Deyirmendjian Claudia, Padda Banmeet, Fowler Kathryn J, Chernyak Victoria, Sirlin Claude B, Jiang Hanyu, Vu Kim-Nhien, Dadour Joseph R, Murphy-Lavallée Jessica, Billiard Jean-Sébastien, Olivié Damien, Nguyen Bich N, Tang An
Department of Radiology, Radiation Oncology, and Nuclear Medicine, Université de Montréal, Montréal, Québec, Canada.
Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA, USA.
Insights Imaging. 2025 Aug 15;16(1):181. doi: 10.1186/s13244-025-02058-7.
Hepatocellular carcinoma (HCC) encompasses a wide array of histopathologic and genetic features that can be broadly categorized as proliferative or non-proliferative HCC to reflect tumor aggressiveness. However, accurately characterizing tumor behavior remains challenging due to the biologic heterogeneity of HCC and limited access to tissue samples. Currently, imaging is used for the diagnosis of HCC using the Liver Imaging Reporting and Data System (LI-RADS) without histologic confirmation in most cases. Emerging data suggest that imaging can provide clinical insight beyond diagnosis and predict patient outcomes by identifying key prognostic features, including those not yet integrated in LI-RADS. Certain CT and MRI features correlate with proliferative and non-proliferative HCC, and may yield prognostic information. Imaging findings such as tumor size, multifocality, and low apparent diffusion coefficient (ADC) have also been associated with microvascular invasion-an independent marker of poor prognosis. Growing data support the role of imaging in predicting treatment responsiveness before therapy initiation, which may influence the selection of a therapeutic agent. The radiologist can offer key clinical information by understanding and describing the prognostic and predictive features in HCC imaging. CRITICAL RELEVANCE STATEMENT: This study provides radiologists with a comprehensive summary of imaging findings associated with HCC prognosis, treatment responsiveness, and microvascular invasion. KEY POINTS: Hepatocellular carcinoma (HCC) is a heterogeneous cancer leading to challenges in diagnosis and management. Tumors can exhibit imaging features associated with proliferative or non-proliferative HCC. Key imaging features can help predict tumor aggressiveness and treatment responsiveness before the therapy is applied. Further research leveraging molecular data and applying machine learning models can improve our understanding of HCC prognostication.
肝细胞癌（HCC）具有广泛的组织病理学和遗传学特征，大致可分为增殖性或非增殖性HCC，以反映肿瘤的侵袭性。然而，由于HCC的生物学异质性以及获取组织样本的机会有限，准确描述肿瘤行为仍然具有挑战性。目前，在大多数情况下，使用肝脏影像报告和数据系统（LI-RADS）进行成像用于HCC的诊断，而无需组织学确认。新出现的数据表明，成像不仅可以用于诊断，还能通过识别关键的预后特征（包括那些尚未纳入LI-RADS的特征）为临床提供见解并预测患者预后。某些CT和MRI特征与增殖性和非增殖性HCC相关，可能产生预后信息。诸如肿瘤大小、多灶性和低表观扩散系数（ADC）等影像学表现也与微血管侵犯相关，微血管侵犯是预后不良的独立标志物。越来越多的数据支持成像在治疗开始前预测治疗反应性方面的作用，这可能会影响治疗药物的选择。放射科医生通过理解和描述HCC成像中的预后和预测特征，可以提供关键的临床信息。关键相关性声明：本研究为放射科医生提供了与HCC预后、治疗反应性和微血管侵犯相关的影像学表现的全面总结。关键点：肝细胞癌（HCC）是一种异质性癌症，导致诊断和管理方面的挑战。肿瘤可表现出与增殖性或非增殖性HCC相关的影像学特征。关键影像学特征可有助于在治疗应用前预测肿瘤的侵袭性和治疗反应性。利用分子数据并应用机器学习模型的进一步研究可以提高我们对HCC预后的理解。
