Multiparametric quantification and visualization of liver fat using ultrasound

Objectives- Several ultrasound measures have shown promise for assessment of steatosis compared to traditional B-scan, however clinicians may be required to integrate information across the parameters. Here, we propose an integrated multiparametric approach, enabling simple clinical assessment of key information from combined ultrasound parameters. Methods- We have measured 13 parameters related to ultrasound and shear wave elastography. These were measured in 30 human subjects under a study of liver fat. The 13 individual measures are assessed for their predictive value using independent magnetic resonance imaging-derived proton density fat fraction (MRI-PDFF) measurements as a reference standard. In addition, a comprehensive and fine-grain analysis is made of all possible combinations of sub-sets of these parameters to determine if any subset can be efficiently combined to predict fat fraction. Results- We found that as few as four key parameters related to ultrasound propagation are sufficient to generate a linear multiparametric parameter with a correlation against MRI-PDFF values of greater than 0.93. This optimal combination was found to have a classification area under the curve (AUC) approaching 1.0 when applying a threshold for separating steatosis grade zero from higher classes. Furthermore, a strategy is developed for applying local estimates of fat content as a color overlay to produce a visual impression of the extent and distribution of fat within the liver. Conclusion- In principle, this approach can be applied to most clinical ultrasound systems to provide the clinician and patient with a rapid and inexpensive estimate of liver fat content

Sonographic Evaluation for Endometrial Polyps

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135550/1/jum201635112381.pd

Liver imaging : it is time to adopt standardized terminology

Liver imaging plays a vital role in the management of patients at risk for hepatocellular carcinoma (HCC); however, progress in the field is challenged by nonuniform and inconsistent terminology in the published literature. The Steering Committee of the American College of Radiology (ACR)’s Liver Imaging Reporting And Data System (LI-RADS), in conjunction with the LI-RADS Lexicon Writing Group and the LI-RADS International Working Group, present this consensus document to establish a single universal liver imaging lexicon. The lexicon is intended for use in research, education, and clinical care of patients at risk for HCC (i.e., the LI-RADS population) and in the general population (i.e., even when LI-RADS algorithms are not applicable). We anticipate that the universal adoption of this lexicon will provide research, educational, and clinical benefits

LI-RADS: A Conceptual and Historical Review from Its Beginning to Its Recent Integration into AASLD Clinical Practice Guidance

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

Radiology Case Reports Relapsed Extramedullary Multiple Myeloma Presenting as Bilateral Solid Perirenal Masses

We present a patient with IgA myeloma who responded well to chemo-radiation therapy. The patient subsequently underwent autologous followed by nonmyeloablative allogenic bone marrow transplant and relapsed after six years in an unusual manner with extensive extramedullary disease with bilateral perirenal involvement. The highly variable expression of myeloma at relapse highlights the importance of individualized follow-up and periodic imaging for early detection of relapse

Characterization of a Linear Streak Artifact With Pulse Inversion Tissue Harmonics in Musculoskeletal Sonography

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135256/1/jum200423121597.pd

Epidemiology of hepatocellular carcinoma: target population for surveillance and diagnosis.

Hepatocellular carcinoma (HCC) is the sixth most common cancer and the second leading cause of cancer mortality worldwide. Incidence rates of liver cancer vary widely between geographic regions and are highest in Eastern Asia and sub-Saharan Africa. In the United States, the incidence of HCC has increased since the 1980s. HCC detection at an early stage through surveillance and curative therapy has considerably improved the 5-year survival. Therefore, medical societies advocate systematic screening and surveillance of target populations at particularly high risk for developing HCC to facilitate early-stage detection. Risk factors for HCC include cirrhosis, chronic infection with hepatitis B virus (HBV), hepatitis C virus (HCV), excess alcohol consumption, non-alcoholic fatty liver disease, family history of HCC, obesity, type 2 diabetes mellitus, and smoking. Medical societies utilize risk estimates to define target patient populations in which imaging surveillance is recommended (risk above threshold) or in which the benefits of surveillance are uncertain (risk unknown or below threshold). All medical societies currently recommend screening and surveillance in patients with cirrhosis and subsets of patients with chronic HBV; some societies also include patients with stage 3 fibrosis due to HCV as well as additional groups. Thus, target population definitions vary between regions, reflecting cultural, demographic, economic, healthcare priority, and biological differences. The Liver Imaging Reporting and Data System (LI-RADS) defines different patient populations for surveillance and for diagnosis and staging. We also discuss general trends pertaining to geographic region, age, gender, ethnicity, impact of surveillance on survival, mortality, and future trends

Epidemiology of hepatocellular carcinoma: target population for surveillance and diagnosis.

Hepatocellular carcinoma (HCC) is the sixth most common cancer and the second leading cause of cancer mortality worldwide. Incidence rates of liver cancer vary widely between geographic regions and are highest in Eastern Asia and sub-Saharan Africa. In the United States, the incidence of HCC has increased since the 1980s. HCC detection at an early stage through surveillance and curative therapy has considerably improved the 5-year survival. Therefore, medical societies advocate systematic screening and surveillance of target populations at particularly high risk for developing HCC to facilitate early-stage detection. Risk factors for HCC include cirrhosis, chronic infection with hepatitis B virus (HBV), hepatitis C virus (HCV), excess alcohol consumption, non-alcoholic fatty liver disease, family history of HCC, obesity, type 2 diabetes mellitus, and smoking. Medical societies utilize risk estimates to define target patient populations in which imaging surveillance is recommended (risk above threshold) or in which the benefits of surveillance are uncertain (risk unknown or below threshold). All medical societies currently recommend screening and surveillance in patients with cirrhosis and subsets of patients with chronic HBV; some societies also include patients with stage 3 fibrosis due to HCV as well as additional groups. Thus, target population definitions vary between regions, reflecting cultural, demographic, economic, healthcare priority, and biological differences. The Liver Imaging Reporting and Data System (LI-RADS) defines different patient populations for surveillance and for diagnosis and staging. We also discuss general trends pertaining to geographic region, age, gender, ethnicity, impact of surveillance on survival, mortality, and future trends