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Quantitative Abdominal Fat Estimation Using MRI
Linköpings universitet, Institutionen för medicin och vård, Radiofysik. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Hälsouniversitetet.ORCID-id: 0000-0002-6189-0807
Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiofysik. Linköpings universitet, Hälsouniversitetet.
Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Bildmedicinskt centrum, Röntgenkliniken i Linköping.ORCID-id: 0000-0002-7750-1917
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2008 (Engelska)Ingår i: Proceedings - International Conference on Pattern Recognition, IEEE Computer Society, 2008, s. 1-4Konferensbidrag, Publicerat paper (Refereegranskat)
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.

Ort, förlag, år, upplaga, sidor
IEEE Computer Society, 2008. s. 1-4
Serie
International Conference on Pattern Recognition, ISSN 1051-4651
Nationell ämneskategori
Medicinsk laboratorie- och mätteknik
Identifikatorer
URN: urn:nbn:se:liu:diva-21108DOI: 10.1109/ICPR.2008.4761764ISI: 000264729001041ISBN: 978-1-4244-2174-9 (tryckt)ISBN: 978-1-4244-2175-6 (tryckt)OAI: oai:DiVA.org:liu-21108DiVA, id: diva2:240618
Konferens
19th International Conference on Pattern Recognition, Tampa FL USA, 8-11 Dec. 2008
Tillgänglig från: 2009-09-29 Skapad: 2009-09-29 Senast uppdaterad: 2019-06-14Bibliografiskt granskad
Ingår i avhandling
1. Quantitative Magnetic Resonance in Diffuse Neurological and Liver Disease
Öppna denna publikation i ny flik eller fönster >>Quantitative Magnetic Resonance in Diffuse Neurological and Liver Disease
2010 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
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.

Ort, förlag, år, upplaga, sidor
Linköping: Linköping University Electronic Press, 2010. s. 127
Serie
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1184
Nationell ämneskategori
Radiologi och bildbehandling
Identifikatorer
urn:nbn:se:liu:diva-54728 (URN)978-91-7393-390-2 (ISBN)
Disputation
2010-04-29, Elsa Brändströmsalen, Campus US, Linköpings universitet, Linköping, 13:15 (Engelska)
Opponent
Handledare
Tillgänglig från: 2010-04-07 Skapad: 2010-04-07 Senast uppdaterad: 2019-06-14Bibliografiskt granskad

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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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RadiofysikCentrum för medicinsk bildvetenskap och visualisering, CMIVHälsouniversitetetMedicinsk radiofysikMedicinsk informatikTekniska högskolanMedicinsk radiologiRöntgenkliniken i LinköpingInternmedicinEndokrin- och magtarmmedicinska kliniken USRadiofysikavdelningen
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