The Gray Zone: LR3, LR-M, and LR-TIV

K. Ganesan, Shivsamb Jalkote, S. Nellore
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引用次数: 1

Abstract

Abstract The goal of Liver Imaging Reporting and Data System (LI-RADS) is to standardize the lexicon, imaging techniques, interpretation, and reporting of observations in patients with a potential risk for developing hepatocellular carcinoma (HCC), and, consequently, improve communication between radiologists and physicians. LI-RADS diagnostic algorithms are applied to a population “at risk,” follow a stepwise algorithmic approach which categorize and stratify individual observations as HCC, and also assess the likelihood of non-HCC malignancies and tumor in vein. Risk factors for developing HCC have geographical variations, which significantly impact diagnostic and management strategies; however, these variations are not considered in the LIRADS v2018 version. Further, the diagnostic algorithm includes several major and ancillary features, and, tie-breaking rules, which result in numerous probable combinations by which a plausible observation could be assigned a particular category, inherently increasing its complexity. Heterogeneity of the diagnostic algorithm results in certain imaging pitfalls and poses challenges in the precise characterization of observations, complicating its use in routine clinical practice. This article reviews the gray zones which may be encountered in the evaluation of LR-3, LR-M, and LR-TIV observations during routine clinical imaging with contrast-enhanced computed tomography and magnetic resonance imaging.
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灰色地带:LR3、LR-M和LR-TIV
肝脏影像学报告和数据系统(LI-RADS)的目标是标准化具有潜在发展为肝细胞癌(HCC)风险的患者的词汇、影像学技术、解释和观察报告,从而改善放射科医生和医生之间的沟通。LI-RADS诊断算法应用于“有风险”的人群,遵循逐步算法方法,将个体观察分类和分层为HCC,并评估非HCC恶性肿瘤和静脉肿瘤的可能性。发生HCC的危险因素具有地理差异,这显著影响诊断和管理策略;然而,这些变化在LIRADS v2018版本中不被考虑。此外,诊断算法包括几个主要和辅助特征,以及打破规则,这导致许多可能的组合,通过这些组合,一个合理的观察可以被分配到一个特定的类别,本质上增加了它的复杂性。诊断算法的异质性导致某些成像缺陷,并对观察结果的精确表征提出挑战,使其在常规临床实践中的应用复杂化。本文回顾了对比增强计算机断层扫描和磁共振成像在常规临床成像中对LR-3、LR-M和LR-TIV观察进行评估时可能遇到的灰色地带。
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30
审稿时长
23 weeks
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