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The Liver Imaging Reporting And Data System (LI-RADS) was created with the support of the American College of Radiology (ACR) to standardize the acquisition, interpretation, reporting, and data collection for imaging examinations in patients at risk for hepatocellular carcinoma (HCC). A comprehensive and rigorous system developed by radiologists, hepatologists, pathologists, and surgeons, LI-RADS addresses a wide range of imaging contexts. Currently, 4 algorithms are available publicly on the ACR website: ultrasound for HCC surveillance, computed tomography and magnetic resonance imaging for HCC diagnosis and tumor staging, contrast-enhanced ultrasound for HCC diagnosis, and computed tomography/magnetic resonance imaging for treatment response assessment. Each algorithm is supported by a decision tree, categorization table, lexicon, atlas, technical requirements, and reporting and management guidance. Category codes reflecting the relative probability of HCC and malignancy are assigned to imaging-detected liver observations, with emerging evidence suggesting that LI-RADS accurately stratifies HCC and malignancy probabilities. LI-RADS is an evolving system and has been updated and refined iteratively since 2011 based on scientific evidence, expert opinion, and user feedback, with input from the American Association for the Study of Liver Diseases and the Organ Procurement Transplantation Network/United Network for Organ Sharing. Concurrent with its most recent update, LI-RADS was integrated into the American Association for the Study of Liver Diseases HCC guidance released in 2018. We anticipate continued refinement of LI-RADS and progressive adoption by radiologists worldwide, with the eventual goal of culminating in a single unified system for international use.

The Liver Imaging Reporting and Data System (LI-RADS®) is a comprehensive system for standardizing the terminology, technique, interpretation, reporting, and data collection of liver observations in individuals at high risk for hepatocellular carcinoma (HCC). LI-RADS is supported and endorsed by the American College of Radiology (ACR). Upon its initial release in 2011, LI-RADS applied only to liver observations identified at CT or MRI. It has since been refined and expanded over multiple updates to now also address ultrasound-based surveillance, contrast-enhanced ultrasound for HCC diagnosis, and CT/MRI for assessing treatment response after locoregional therapy. The LI-RADS 2018 version was integrated into the HCC diagnosis, staging, and management practice guidance of the American Association for the Study of Liver Diseases (AASLD). This article reviews the major LI-RADS updates since its 2011 inception and provides an overview of the currently published LI-RADS algorithms.

The Liver Imaging Reporting and Data System (LI-RADS) is composed of four individual algorithms intended to standardize the lexicon, as well as reporting and care, in patients with or at risk for hepatocellular carcinoma in the context of surveillance with US; diagnosis with CT, MRI, or contrast material-enhanced US; and assessment of treatment response with CT or MRI. This report provides a broad overview of LI-RADS, including its historic development, relationship to other imaging guidelines, composition, aims, and future directions. In addition, readers will understand the motivation for and key components of the 2018 update.

The Liver Imaging and Reporting Data System (LI-RADS) is a comprehensive system for standardizing the terminology, technique, interpretation, reporting, and data collection of liver imaging with the overarching goal of improving communication, clinical care, education, and research relating to patients at risk for or diagnosed with hepatocellular carcinoma (HCC). In 2018, the American Association for the Study of Liver Diseases (AASLD) integrated LI-RADS into its clinical practice guidance for the imaging-based diagnosis of HCC. The harmonization between the AASLD and LI-RADS diagnostic imaging criteria required minor modifications to the recently released LI-RADS v2017 guidelines, necessitating a LI-RADS v2018 update. This article provides an overview of the key changes included in LI-RADS v2018 as well as a look at the LI-RADS v2018 diagnostic algorithm and criteria, technical recommendations, and management suggestions. Substantive changes in LI-RADS v2018 are the removal of the requirement for visibility on antecedent surveillance ultrasound for LI-RADS 5 (LR-5) categorization of 10-19 mm observations with nonrim arterial phase hyper-enhancement and nonperipheral "washout", and adoption of the Organ Procurement and Transplantation Network definition of threshold growth (≥ 50% size increase of a mass in ≤ 6 months). Nomenclatural changes in LI-RADS v2018 are the removal of -us and -g as LR-5 qualifiers.

The composition of the inner magnetosphere is of great importance for determining the plasma pressure and thus the currents and magnetic field configuration. In this study, we perform a statistical survey of equatorial plasma pressure distributions and investigate the relative contributions of ions and electron with different energies inside of geostationary orbit under two auroral electrojet levels based on over 60 months of observations from the Helium, Oxygen, Proton, and Electron and Radiation Belt Storm Probes Ion Composition Experiment mass spectrometers onboard Van Allen Probes. We find that the total and partial pressures of different species increase significantly at high auroral electrojet levels with hydrogen pressure being dominant in the plasmasphere. The pressures of the heavy ions and electrons increase outside the plasmapause and develop a strong dawn-dusk asymmetry with ion pressures peaking at dusk and electron pressure peaking at dawn. In addition, ring current hydrogen with energies ranging from 50 keV up to several hundred keV is the dominant component of plasma pressure during both quiet (>90%) and active times (>60%), while oxygen with 10

