Cynthia Santillan

MR imaging of liver fibrosis: current state of the art.

Chronic liver disease is a major public health problem worldwide. Liver fibrosis, a common feature of almost all causes of chronic liver disease, involves the accumulation of collagen, proteoglycans, and other macromolecules within the extracellular matrix. Fibrosis tends to progress, leading to hepatic dysfunction, portal hypertension, and ultimately cirrhosis. Liver biopsy, the standard of reference for diagnosing liver fibrosis, is invasive, costly, and subject to complications and sampling variability. These limitations make it unsuitable for diagnosis and longitudinal monitoring in the general population. Thus, development of a noninvasive, accurate, and reproducible test for diagnosis and monitoring of liver fibrosis would be of great value. Conventional cross-sectional imaging techniques have limited capability to demonstrate liver fibrosis. In clinical practice, imaging studies are usually reserved for evaluation of the presence of portal hypertension or hepatocellular carcinoma in cases that have progressed to cirrhosis. In response to the rising prevalence of chronic liver diseases in Western nations, a number of imaging-based methods including ultrasonography-based transient elastography, computed tomography-based texture analysis, and diverse magnetic resonance (MR) imaging-based techniques have been proposed for noninvasive diagnosis and grading of hepatic fibrosis across its entire spectrum of severity. State-of-the-art MR imaging-based techniques in current practice and in development for noninvasive assessment of liver fibrosis include conventional contrast material-enhanced MR imaging, double contrast-enhanced MR imaging, MR elastography, diffusion-weighted imaging, and MR perfusion imaging.

Magnetic resonance enterography is feasible and reliable in multicenter clinical trials in patients with Crohn's disease, and may help select subjects with active inflammation

Reliable tools for patient selection are critical for clinical drug trials.

Computed tomography of small bowel obstruction.

Multidetector computed tomography (CT) is a powerful tool for the assessment of patients with small bowel obstruction (SBO). CT can provide important information about the cause and site of obstruction and the presence of a closed-loop obstruction or ischemia. Under investigation is the ability of CT to accurately identify patients without clear indications for urgent surgery who may benefit from earlier intervention. This article reviews the appropriate CT technique for assessment of SBO, common causes for obstruction, imaging findings in SBO, and the significance of those findings for determining whether a patient is likely to require surgical management for SBO.

LI-RADS Categorization of Benign and Likely Benign Findings in Patients at Risk of Hepatocellular Carcinoma: A Pictorial Atlas

OBJECTIVE The 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. CONCLUSION LI-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.

Imaging Outcomes of Liver Imaging Reporting and Data System Version 2014 Category 2, 3, and 4 Observations Detected at CT and MR Imaging

Purpose To determine the proportion of untreated Liver Imaging Reporting and Data System (LI-RADS) version 2014 category 2, 3, and 4 observations that progress, remain stable, or decrease in category and to compare the cumulative incidence of progression in category. Materials and Methods In this retrospective, longitudinal, single-center, HIPAA-compliant, institutional review board-approved study, 157 patients (86 men and 71 women; mean age ± standard deviation, 59.0 years ± 9.7) underwent two or more multiphasic computed tomographic (CT) or magnetic resonance (MR) imaging examinations for hepatocellular carcinoma surveillance, with the first examination in 2011 or 2012. One radiologist reviewed baseline and follow-up CT and MR images (mean follow-up, 614 days). LI-RADS categories issued in the clinical reports by using version 1.0 or version 2013 were converted to version 2014 retrospectively; category modifications were verified with another radiologist. For index category LR-2, LR-3, and LR-4 observations, the proportions that progressed, remained stable, or decreased in category were calculated. Cumulative incidence curves for progression were compared according to baseline LI-RADS category (by using log-rank tests). Results All 63 index LR-2 observations remained stable or decreased in category. Among 166 index LR-3 observations, seven (4%) progressed to LR-5, and eight (5%) progressed to LR-4. Among 52 index LR-4 observations, 20 (38%) progressed to a malignant category. The cumulative incidence of progression to a malignant category was higher for index LR-4 observations than for index LR-3 or LR-2 observations (each P < .001) but was not different between LR-3 and LR-2 observations (P = .155). The cumulative incidence of progression to at least category LR-4 was trend-level higher for index LR-3 observations than for LR-2 observations (P = .0502). Conclusion Observations classified according to LI-RADS version 2014 categories are associated with different imaging outcomes. (©) RSNA, 2016 Online supplemental material is available for this article.

