Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 271

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Fatty Liver Disease: MR Imaging Techniques for the Detection and Quantification of Liver Steatosis

Cassidy, Fiona Hughes, Yokoo, Takeshi, Aganovic, Lejla, Hanna, Robert F., Bydder, Mark, Middleton, Michael S., Hamilton, Gavin, Chavez, Alyssa D., Schwimmer, Jeffrey B., Sirlin, Claude B.·2009·RadioGraphics

Abstract

Fatty liver disease is the most common cause of chronic liver disease in the United States. Noninvasive detection and quantification of fat is becoming more and more important clinically, due in large part to the growing prevalence of nonalcoholic fatty liver disease. Steatosis, the accumulation of fat-containing vacuoles within hepatocytes, is a key histologic feature of fatty liver disease. Liver biopsy, the current standard of reference for the assessment of steatosis, is invasive, has sampling errors, and is not appropriate in some settings. Several magnetic resonance (MR) imaging-based techniques--including chemical shift imaging, frequency-selective imaging, and MR spectroscopy--are currently in clinical use for the detection and quantification of fat-water admixtures, with each technique having important advantages, disadvantages, and limitations. These techniques permit the breakdown of the net MR signal into fat and water signal components, allowing the quantification of fat in liver tissue, and are increasingly being used in the diagnosis, treatment, and follow-up of fatty liver disease.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1148/rg.291075123

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 3 references

Cited by

See all 271

Metadata

Authors
Cassidy, F. H., Yokoo, T., Aganovic, L., Hanna, R. F., Bydder, M., Middleton, M. S., Hamilton, G., Chavez, A. D., Schwimmer, J. B., & Sirlin, C. B.
Venue
RadioGraphics
Published
2009-01
Volume
29
Issue
1
Pages
231-260
ISSN
  • 0271-5333 (ISSN-L)
  • 1527-1323
OpenAlex
W2148948654
Cited by
271
References
3
FWCI
14.81
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Fatty Liver Disease: MR Imaging Techniques for the Detection and Quantification of Liver Steatosis. https://app.cochat.ai/papers/10.1148/rg.291075123
The paper
Cassidy, F. H., Yokoo, T., Aganovic, L., Hanna, R. F., Bydder, M., Middleton, M. S., Hamilton, G., Chavez, A. D., Schwimmer, J. B., & Sirlin, C. B. (2009). Fatty Liver Disease: MR Imaging Techniques for the Detection and Quantification of Liver Steatosis. RadioGraphics. https://doi.org/10.1148/rg.291075123

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.