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A randomized trial of cold-exposure on energy expenditure and supraclavicular brown adipose tissue volume in humans
Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Medicine and Health Sciences.
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Medicine and Health Sciences.
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2016 (English)In: Metabolism: Clinical and Experimental, ISSN 0026-0495, E-ISSN 1532-8600, Vol. 65, no 6, p. 926-934Article in journal (Refereed) Published
Abstract [en]

Objective

To study if repeated cold-exposure increases metabolic rate and/or brown adipose tissue (BAT) volume in humans when compared with avoiding to freeze.

Design

Randomized, open, parallel-group trial.

Methods

Healthy non-selected participants were randomized to achieve cold-exposure 1 hour/day, or to avoid any sense of feeling cold, for 6 weeks. Metabolic rate (MR) was measured by indirect calorimetry before and after acute cold-exposure with cold vests and ingestion of cold water. The BAT volumes in the supraclavicular region were measured with magnetic resonance imaging (MRI).

Results

Twenty-eight participants were recruited, 12 were allocated to controls and 16 to cold-exposure. Two participants in the cold group dropped out and one was excluded. Both the non-stimulated and the cold-stimulated MR were lowered within the group randomized to avoid cold (MR at room temperature from 1841 ± 199 kCal/24 h to 1795 ± 213 kCal/24 h, p = 0.047 cold-activated MR from 1900 ± 150 kCal/24 h to 1793 ± 215 kCal/24 h, p = 0.028). There was a trend towards increased MR at room temperature following the intervention in the cold-group (p = 0.052). The difference between MR changes by the interventions between groups was statistically significant (p = 0.008 at room temperature, p = 0.032 after cold-activation). In an on-treatment analysis after exclusion of two participants that reported ≥ 8 days without cold-exposure, supraclavicular BAT volume had increased in the cold-exposure group (from 0.0175 ± 0.015 l to 0.0216 ± 0.014 l, p = 0.049).

Conclusions

We found evidence for plasticity in metabolic rate by avoiding to freeze compared with cold-exposure in a randomized setting in non-selected humans.

Place, publisher, year, edition, pages
Elsevier, 2016. Vol. 65, no 6, p. 926-934
Keyword [en]
Brown adipose tissue; Cold exposure; Magnetic resonance imaging; Metabolic rate
National Category
Pharmacology and Toxicology
Identifiers
URN: urn:nbn:se:liu:diva-128200DOI: 10.1016/j.metabol.2016.03.012ISI: 000376145100013PubMedID: 27173471OAI: oai:DiVA.org:liu-128200DiVA, id: diva2:930096
Funder
Knut and Alice Wallenberg Foundation
Note

Funding agencies: Linkoping University; County Council of Ostergotland (LUA-ALF), Sweden; Swedish Research Council [2013-4466, 2012-1652, 2014-2516]; Knut and Alice Wallenberg Foundation; Sahlgrenskas University Hospital (LUA-ALF); European Union grant (DIABAT) [HEALTH-F2-

Available from: 2016-05-22 Created: 2016-05-22 Last updated: 2018-03-22
In thesis
1. Fat-Referenced MRI: Quanitaive MRI for Tissue Characterizaion and Volume Measurement
Open this publication in new window or tab >>Fat-Referenced MRI: Quanitaive MRI for Tissue Characterizaion and Volume Measurement
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The amount and distribution of adipose and lean tissues has been shown to be predictive of mortality and morbidity in metabolic disease. Traditionally these risks are assessed by anthropometric measurements based on weight, length, girths or the body mass index (BMI). These measurements are predictive of risks on a population level, where a too low or a too high BMI indicates an increased risk of both mortality and morbidity. However, today a large part of the world’s population belongs to a group with an elevated risk according to BMI, many of which will live long and healthy lives. Thus, better instruments are needed to properly direct health-care resources to those who need it the most.

Medical imaging method can go beyond anthropometrics. Tomographic modalities, such as magnetic resonance imaging (MRI), can measure how we have stored fat in and around organs. These measurements can eventually lead to better individual risk predictions. For instance, a tendency to store fat as visceral adipose tissue (VAT) is associated with an increased risk of diabetes type 2, cardio-vascular disease, liver disease and certain types of cancer. Furthermore, liver fat is associated with liver disease, diabetes type 2. Brown adipose tissue (BAT), is another emerging component of body-composition analysis. While the normal white adipose tissue stores fat, BAT burns energy to produce heat. This unique property makes BAT highly interesting, from a metabolic point of view.

Magnetic resonance imaging can both accurately and safely measure internal adipose tissue compartments, and the fat infiltration of organs. Which is why MRI is often considered the reference method for non-invasive body-composition analysis. The two major challenges of MRI based body-composition analysis are, the between-scanner reproducibility and a cost-effective analysis of the images. This thesis presents a complete implementation of fat-referenced MRI, a technique that produces quantitative images that can increase both inter-scanner and automation of the image analysis.

With MRI, it is possible to construct images where water and fat are separated into paired images. In these images, it easy to depict adipose tissue and lean tissue structures. This thesis takes water-fat MRI one step further, by introducing a quantitative framework called fat-referenced MRI. By calibrating the image using the subjects' own adipose tissue (paper II), the otherwise non-quantitative fat images are made quantitative. In these fat-referenced images it is possible to directly measure the amount of adipose tissue in different compartments. This quantitative property makes image analysis easy and accurate, as lean and adipose tissues can be separated on a sub-voxel level. Fat-referenced MRI further allows the quantification and characterization of BAT.

This thesis work starts by formulating a method to produce water-fat images (paper I) based on two gradient recall images, i.e.\ 2-point Dixon images (2PD). It furthers shows that fat-referenced 2PD images can be corrected for T2*, making the 2PD body-composition measurements comparable with confounder-corrected Dixon measurements (paper III}).

Both the water-fat separation method and fat image calibration are applied to BAT imaging. The methodology is first evaluated in an animal model, where it is shown that it can detect both BAT browning and volume increase following cold acclimatization (paper IV). It is then applied to postmortem imaging, were it is used to locate interscapular BAT in human infants (paper V). Subsequent analysis of biopsies, taken based on the MRI images, showed that the interscapular BAT was of a type not previously believed to exist in humans. In the last study, fat-referenced MRI is applied to BAT imaging of adults. As BAT structures are difficult to locate in many adults, the methodology was also extended with a multi-atlas segmentation methods (paper VI).

In summary, this thesis shows that fat-referenced MRI is a quantitative method that can be used for body-composition analysis. It also shows that fat-referenced MRI can produce quantitative high-resolution images, a necessity for many BAT applications.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2018. p. 85
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1910
Keyword
MRI, water-fat separation, quantitative MRI
National Category
Medical Image Processing
Identifiers
urn:nbn:se:liu:diva-145316 (URN)10.3384/diss.diva-145316 (DOI)9789176853511 (ISBN)
Public defence
2018-03-21, Grantisalen, Campus US, Linköping, 09:15 (English)
Opponent
Supervisors
Note

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Available from: 2018-02-27 Created: 2018-02-22 Last updated: 2018-02-28Bibliographically approved

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Romu, ThobiasDahlqvist Leinhard, OlofDahlström, NilsPersson, AndersBorga, MagnusNyström, Fredrik

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Medical InformaticsFaculty of Science & EngineeringCenter for Medical Image Science and Visualization (CMIV)Department of Medical and Health SciencesFaculty of Medicine and Health SciencesDivision of Radiological SciencesDepartment of Radiation PhysicsDepartment of Radiology in LinköpingThe Institute of TechnologyDivision of Cardiovascular MedicineDepartment of Endocrinology
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