Primary hepatocellular carcinoma is a common malignant tumor at home and abroad. In 2020, it became the seventh most malignant tumor to threaten human health on a global scale, with a high mortality rate that ranked fourth among cancers. Therefore, a precise diagnosis is crucial for the prognosis of primary hepatocellular carcinoma. Radiomics, an emerging non-invasive data analysis method, extracts a large number of high-throughput features from imaging images, thereby providing a more accurate basis for clinical diagnosis and treatment decision-making. Currently, there are many radiomic models for diagnosing hepatocellular carcinoma, but there is a lack of consensus. This consensus formulates ultimate radiomics model recommendations based on the latest research evidence, an evidence-based medicine combination grading system, comprehensive consideration of clinical practice, and the experience of physician specialists so as to provide clinicians with a methodological basis for clarifying the diagnosis, developing the best decision-making scheme, and guiding clinically comprehensive treatment.

Hepatocellular carcinoma; Diagnosis; Omics; Model; Consensus