The computed tomography / magnetic resonance imaging (CT/MRI) Liver Imaging Reporting & Data System (LI-RADS) is a standardized system for diagnostic imaging terminology, technique, interpretation, and reporting in patients with or at risk for developing hepatocellular carcinoma (HCC). Using diagnostic algorithms and tables, the system assigns to liver observations category codes reflecting the relative probability of HCC or other malignancies. This review article provides an overview of the 2017 version of CT/MRI LI-RADS with a focus on MRI. The main LI-RADS categories and their application will be described. Changes and updates introduced in this version of LI-RADS will be highlighted, including modifications to the diagnostic algorithm and to the optional application of ancillary features. Comparisons to other major diagnostic systems for HCC will be made, emphasizing key similarities, differences, strengths, and limitations. In addition, this review presents the new Treatment Response algorithm, while introducing the concepts of MRI nonviability and viability. Finally, planned future directions for LI-RADS will be outlined.Level of evidence5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018;47:1459-1474.

A radiologist issuing a LI-RADS category is, implicitly or explicitly, a member of a multidisciplinary team. If the definite diagnosis of a benign or malignant entity is not possible, categorizing the uncertainty as LR-2, -3, -4, or -M has important management implications. In this article, we discuss the range of options for management or further diagnostic testing and how a LR category may affect the choice between them. We then review recent published data regarding eventual diagnoses following assignment of a LR category.

Over the past 16 years, several scientific organizations have proposed systems that incorporate imaging for surveillance, diagnosis, staging, treatment, and monitoring of treatment response of hepatocellular carcinoma (HCC). These systems are needed to standardize the acquisition, interpretation, and reporting of liver imaging examinations; help differentiate benign from malignant observations; improve consistency between radiologists; and provide guidance for management of HCC. This review article discusses the historical evolution of HCC imaging systems. We indicate the features differentiating these systems, including target population, screening and surveillance algorithm, diagnostic imaging modalities, diagnostic scope, expertise and technical requirements, terminology, major and ancillary imaging features, staging and transplant eligibility, and assessment of treatment response. We highlight the potential benefits of unifying the systems, which we anticipate will enable sharing, pooling, and meta-analysis of data; facilitate multi-center trials; and accelerate dissemination of knowledge.

Purpose To determine in a large multicenter multireader setting the interreader reliability of Liver Imaging Reporting and Data System (LI-RADS) version 2014 categories, the major imaging features seen with computed tomography (CT) and magnetic resonance (MR) imaging, and the potential effect of reader demographics on agreement with a preselected nonconsecutive image set. Materials and Methods Institutional review board approval was obtained, and patient consent was waived for this retrospective study. Ten image sets, comprising 38-40 unique studies (equal number of CT and MR imaging studies, uniformly distributed LI-RADS categories), were randomly allocated to readers. Images were acquired in unenhanced and standard contrast material-enhanced phases, with observation diameter and growth data provided. Readers completed a demographic survey, assigned LI-RADS version 2014 categories, and assessed major features. Intraclass correlation coefficient (ICC) assessed with mixed-model regression analyses was the metric for interreader reliability of assigning categories and major features. Results A total of 113 readers evaluated 380 image sets. ICC of final LI-RADS category assignment was 0.67 (95% confidence interval [CI]: 0.61, 0.71) for CT and 0.73 (95% CI: 0.68, 0.77) for MR imaging. ICC was 0.87 (95% CI: 0.84, 0.90) for arterial phase hyperenhancement, 0.85 (95% CI: 0.81, 0.88) for washout appearance, and 0.84 (95% CI: 0.80, 0.87) for capsule appearance. ICC was not significantly affected by liver expertise, LI-RADS familiarity, or years of postresidency practice (ICC range, 0.69-0.70; ICC difference, 0.003-0.01 [95% CI: -0.003 to -0.01, 0.004-0.02]. ICC was borderline higher for private practice readers than for academic readers (ICC difference, 0.009; 95% CI: 0.000, 0.021). Conclusion ICC is good for final LI-RADS categorization and high for major feature characterization, with minimal reader demographic effect. Of note, our results using selected image sets from nonconsecutive examinations are not necessarily comparable with those of prior studies that used consecutive examination series. © RSNA, 2017.

The Liver Imaging Reporting and Data System (LI-RADS) standardizes the interpretation, reporting, and data collection for imaging examinations in patients at risk for hepatocellular carcinoma (HCC). It assigns category codes reflecting relative probability of HCC to imaging-detected liver observations based on major and ancillary imaging features. LI-RADS also includes imaging features suggesting malignancy other than HCC. Supported and endorsed by the American College of Radiology (ACR), the system has been developed by a committee of radiologists, hepatologists, pathologists, surgeons, lexicon experts, and ACR staff, with input from the American Association for the Study of Liver Diseases and the Organ Procurement Transplantation Network/United Network for Organ Sharing. Development of LI-RADS has been based on literature review, expert opinion, rounds of testing and iteration, and feedback from users. This article summarizes and assesses the quality of evidence supporting each LI-RADS major feature for diagnosis of HCC, as well as of the LI-RADS imaging features suggesting malignancy other than HCC. Based on the evidence, recommendations are provided for or against their continued inclusion in LI-RADS. © RSNA, 2017 Online supplemental material is available for this article.

