Methods for automatic analysis of glucose uptake in adipose tissue using quantitative PET/MRI data
Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Brown adipose tissue (BAT) is the main tissue involved in non-shivering heat production. A greater understanding of BAT could possibly lead to new ways of prevention and treatment of obesity and type 2 diabetes. The increasing prevalence of these conditions and the problems they cause society and individuals make the study of the subject important.
An ongoing study performed at the Turku University Hospital uses images acquired using PET/MRI with 18F-FDG as the tracer. Scans are performed on sedentary and athlete subjects during normal room temperature and during cold stimulation. Sedentary subjects then undergo scanning during cold stimulation again after a six weeks long exercise training intervention. This degree project used images from this study.
The objective of this degree project was to examine methods to automatically and objectively quantify parameters relevant for activation of BAT in combined PET/MRI data. A secondary goal was to create images showing glucose uptake changes in subjects from images taken at different times.
Parameters were quantified in adipose tissue directly without registration (image matching), and for neck scans also after registration. Results for the first three subjects who have completed the study are presented. Larger registration errors were encountered near moving organs and in regions with less information.
The creation of images showing changes in glucose uptake seem to be working well for the neck scans, and somewhat well for other sub-volumes. These images can be useful for identification of BAT. Examples of these images are shown in the report.
Place, publisher, year, edition, pages
2014. , 27 p.
UPTEC F, ISSN 1401-5757 ; 14044
brown adipose tissue, medical images, image registration, BAT, PET, MRI
brunt fett, medicinska bilder, bildregistrering, BAT, PET, MRI
Computer Vision and Robotics (Autonomous Systems)
IdentifiersURN: urn:nbn:se:uu:diva-233200OAI: oai:DiVA.org:uu-233200DiVA: diva2:751005
Master Programme in Engineering Physics
Kullberg, Joel, Docent
Nyberg, Tomas, Teknologie DoktorStrand, Robin, Docent