我国是肝癌的高发国家，大多数肝癌是由肝硬化结节演变而来，因此肝硬化高危结节的早期检出与评估对肝硬化临床管理和提高肝癌患者预后非常重要。国内外相关指南和共识均提出，影像学检查是监测肝硬化进展的主要手段。既往较多研究以及我们的前期研究提示影像学检查，特别是MRI检查能有效检出肝硬化结节以及大致评估结节的病理阶段，但目前仍缺乏对肝硬化高危结节的准确评估方法。本研究拟采用建立最接近人肝癌的猪肝癌实验动物模型和临床试验，评价多种MRI技术各自对肝硬化高危结节预测的准确性，在此基础上我们将结合多模态MR技术、相关实验室参数及其他重要的临床标志物，进行大数据分析，推导数学模型并验证、修正，以期建立一个行之有效的肝硬化高危结节早期预测与诊断系统。

Hepatocellular carcinoma (HCC) is highly prevalent in China. Pathologically, most HCCs evolve from liver cirrhotic nodules. Therefore, early detection and evaluation of cirrhotic nodules in patient at high risks of developing HCCs are vital for the proper clinical management of liver cirrhosis and improving the prognosis of HCC patients. Currently, clinical practice guidelines from home and abroad all identified imaging examination as the major technique for liver cirrhosis surveillance. Previous studies, in accordance with our preliminary research suggested that imaging examination, especially magnetic resonance imaging (MRI), can effectively detect cirrhotic nodules and probably evaluate the pathologic stages of cirrhotic nodules. However, precise assessment of high-risk liver cirrhotic nodules remains a challenge. This study aims to assess the diagnostic performances of several MRI modalities, separately, in predicting high-risk cirrhotic nodules, by establishing a pig liver cirrhosis model which can highly imitate the progress of cirrhotic nodules in human, and in clinical trials. Based on this, we intend to develop a diagnostic algorithm for high-risk cirrhotic nodules by performing a big data analytics on the weighted multimodal MRI parameters, laboratory serology results and other significant clinical information, and to validate its diagnostic performance and clinical utility.