The Liver Imaging Reporting and Data System (LI-RADS) is a reporting system created for the standardized interpretation of liver imaging findings in patients who are at risk for hepatocellular carcinoma (HCC). This system was developed with the cooperative and ongoing efforts of an American College of Radiology-supported committee of diagnostic radiologists with expertise in liver imaging and valuable input from hepatobiliary surgeons, hepatologists, hepatopathologists, and interventional radiologists. In this article, the 2017 version of LI-RADS for computed tomography and magnetic resonance imaging is reviewed. Specific topics include the appropriate population for application of LI-RADS; technical recommendations for image optimization, including definitions of dynamic enhancement phases; diagnostic and treatment response categories; definitions of major and ancillary imaging features; criteria for distinguishing definite HCC from a malignancy that might be non-HCC; management options following LI-RADS categorization; and reporting. ©RSNA, 2017.

The increasing incidence and high morbidity and mortality of hepatocellular carcinoma (HCC) have inspired the creation of the Liver Imaging Reporting and Data System (LI-RADS). LI-RADS aims to reduce variability in exam interpretation, improve communication, facilitate clinical therapeutic decisions, reduce omission of pertinent information, and facilitate the monitoring of outcomes. LI-RADS is a dynamic process, which is updated frequently. In this article, we describe the LI-RADS 2014 version (v2014), which marks the second update since the initial version in 2011.

To improve standardization and consensus regarding performance, interpreting, and reporting computed tomography (CT) and magnetic resonance imaging (MRI) examinations of the liver in patients at risk for hepatocellular carcinoma (HCC), LI-RADS (Liver Imaging Reporting and Data System) was launched in March 2011 and adopted by many clinical practices throughout the world. LI-RADS categorizes nodules recognized at CT or MRI, in patients at high risk of HCC, as definitively benign, probably benign, intermediate probability of being HCC, probably HCC, and definitively HCC (corresponding to LI-RADS categories 1-5). The LI-RADS Management Working Group, consisting of internationally recognized medical and surgical experts on HCC management, as well as radiologists involved in the development of LI-RADS, was convened to evaluate management implications related to radiological categorization of the estimated probability that a lesion will be ultimately diagnosed as HCC. In this commentary, we briefly review LI-RADS and the initial consensus of the LI-RADS Management Working Group reached during its deliberations in 2013. We then focus on initial discordance of LI-RADS with American Association for the Study of Liver Diseases and Organ Procurement Transplant Network guidelines, the basis for these differences, and how they are being addressed going forward to optimize reporting of CT and MRI findings in patients at risk for HCC and to increase consensus throughout the international community of physicians involved in the diagnosis and treatment of HCC.

ObjectiveThe purpose of this article is to review the imaging features and Liver Imaging Reporting and Data System (LI-RADS) categorization of benign and likely benign entities, including typical cirrhotic nodules, distinctive nodular observations, and benign entities that may simulate hepatocellular carcinoma.ConclusionLI-RADS is a system of standardized criteria for interpreting liver CT and MR images of patients at risk of hepatocellular carcinoma. Most of the observations in these patients are not malignant. With the development of fibrosis and cirrhosis, these benign entities may take on an altered appearance.

Background: Focal nodular hyperplasia (FNH) and hepatic adenoma (HA) are two common benign liver lesions with different management options. In particular, resection is considered for large HA lesions to avoid possible bleeding complications or rarely malignant degeneration. Purpose: To determine whether early enhancement of a draining hepatic vein (EDHV) and absence of perilesional enhancement (PLE) on arterial phase MR images are useful for distinguishing FNH from HA. Study Type: Retrospective. Population: A total of 34 patients: 16 with FNH and 18 with HA lesions. Field Strength/Sequence: A1.5 T, axial T1 fat‐suppressed arterial postcontrast. Assesment: Four abdominal radiologists blinded to pathologic diagnosis assessed for the presence or absence of EDHV in association with the lesion, definitively characterized by pathology. This was considered present if contrast could be identified in a hepatic vein contiguous with the lesion in question. Secondarily, PLE was evaluated. Statistical Tests: Fleiss's multirater kappa statistic, Chi‐squared statistic, Phi‐coefficient. Significance level P < 0.05. Results: Considering all observations obtained from the four readers, an EDHV was identified with FNH 48.5% of the time. EDHV was seen with HA in 8.8% of cases. PLE was seen with significantly greater frequency in HA. The presence of an EDHV was associated with the absence of PLE. Data Conclusion: In a lesion that may be either an FNH or HA, confident identification on arterial phase images of an EDHV should lead the reader to favor FNH, while the presence PLE should dissuade the reader from FNH. Evidence Level: 4. Technical Efficacy: Stage 2. [ABSTRACT FROM AUTHOR]