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Quantitative Abdominal Fat Estimation Using MRI
Linköping University, Department of Medicine and Care, Radio Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Health Sciences.
Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.ORCID iD: 0000-0002-7750-1917
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2008 (English)In: Proceedings - International Conference on Pattern Recognition, IEEE Computer Society, 2008, 1-4 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper introduces a new method for automaticquantification of subcutaneous, visceral and nonvisceralinternal fat from MR-images acquired usingthe two point Dixon technique in the abdominal region.The method includes (1) a three dimensionalphase unwrapping to provide water and fat images, (2)an image intensity inhomogeneity correction, and (3) amorphon based registration and segmentation of thetissue. This is followed by an integration of the correctedfat images within the different fat compartmentsthat avoids the partial volume effects associated withtraditional fat segmentation methods. The method wastested on 18 subjects before and after a period of fastfoodhyper-alimentation showing high stability andperformance in all analysis steps.

Place, publisher, year, edition, pages
IEEE Computer Society, 2008. 1-4 p.
Series
International Conference on Pattern Recognition, ISSN 1051-4651
National Category
Medical Laboratory and Measurements Technologies
Identifiers
URN: urn:nbn:se:liu:diva-21108DOI: 10.1109/ICPR.2008.4761764ISI: 000264729001041ISBN: 978-1-4244-2174-9 (print)ISBN: 978-1-4244-2175-6 (print)OAI: oai:DiVA.org:liu-21108DiVA: diva2:240618
Conference
19th International Conference on Pattern Recognition, Tampa FL USA, 8-11 Dec. 2008
Available from: 2009-09-29 Created: 2009-09-29 Last updated: 2015-10-09Bibliographically approved
In thesis
1. Quantitative Magnetic Resonance in Diffuse Neurological and Liver Disease
Open this publication in new window or tab >>Quantitative Magnetic Resonance in Diffuse Neurological and Liver Disease
2010 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Introduction: Magnetic resonance (MR) imaging is one of the most important diagnostic tools in modern medicine. Compared to other imaging modalities, it provides superior soft tissue contrast of all parts of the body and it is considered to be safe for patients. Today almost all MR is performed in a nonquantitative manner, only comparing neighboring tissue in the search for pathology. It is possible to quantify MR-signals and relate them to their physical entities, but time consuming and complicated calibration procedures have prevented this being used in a practical manner for clinical routines. The aim of this work is to develop and improve quantification methods in MRspectroscopy (MRS) and MR-imaging (MRI). The techniques are intended to be applied to diffuse diseases, where conventional imaging methods are unable to perform accurate staging or to reveal metabolic changes associated with disease development.

Methods: Proton (1H) MRS was used to characterize the white matter in the brain of multiple sclerosis (MS) patients. Phosphorus (31P) MRS was used to evaluate the energy metabolism in patients with diffuse liver disease. A new quantitative MRI (qMRI) method was invented for accurate, rapid and simultaneous quantification of B1, T1, T2, and proton density. A method for automatic assessment of visceral adipose tissue volume based on an in- and out-ofphase imaging protocol was developed. Finally, a method for quantification of the hepatobiliary uptake of liver specific T1 enhancing contrast agents was demonstrated on healthy subjects.

Results: The 1H MRS investigations of white matter in MS-patients revealed a significant correlation between tissue concentrations of Glutamate and Creatine on the one hand and the disease progression rate on the other, as measured using the MSSS. High accuracy, both in vitro and in vivo, of the measured MR-parameters from the qMRI method was observed. 31P MRS showed lower concentrations of phosphodiesters, and a higher metabolic charge in patients with cirrhosis, compared to patients with mild fibrosis and to controls. The adipose tissue quantification method agreed with estimates obtained using manual segmentation, and enabled measurements which were insensitive to partial volume effects. The hepatobiliary uptake of Gd-EOB-DTPA and Gd-BOPTA was significantly correlated in healthy subjects.

Conclusion: In this work, new methods for accurate quantification of MR parameters in diffuse diseases in the liver and the brain were demonstrated. Several applications were shown where quantitative MR improves the interpretation of observed signal changes in MRI and MRS in relation to underlying differences in physiology and pathophysiology.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2010. 127 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1184
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:liu:diva-54728 (URN)978-91-7393-390-2 (ISBN)
Public defence
2010-04-29, Elsa Brändströmsalen, Campus US, Linköpings universitet, Linköping, 13:15 (English)
Opponent
Supervisors
Available from: 2010-04-07 Created: 2010-04-07 Last updated: 2017-01-31Bibliographically approved

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Leinhard, Olof DahlqvistRydell, JoakimSmedby, ÖrjanNystöm, FredrikLundberg, PeterBorga, Magnus

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Leinhard, Olof DahlqvistRydell, JoakimSmedby, ÖrjanNystöm, FredrikLundberg, PeterBorga, Magnus
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Radio PhysicsCenter for Medical Image Science and Visualization (CMIV)Faculty of Health SciencesRadiation PhysicsMedical InformaticsThe Institute of TechnologyRadiologyDepartment of Radiology in LinköpingInternal MedicineDepartment of Endocrinology and Gastroenterology UHLDepartment of Radiation Physics
Medical Laboratory and Measurements Technologies

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