Characterization of Brown Adipose Tissue by water-fat separated Magnetic Resonance Imaging
2015 (English)In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 42, no 6, 1639-1645 p.Article in journal (Refereed) Published
Purpose: To evaluate the possibility of quantifying brown adipose tissue (BAT) volume and fat concentration with a high resolution, long TE, dual-echo Dixon imaging protocol.
Materials and methods: A 0.42 mm isotropic resolution water-fat separated MRI protocol was implemented by utilizing the second opposite-phase echo and third in-phase echo. Fat images were calibrated with regard to the intensity of nearby white adipose tissue (WAT) to form relative fat content (RFC) images. To evaluate the ability to measure BAT volume and RFC contrast dynamics, rats were divided into two groups that were kept at 4° or 22° C for five days. The rats were then scanned in a 70 cm bore 3.0 T MRI scanner and a human dual energy CT. Interscapular, paraaortal and perirenal BAT (i/pa/pr-BAT) depots as well as WAT and muscle were segmented in the MRI and CT images. Biopsies were collected from the identified BAT depots.
Results: The biopsies confirmed that the three depots identified with the RFC images consisted of BAT. There was a significant linear correlation (p <0.001) between the measured RFC and the Hounsfield units from DECT. Significantly lower iBAT RFC (p = 0.0064) and significantly larger iBAT and prBAT volumes (p=0.0017) were observed in the cold stimulated rats.
Conclusions: The calibrated Dixon images with RFC scaling can depict BAT and be used to measure differences in volume, and fat concentration, induced by cold stimulation. The high correlation between RFC and HU suggests that the fat concentration is the main RFC image contrast mechanism.
Place, publisher, year, edition, pages
John Wiley & Sons, 2015. Vol. 42, no 6, 1639-1645 p.
Brown Adipose Tissue; BAT; Fat Water MRI
Medical Image Processing Radiology, Nuclear Medicine and Medical Imaging
IdentifiersURN: urn:nbn:se:liu:diva-116931DOI: 10.1002/jmri.24931ISI: 000368258100020OAI: oai:DiVA.org:liu-116931DiVA: diva2:801651
FunderKnowledge Foundation, 2011.0059