自2011年首次发布以来，肝脏影像报告和数据系统（LI-RADS）已经发展和扩大了范围。它最初是用于CT或MRI的单一算法，用于肝细胞癌（HCC）诊断并使用细胞外造影剂，并已发展成为覆盖所有主要肝脏成像模式和使用情境的多算法网络。此外，它还开发了自己的词汇表、报告模板和补充材料。本文重点介绍LI-RADS在过去11年中的主要成果，包括在全球范围内的临床治疗和研究中的应用，并在美国完全统一了HCC诊断系统。此外，作者讨论了当前的知识空白，包括监测、诊断人群定义、认为复杂、LR-5（明确的HCC）类别的敏感性有限、不确定观察的管理影响、报告挑战以及基于放射治疗和系统治疗的治疗反应评估的挑战。最后，作者讨论了未来的方向，重点关注减轻当前的挑战和整合先进技术。作者们预测，LI-RADS最终将转变为一种基于概率的诊断和预后系统，将整合患者特征和定量成像特征，并考虑成像模式和造影剂。©RSNA，2023。

Since its initial release in 2011, the Liver Imaging Reporting and Data System (LI-RADS) has evolved and expanded in scope. It started as a single algorithm for hepatocellular carcinoma (HCC) diagnosis with CT or MRI with extracellular contrast agents and has grown into a multialgorithm network covering all major liver imaging modalities and contexts of use. Furthermore, it has developed its own lexicon, report templates, and supplementary materials. This article highlights the major achievements of LI-RADS in the past 11 years, including adoption in clinical care and research across the globe, and complete unification of HCC diagnostic systems in the United States. Additionally, the authors discuss current gaps in knowledge, which include challenges in surveillance, diagnostic population definition, perceived complexity, limited sensitivity of LR-5 (definite HCC) category, management implications of indeterminate observations, challenges in reporting, and treatment response assessment following radiation-based therapies and systemic treatments. Finally, the authors discuss future directions, which will focus on mitigating the current challenges and incorporating advanced technologies. Tha authors envision that LI-RADS will ultimately transform into a probability-based system for diagnosis and prognostication of liver cancers that will integrate patient characteristics and quantitative imaging features, while accounting for imaging modality and contrast agent.© RSNA, 2023.