The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Magnetic resonance spectroscopy to measure hepatic triglyceride content: prevalence of hepatic steatosis in the general population
Abstract
Despite the increasing prevalence of nonalcoholic fatty liver disease (NAFLD), the criteria used to diagnose the disorder remain poorly defined. Localized proton magnetic resonance spectroscopy (MRS) accurately measures hepatic triglyceride content (HTGC) but has been used only in small research studies. Here, MRS was used to analyze the distribution of HTGC in 2,349 participants from the Dallas Heart Study (DHS). The reproducibility of the procedure was validated by showing that duplicate HTGC measurements were high correlated ( r = 0.99, P < 0.001) and that the coefficient of variation between measurements was low (8.5%). Intake of a high-fat meal did not significantly affect the measurements, and values were similar when measurements were made from the right and left hepatic lobes. To determine the “upper limit of normal” for HTGC, the distribution of HTGC was examined in the 345 subjects from the DHS who had no identifiable risk factors for hepatic steatosis (nonobese, nondiabetic subjects with minimal alcohol consumption, normal liver function tests, and no known liver disease). The 95th percentile of HTGC in these subjects was 5.56%, which corresponds to a hepatic triglyceride level of 55.6 mg/g. With this value as a cutoff, the prevalence of hepatic steatosis in Dallas County was estimated to be 33.6%. Thus MRS provides a sensitive, quantitative, noninvasive method to measure HTGC and, when applied to a large urban US population, revealed a strikingly high prevalence of hepatic steatosis.
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Cites
Nonalcoholic Fatty Liver Disease
Angulo, P. (2002) · New England Journal of Medicine · doi:10.1056/nejmra011775 · Cited by 5,228
Nonalcoholic fatty liver disease: a spectrum of clinical and pathological severity.
MATTEONI, C., YOUNOSSI, Z., GRAMLICH, T., BOPARAI, N., LIU, Y., & MCCULLOUGH, A. (1999) · Gastroenterology · doi:10.1016/s0016-5085(99)70506-8 · Cited by 3,345
Nonalcoholic Fatty Liver Disease
Marchesini, G., Brizi, M., Bianchi, G., Tomassetti, S., Bugianesi, E., Lenzi, M., McCullough, A. J., Natale, S., Forlani, G., & Melchionda, N. (2001) · Diabetes · doi:10.2337/diabetes.50.8.1844 · Cited by 2,581
Mayerson, A. B., Hundal, R. S., Dufour, S., Lebon, V., Befroy, D., Cline, G. W., Enocksson, S., Inzucchi, S. E., Shulman, G. I., & Petersen, K. F. (2002) · Diabetes · doi:10.2337/diabetes.51.3.797 · Cited by 647
Quantification of liver fat using magnetic resonance spectroscopy
Thomsen, C., Becker, U., Winkler, K., Christoffersen, P., Jensen, M., & Henriksen, O. (1994) · Magnetic Resonance Imaging · doi:10.1016/0730-725x(94)92543-7 · Cited by 332
Seppala-Lindroos, A. (2002) · Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.87.7.3023 · Cited by 168
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Rudovich, N. N., Weickert, M. O., Machann, J., & Pfeiffer, A. F. H. (2010) · Journal of Hepatology · doi:10.1016/j.jhep.2010.02.004 · Cited by 16
Liver triacylglycerol content and gestational diabetes: effects of moderate energy restriction
Hodson, K., Dalla Man, C., Smith, F. E., Barnes, A., McParlin, C., Cobelli, C., Robson, S. C., Araújo-Soares, V., & Taylor, R. (2017) · Diabetologia · doi:10.1007/s00125-016-4143-9 · Cited by 16
Willis, S. A., Malaikah, S., Bawden, S. J., Sherry, A. P., Sargeant, J. A., Coull, N. A., Bradley, C. R., Rowlands, A., Naim, I., Ennequin, G., et al. (2024) · Diabetes, Obesity and Metabolism · doi:10.1111/dom.15755 · Cited by 9
Zhyzhneuskaya, S. V., Al‐Mrabeh, A. H., Peters, C., Barnes, A. C., Hollingsworth, K. G., Welsh, P., Sattar, N., Lean, M. E. J., & Taylor, R. (2025) · Diabetic Medicine · doi:10.1111/dme.15462 · Cited by 6
Novel Antidiabetic Strategies and Diabetologists' Views in Nonalcoholic Steatohepatitis
Kahl, S., Pützer, J., & Roden, M. (2022) · Seminars in Liver Disease · doi:10.1055/s-0041-1732354 · Cited by 5
Metadata
- Authors
- Szczepaniak, L. S., Nurenberg, P., Leonard, D., Browning, J. D., Reingold, J. S., Grundy, S., Hobbs, H. H., & Dobbins, R. L.
- Venue
- American Journal of Physiology-Endocrinology and Metabolism
- Publisher
- American Physiological Society
- Published
- 2005-02
- Volume
- 288
- Issue
- 2
- Pages
- E462-E468
- ISSN
- 0193-1849 (ISSN-L)
- 1522-1555
- OpenAlex
- W2159469729
- Cited by
- 1,562
- References
- 6
- FWCI
- 21.38
- Type
- journal article
- Language
- en
- Open access
- closed
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