysis, to advanced approaches like machine learning (ML), meta-analysis, and bioinformatics. Contextualizing these methodologies within liver disease research enhances our understanding of liver diseases. The focus is on radiomics, an emerging field, which is first placed in historical context before its applications are explained across fatty liver diseases (FLD), fibrosis, cirrhosis, and liver cancers. The role of radiomics in early detection, disease staging, and outcome prediction, particularly as a non-invasive alternative to liver biopsy, is analyzed in-depth. Current imaging modalities for liver cancer diagnosis are also examined, highlighting their advantages and limitations. Alongside radiomics, these imaging tools enable comprehensive liver assessment. Lastly, the integration of radiomics with other data types, especially genomic data, is explored, emphasizing its role in a holistic approach to liver disease management. The review concludes with a forward-looking perspective on future directions and advancements in radiomics and liver cancer research, addressing the challenges and opportunities in the field. It underscores the transformative impact of these developments on liver cancer research, patient care, personalized medicine, and clinical decision-making. • Radiomics aids diagnosis across liver disease stages, including NAFLD, fibrosis, cirrhosis, and liver cancer.. • Radiomics offers a non-invasive, effective alternative to liver biopsy for diagnosing liver conditions. • Radiomics integrates with MRI, CT, and ultrasound to enhance liver disease imaging and diagnosis. • Radiomics supports personalized medicine and improves clinical decisions in liver disease management.