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Quantification of Liver Fat Content with CT and MRI: State of the Art
- Source :
- Radiology
- Publication Year :
- 2021
-
Abstract
- Hepatic steatosis is defined as pathologically elevated liver fat content and has many underlying causes. Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide, with an increasing prevalence among adults and children. Abnormal liver fat accumulation has serious consequences, including cirrhosis, liver failure, and hepatocellular carcinoma. In addition, hepatic steatosis is increasingly recognized as an independent risk factor for the metabolic syndrome, type 2 diabetes, and, most important, cardiovascular mortality. During the past 2 decades, noninvasive imaging-based methods for the evaluation of hepatic steatosis have been developed and disseminated. Chemical shift–encoded MRI is now established as the most accurate and precise method for liver fat quantification. CT is important for the detection and quantification of incidental steatosis and may play an increasingly prominent role in risk stratification, particularly with the emergence of CT-based screening and artificial intelligence. Quantitative imaging methods are increasingly used for diagnostic work-up and management of steatosis, including treatment monitoring. The purpose of this state-of-the-art review is to provide an overview of recent progress and current state of the art for liver fat quantification using CT and MRI, as well as important practical considerations related to clinical implementation. © RSNA, 2021 Online supplemental material is available for this article.
- Subjects :
- medicine.medical_specialty
Cirrhosis
business.industry
Reproducibility of Results
Type 2 diabetes
Chronic liver disease
medicine.disease
Gastroenterology
Magnetic Resonance Imaging
Fatty Liver
Reviews and Commentary
Liver
Hepatocellular carcinoma
Internal medicine
Nonalcoholic fatty liver disease
medicine
Humans
Radiology, Nuclear Medicine and imaging
Steatosis
Metabolic syndrome
Risk factor
business
Tomography, X-Ray Computed
Subjects
Details
- ISSN :
- 15271315
- Volume :
- 301
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- Radiology
- Accession number :
- edsair.doi.dedup.....d0b472fa2b1c60153b23825f2cd83335