Understanding LI-RADS: a primer for practical use.

The Liver Imaging-Reporting and Data System (LI-RADS) is a comprehensive system for standardized interpretation and reporting of computed tomography and magnetic resonance examinations performed in patients at risk for hepatocellular carcinoma. LI-RADS includes a diagnostic algorithm, lexicon, and atlas as well as suggestions for reporting, management, and imaging techniques. This primer provides an introduction to LI-RADS for radiologists including an explanation of the diagnostic algorithm, descriptions of the categories, and definitions of the major imaging features used to categorize observations with case examples.

Cirrhotic liver: What's that nodule? The LI-RADS approach.

The Liver Imaging Reporting and Data System (LI‐RADS) is an American College of Radiology (ACR)‐endorsed diagnostic system of standardized terminology, interpretation, and reporting for imaging examinations of the liver in patients at high risk for hepatocellular carcinoma (HCC). LI‐RADS assigns a category to observations in the liver indicating the likelihood of benignity or HCC. LI‐RADS categories include LR‐1: Definitely Benign, LR‐2: Probably Benign, LR‐3: Intermediate Probability for HCC, LR‐4: Probably HCC, LR‐5: Definite HCC, LR‐5V: Definite HCC with Tumor in Vein, LR‐Treated: Treated HCC, LR‐M Probable Malignancy, not specific for HCC. This article reviews the types of nodules seen in the cirrhotic liver, examines core LI‐RADS concepts and definitions, and utilizes the LI‐RADS v2014 algorithm to categorize representative observations depicted at magnetic resonance imaging in a case‐based approach. J. Magn. Reson. Imaging 2016;43:281–294.

Cirrhotic Liver: What's That Nodule? The LI-RADS

The Liver Imaging Reporting and Data System (LI‐RADS) is an American College of Radiology (ACR)‐endorsed diagnostic system of standardized terminology, interpretation, and reporting for imaging examinations of the liver in patients at high risk for hepatocellular carcinoma (HCC). LI‐RADS assigns a category to observations in the liver indicating the likelihood of benignity or HCC. LI‐RADS categories include LR‐1: Definitely Benign, LR‐2: Probably Benign, LR‐3: Intermediate Probability for HCC, LR‐4: Probably HCC, LR‐5: Definite HCC, LR‐5V: Definite HCC with Tumor in Vein, LR‐Treated: Treated HCC, LR‐M Probable Malignancy, not specific for HCC. This article reviews the types of nodules seen in the cirrhotic liver, examines core LI‐RADS concepts and definitions, and utilizes the LI‐RADS v2014 algorithm to categorize representative observations depicted at magnetic resonance imaging in a case‐based approach. J. Magn. Reson. Imaging 2016;43:281–294.

LI-RADS major features: CT, MRI with extracellular agents, and MRI with hepatobiliary agents

The Liver Imaging Reporting and Data System (LI-RADS) was designed to standardize the interpretation and reporting of observations seen on studies performed in patients at risk for development of hepatocellular carcinoma (HCC). The LI-RADS algorithm guides radiologists through the process of categorizing observations on a spectrum from definitely benign to definitely HCC. Major features are the imaging features used to categorize observations as LI-RADS 3 (intermediate probability of malignancy), LIRADS 4 (probably HCC), and LI-RADS 5 (definite HCC). Major features include arterial phase hyperenhancement, washout appearance, enhancing capsule appearance, size, and threshold growth. Observations that have few major criteria are assigned lower categories than those that have several, with the goal of preserving high specificity for the LR-5 category of Definite HCC. The goal of this paper is to discuss LI-RADS major features, including definitions, rationale for selection as major features, and imaging examples.

Contrast Enhanced Ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS®): the official version by the American College of Radiology (ACR)

Author(s): Kono, Yuko; Lyshchik, Andrej; Cosgrove, David; Dietrich, Christoph F; Jang, Hyun-Jung; Kim, Tae Kyoung; Piscaglia, Fabio; Willmann, Juergen K; Wilson, Stephanie R; Santillan, Cynthia; Kambadakone, Avinash; Mitchell, Donald; Vezeridis, Alexander; Sirlin, Claude B