肝细胞癌的预后和预测影像标记:一篇图片文章。

IF 4.5 2区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Claudia Deyirmendjian, Banmeet Padda, Kathryn J Fowler, Victoria Chernyak, Claude B Sirlin, Hanyu Jiang, Kim-Nhien Vu, Joseph R Dadour, Jessica Murphy-Lavallée, Jean-Sébastien Billiard, Damien Olivié, Bich N Nguyen, An Tang
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引用次数: 0

摘要

肝细胞癌(HCC)包括一系列广泛的组织病理学和遗传特征,可以大致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的生物学异质性和有限的组织样本,准确表征肿瘤行为仍然具有挑战性。目前,大多数HCC的影像学诊断采用肝影像学报告和数据系统(LI-RADS),没有组织学证实。新出现的数据表明,成像可以提供诊断之外的临床见解,并通过识别关键预后特征来预测患者的预后,包括那些尚未整合到LI-RADS中的特征。某些CT和MRI特征与增殖性和非增殖性HCC相关,并可能提供预后信息。影像学表现如肿瘤大小、多灶性和低表观扩散系数(ADC)也与微血管侵袭有关,这是预后不良的独立标志。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,这可能影响治疗药物的选择。放射科医生可以通过理解和描述HCC影像学的预后和预测特征来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结果的综合总结。肝细胞癌(HCC)是一种异质性癌症,在诊断和治疗方面都面临挑战。肿瘤可表现出与增殖性或非增殖性HCC相关的影像学特征。关键的影像学特征可以帮助预测肿瘤的侵袭性和治疗反应在治疗前应用。利用分子数据和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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prognostic and predictive imaging markers of hepatocellular carcinoma: a pictorial essay.

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.

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来源期刊
Insights into Imaging
Insights into Imaging Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
7.30
自引率
4.30%
发文量
182
审稿时长
13 weeks
期刊介绍: Insights into Imaging (I³) is a peer-reviewed open access journal published under the brand SpringerOpen. All content published in the journal is freely available online to anyone, anywhere! I³ continuously updates scientific knowledge and progress in best-practice standards in radiology through the publication of original articles and state-of-the-art reviews and opinions, along with recommendations and statements from the leading radiological societies in Europe. Founded by the European Society of Radiology (ESR), I³ creates a platform for educational material, guidelines and recommendations, and a forum for topics of controversy. A balanced combination of review articles, original papers, short communications from European radiological congresses and information on society matters makes I³ an indispensable source for current information in this field. I³ is owned by the ESR, however authors retain copyright to their article according to the Creative Commons Attribution License (see Copyright and License Agreement). All articles can be read, redistributed and reused for free, as long as the author of the original work is cited properly. The open access fees (article-processing charges) for this journal are kindly sponsored by ESR for all Members. The journal went open access in 2012, which means that all articles published since then are freely available online.
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