{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T00:05:47Z","timestamp":1788998747363,"version":"build-2803163510"},"reference-count":133,"publisher":"Oxford University Press (OUP)","issue":"1089","license":[{"start":{"date-parts":[[2017,11,1]],"date-time":"2017-11-01T00:00:00Z","timestamp":1509494400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,11,1]]},"abstract":"<jats:p>Adipose cells have traditionally been viewed as a simple, passive energy storage depot for triglycerides. However, in recent years it has become clear that adipose cells are highly physiologically active and have a multitude of endocrine, metabolic, haematological and immune functions. Changes in the number or size of adipose cells may be directly implicated in disease (e.g. in the metabolic syndrome), but may also be linked to other pathological processes such as inflammation, malignant infiltration or infarction. MRI is ideally suited to the quantification of fat, since most of the acquired signal comes from water and fat protons. Fat fraction (FF, the proportion of the acquired signal derived from fat protons) has, therefore, emerged as an objective, image-based biomarker of disease. Methods for FF quantification are becoming increasingly available in both research and clinical settings, but these methods vary depending on the scanner, manufacturer, imaging sequence and reconstruction software being used. Careful selection of the imaging method\u2014and correct interpretation\u2014can improve the accuracy of FF measurements, minimize potential confounding factors and maximize clinical utility. Here, we review methods for fat quantification and their strengths and weaknesses, before considering how they can be tailored to specific applications, particularly in the gastrointestinal and musculoskeletal systems. FF quantification is becoming established as a clinical and research tool, and understanding the underlying principles will be helpful to both imaging scientists and clinicians.<\/jats:p>","DOI":"10.1259\/bjr.20170344","type":"journal-article","created":{"date-parts":[[2017,9,22]],"date-time":"2017-09-22T07:38:40Z","timestamp":1506065920000},"source":"Crossref","is-referenced-by-count":92,"title":["Fat fraction mapping using magnetic resonance imaging: insight into pathophysiology"],"prefix":"10.1093","volume":"91","author":[{"given":"Timothy JP","family":"Bray","sequence":"first","affiliation":[{"name":"Centre for Medical Imaging, University College London , , London , UK"},{"name":"University College London , , London , UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Manil D","family":"Chouhan","sequence":"additional","affiliation":[{"name":"Centre for Medical Imaging, University College London , , London , UK"},{"name":"University College London , , London , UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shonit","family":"Punwani","sequence":"additional","affiliation":[{"name":"Centre for Medical Imaging, University College London , , London , UK"},{"name":"University College London , , London , UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alan","family":"Bainbridge","sequence":"additional","affiliation":[{"name":"Department of Medical Physics, University College London Hospitals , , London , UK"},{"name":"University College London Hospitals , , London , UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Margaret A","family":"Hall-Craggs","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2017,11,21]]},"reference":[{"key":"2024050214341487700_b1","doi-asserted-by":"crossref","first-page":"191","DOI":"10.5114\/aoms.2013.33181","article-title":"Biochemistry of adipose tissue: an endocrine organ","volume":"9","author":"Coelho","year":"2013","journal-title":"Arch Med Sci"},{"key":"2024050214341487700_b2","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1038\/372425a0","article-title":"Positional cloning of the mouse obese gene and its human homologue","volume":"372","author":"Zhang","year":"1994","journal-title":"Nature"},{"key":"2024050214341487700_b3","doi-asserted-by":"crossref","first-page":"2917","DOI":"10.1016\/j.febslet.2006.04.028","article-title":"The metabolic syndrome and adipocytokines","volume":"580","author":"Matsuzawa","year":"2006","journal-title":"FEBS Lett"},{"key":"2024050214341487700_b4","doi-asserted-by":"crossref","first-page":"431","DOI":"10.5114\/aoms.2012.29518","article-title":"Serum concentrations of adiponectin, leptin, resistin, ghrelin and insulin and their association with obesity indices in obese normo- and hypertensive patients - pilot study","volume":"8","author":"St\u0119pie\u0144","year":"2012","journal-title":"Arch Med Sci"},{"key":"2024050214341487700_b5","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1038\/nm1166","article-title":"Local and systemic insulin resistance resulting from hepatic activation of IKK-\u03b2 and NF-\u03baB","volume":"11","author":"Cai","year":"2005","journal-title":"Nat Med"},{"key":"2024050214341487700_b6","doi-asserted-by":"crossref","first-page":"1253","DOI":"10.1194\/jlr.R700005-JLR200","article-title":"Thematic review series: adipocyte biology. 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