The DOI matches its Crossref record; 118 of the 118 references it cites were found in a registry or an index.
Quantification of Liver Fat Content with CT and MRI: State of the Art
Open accessAbstract
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.
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“MRI can be used to quantify the triglyceride content (usually expressed as proton density fat fraction [PDFF]) in the liver and is the non-invasive gold standard for hepatic lipid quanti fi cation in MASLD.”
From EASL-EASD-EASO Clinical Practice Guidelines on the management of metabolic dysfunction-associated steatotic liver disease (MASLD). (2024) · cites this paper as [162]
In the citing paper
“While CT scans obtained in clinical routine (usually performed for other purposes) can provide a rough estimate of liver steatosis and thereby suggest SLD, 162 this method is not suitable for proper assessment of steatosis.”
From EASL-EASD-EASO Clinical Practice Guidelines on the management of metabolic dysfunction-associated steatotic liver disease (MASLD). (2024) · cites this paper as [162]
Citations
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Cited by
Sorted by citations
Tacke, F., Horn, P., Wai-Sun Wong, V., Ratziu, V., Bugianesi, E., Francque, S., Zelber-Sagi, S., Valenti, L., Roden, M., Schick, F., et al. (2024) · Journal of Hepatology · doi:10.1016/j.jhep.2024.04.031 · Cited by 2,210
(2024) · Obesity Facts · doi:10.1159/000539371 · Cited by 545
Value-added Opportunistic CT Screening: State of the Art
Pickhardt, P. J. (2022) · Radiology · doi:10.1148/radiol.211561 · Cited by 266
Fast and Low-GPU-memory abdomen CT organ segmentation: The FLARE challenge
Ma, J., Zhang, Y., Gu, S., An, X., Wang, Z., Ge, C., Wang, C., Zhang, F., Wang, Y., Xu, Y., et al. (2022) · Medical Image Analysis · doi:10.1016/j.media.2022.102616 · Cited by 182
Opportunistic Screening: Radiology Scientific Expert Panel
Pickhardt, P. J., Summers, R. M., Garrett, J. W., Krishnaraj, A., Agarwal, S., Dreyer, K. J., & Nicola, G. N. (2023) · Radiology · doi:10.1148/radiol.222044 · Cited by 134
Metadata
- Authors
- Starekova, J., Hernando, D., Pickhardt, P. J., & Reeder, S. B.
- Affiliations
- University of Wisconsin–Madison (US)
- Venue
- Radiology
- Published
- 2021-11
- Volume
- 301
- Issue
- 2
- Pages
- 250-262
- ISSN
- 0033-8419 (ISSN-L)
- 1527-1315
- PMC
- PMC8574059
- OpenAlex
- W3199340922
- Cited by
- 320
- References
- 117
- Citations by year
- 2026: 86 · 2025: 96 · 2024: 69 · 2023: 46 · 2022: 22 · 2021: 1
- FWCI
- 5.32
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Radiology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health contsponsor (R01 DK088925, R01 DK100651, R44-EB025729, R01-DK117354)
- Topics
- Health Sciences › Medicine › Hepatology › Liver Disease Diagnosis and Treatment
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
- Keywords
- hepatic steatosis, liver fat quantification, non-alcoholic fatty liver disease, chemical shift MRI, non-invasive imaging, cardiovascular risk, metabolic syndrome, type 2 diabetes, artificial intelligence, treatment monitoring
- MeSH terms
- Fatty Liver, Humans, Liver, Magnetic Resonance Imaging, Tomography, X-Ray Computed, Reproducibility of Results
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