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Automated segmentation of human cervical-supraclavicular adipose tissue in magnetic resonance images
Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för kirurgiska vetenskaper, Radiologi.
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.ORCID-id: 0000-0001-7764-1787
Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för kvinnors och barns hälsa.ORCID-id: 0000-0001-9109-4556
Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinsk cellbiologi.
Vise andre og tillknytning
2017 (engelsk)Inngår i: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 7, artikkel-id 3064Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Human brown adipose tissue (BAT), with a major site in the cervical-supraclavicular depot, is a promising anti-obesity target. This work presents an automated method for segmenting cervical-supraclavicular adipose tissue for enabling time-efficient and objective measurements in large cohort research studies of BAT. Fat fraction (FF) and R2* maps were reconstructed from water-fat magnetic resonance imaging (MRI) of 25 subjects. A multi-atlas approach, based on atlases from nine subjects, was chosen as automated segmentation strategy. A semi-automated reference method was used to validate the automated method in the remaining subjects. Automated segmentations were obtained from a pipeline of preprocessing, affine registration, elastic registration and postprocessing. The automated method was validated with respect to segmentation overlap (Dice similarity coefficient, Dice) and estimations of FF, R2* and segmented volume. Bias in measurement results was also evaluated. Segmentation overlaps of Dice = 0.93 +/- 0.03 (mean +/- standard deviation) and correlation coefficients of r > 0.99 (P < 0.0001) in FF, R2* and volume estimates, between the methods, were observed. Dice and BMI were positively correlated (r = 0.54, P = 0.03) but no other significant bias was obtained (P >= 0.07). The automated method compared well with the reference method and can therefore be suitable for time-efficient and objective measurements in large cohort research studies of BAT.

sted, utgiver, år, opplag, sider
2017. Vol. 7, artikkel-id 3064
HSV kategori
Forskningsprogram
Datoriserad bildbehandling
Identifikatorer
URN: urn:nbn:se:uu:diva-323968DOI: 10.1038/s41598-017-01586-7ISI: 000402865000003PubMedID: 28596551OAI: oai:DiVA.org:uu-323968DiVA, id: diva2:1108055
Forskningsfinansiär
Swedish Research CouncilEU, FP7, Seventh Framework Programme, 279153Tilgjengelig fra: 2017-06-08 Laget: 2017-06-12 Sist oppdatert: 2019-04-15bibliografisk kontrollert
Inngår i avhandling
1. Magnetic Resonance Imaging of Human Brown Adipose Tissue: Methodological Development and Application
Åpne denne publikasjonen i ny fane eller vindu >>Magnetic Resonance Imaging of Human Brown Adipose Tissue: Methodological Development and Application
2019 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

Brown adipose tissue (BAT) is a thermogenic organ with the main human depot located in the cervical-supraclavicular (sBAT) region. BAT is proposed as a potential therapeutic target for obesity and diabetes. This thesis aims to contribute to the development of magnetic resonance imaging (MRI)-based methods and to the application of these in studies of human BAT. Water-fat MRI enables separation of water and fat, the dominant contributors to the MR signal, and the quantification of fat fraction (FF) and effective transverse relaxation rate (R2*). FF and R2* are often used in studies of human BAT, e.g. for characterizing the tissue and distinguishing it from white adipose tissue. A Cooling-reheating protocol was introduced for studying changes in sBAT, related to lipid content and perfusion. sBAT FF decreased after cold exposure. The sustained low FF after reheating suggested lipid consumption as the primary cause. This conclusion was based on the assumption of a normalized perfusion after reheating. An automated method for segmentation of sBAT was developed. The method compared well with a semi-automated reference method with respect to segmentation overlap and estimated mean sBAT FF and R2*. A modified version of the automated method was applied to a large-scale study where an association between sBAT FF and glucose tolerance indicated a role for BAT in glucose metabolism, potentially linked to the risk of developing diabetes.  A Cooling-reheating protocol was evaluated with positron emission tomography measurements of perfusion and cold-stimulated BAT activity. Inverse correlations between sBAT FF and BAT activity suggested sBAT FF to predict cold-induced BAT activity. After reheating, the cold-induced increase in perfusion normalized and the cold-induced decrease in FF partially normalized. This suggested potential decreases in FF after reheating to mainly be due to lipid consumption and decreases in FF after cold exposure to possibly be influenced by perfusion.

sted, utgiver, år, opplag, sider
Uppsala: Acta Universitatis Upsaliensis, 2019. s. 83
Serie
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1572
Emneord
Brown adipose tissue, Magnetic resonance imaging, Positron emission tomography, Image segmentation, Glucose metabolism
HSV kategori
Identifikatorer
urn:nbn:se:uu:diva-381766 (URN)978-91-513-0651-3 (ISBN)
Disputas
2019-06-07, Rosénsalen, Entrance 95/96, Akademiska sjukhuset, Uppsala, 09:15 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2019-05-17 Laget: 2019-04-15 Sist oppdatert: 2019-06-18

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