New frontiers in hepatocellular carcinoma: Precision imaging for microvascular invasion prediction

Abstract

This paper highlights the innovative approach and findings of the recently published study by Xu et al, which underscores the integration of radiomics and clinicoradiological factors to enhance the preoperative prediction of microvascular invasion in patients with hepatitis B virus-related hepatocellular carcinoma (HBV-HCC). The study’s use of contrast-enhanced computed tomography radiomics to construct predictive models offers a significant advancement in the surgical planning and management of HBV-HCC, potentially transforming patient outcomes through more personalized treatment strategies. This editorial commends the study's contribution to precision medicine and discusses its implications for future research and clinical practice.

Keywords: Microvascular invasion prediction; Hepatocellular carcinoma; Radiomics; Precision imaging; Hepatitis B virus

Core Tip: The integration of precision medicine in hepatocellular carcinoma (HCC) management is crucial for tailoring treatment to individual patient characteristics, and leveraging radiomics serves as a powerful non-invasive tool for predicting microvascular invasion preoperatively, thereby guiding more informed surgical decisions. To enhance the robustness and applicability of predictive models, multicentric studies involving diverse populations should be promoted, alongside the integration of radiomics with genetic and molecular markers for a more comprehensive understanding of the tumor microenvironment. Embracing advancements in imaging technologies and conducting cost-effectiveness analyses are essential for justifying the adoption of radiomics in clinical practice. Additionally, addressing ethical considerations regarding patient data privacy and promoting the use of radiomics in prospective clinical trials can help validate their effectiveness in real-world settings. Investing in training for healthcare professionals will improve their interpretation of radiomics data, facilitating its routine use, while fostering collaboration among oncologists, radiologists, data scientists, and researchers will continually refine predictive models and enhance their utility in managing HCC.