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The Colours of Diabetes: advances and novel applications of molecular optical techniques for studies of the pancreas
Umeå University, Faculty of Medicine, Umeå Centre for Molecular Medicine (UCMM).
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Diabetes is a rapidly increasing health problem. In a global perspective,approximately 415 million people suffered from diabetes in 2015 and this number ispredicted to increase to 640 million by 2040. To tackle this pandemic there is a needfor better analytical tools by which we can increase our understanding of the disease.One discipline that has already provided much needed insight to diabetes etiology isoptical molecular imaging. Using various forms of light it is possible to create animage of the analysed sample that can provide information about molecularmechanistic aspects of the disease and to follow spatial and temporal dynamics.

The overall aim of this thesis is to improve and adapt existing andnovel optical imaging approaches for their specific use in diabetes research. Hereby,we have focused on three techniques: (I) Optical projection tomography (OPT),which can be described as the optical equivalent of x-ray computed tomography(CT), and two vibrational microspectroscopic (VMS) techniques, which records theunique vibrational signatures of molecules building up the sample: (II) Fouriertransforminfrared vibrational microspectroscopy (FT-IR) and (III) Ramanvibrational microspectroscopy (Raman).

The computational tools and hardware applications presented here generallyimprove OPT data quality, processing speed, sample size and channel capacity.Jointly, these developments enable OPT as a routine tool in diabetes research,facilitating aspects of e.g. pancreatic β-cell generation, proliferation,reprogramming, destruction and preservation to be studied throughout the pancreaticvolume and in large cohorts of experimental animals. Further, a novel application ofmultivariate analysis of VMS data derived from pancreatic tissues is introduced.This approach enables detection of novel biochemical alterations in the pancreasduring diabetes disease progression and can be used to confirm previously reportedbiochemical alterations, but at an earlier stage. Finally, our studies indicate thatRaman imaging is applicable to in vivo studies of grafted islets of Langerhans,allowing for longitudinal studies of pancreatic islet biochemistry.viIn summary, presented here are new and improved methods by which opticalimaging techniques can be utilised to study 3D-spatial, quantitative andmolecular/biochemical alterations of the normal and diseased pancreas.

Place, publisher, year, edition, pages
Umeå: Umeå universitet , 2016. , 55 p.
Series
Umeå University medical dissertations, ISSN 0346-6612 ; 1811
Keyword [en]
Optical projection tomography, Technique development, Near-infrared, 3D visualization, Biomedical imaging, ß-cell mass, Diabetes, Vibrational micro spectroscopy
National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
URN: urn:nbn:se:umu:diva-119845ISBN: 978-91-7601-426-4OAI: oai:DiVA.org:umu-119845DiVA: diva2:924941
Public defence
2016-05-26, Hörsal Betula, Målpunkt L, Plan 0, Norrlands Universitets sjukhus, Umeå, 09:00 (English)
Opponent
Supervisors
Available from: 2016-05-04 Created: 2016-04-29 Last updated: 2016-05-26Bibliographically approved
List of papers
1. Image processing assisted algorithms for optical projection tomography
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2012 (English)In: IEEE Transactions on Medical Imaging, ISSN 0278-0062, E-ISSN 1558-254X, Vol. 31, no 1, 1-15 p.Article in journal (Refereed) Published
Abstract [en]

Since it was first presented in 2002, optical projection tomography (OPT) has emerged as a powerful tool for the study of biomedical specimen on the mm to cm scale. In this paper, we present computational tools to further improve OPT image acquisition and tomographic reconstruction. More specifically, these methods provide: semi-automatic and precise positioning of a sample at the axis of rotation and a fast and robust algorithm for determination of postalignment values throughout the specimen as compared to existing methods. These tools are easily integrated for use with current commercial OPT scanners and should also be possible to implement in "home made" or experimental setups for OPT imaging. They generally contribute to increase acquisition speed and quality of OPT data and thereby significantly simplify and improve a number of three-dimensional and quantitative OPT based assessments.

Keyword
artifacts, axis of rotation (AR), biomedical image processing, islets of Langerhans, optical projection tomography (OPT), pancreas, postalignment
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:umu:diva-51582 (URN)10.1109/TMI.2011.2161590 (DOI)000298782200001 ()21768046 (PubMedID)
Available from: 2012-01-27 Created: 2012-01-27 Last updated: 2016-05-03Bibliographically approved
2. Near infrared optical projection tomography for assessments of β-cell mass distribution in diabetes research
Open this publication in new window or tab >>Near infrared optical projection tomography for assessments of β-cell mass distribution in diabetes research
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2013 (English)In: Journal of Visualized Experiments, ISSN 1940-087X, Vol. 71, no e50238Article in journal (Refereed) Published
Abstract [en]

By adapting OPT to include the capability of imaging in the near infrared (NIR) spectrum, we here illustrate the possibility to image larger bodies of pancreatic tissue, such as the rat pancreas, and to increase the number of channels (cell types) that may be studied in a single specimen. We further describe the implementation of a number of computational tools that provide: 1/ accurate positioning of a specimen's (in our case the pancreas) centre of mass (COM) at the axis of rotation (AR)2; 2/ improved algorithms for post-alignment tuning which prevents geometric distortions during the tomographic reconstruction2 and 3/ a protocol for intensity equalization to increase signal to noise ratios in OPT-based BCM determinations3. In addition, we describe a sample holder that minimizes the risk for unintentional movements of the specimen during image acquisition. Together, these protocols enable assessments of BCM distribution and other features, to be performed throughout the volume of intact pancreata or other organs (e.g. in studies of islet transplantation), with a resolution down to the level of individual islets of Langerhans.

National Category
Biomedical Laboratory Science/Technology
Identifiers
urn:nbn:se:umu:diva-64029 (URN)10.3791/50238 (DOI)
Available from: 2013-01-14 Created: 2013-01-14 Last updated: 2016-05-03Bibliographically approved
3. Improving signal detection in emission optical projection tomography via single source multi-exposure image fusion
Open this publication in new window or tab >>Improving signal detection in emission optical projection tomography via single source multi-exposure image fusion
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2013 (English)In: Optics Express, ISSN 1094-4087, Vol. 21, no 14, 16584-16604 p.Article in journal (Refereed) Published
Abstract [en]

We demonstrate a technique to improve structural data obtained from Optical Projection Tomography (OPT) using Image Fusion (IF) and contrast normalization. This enables the visualization of molecular expression patterns in biological specimens with highly variable contrast values. In the approach, termed IF-OPT, different exposures are fused by assigning weighted contrasts to each. When applied to projection images from mouse organs and digital phantoms our results demonstrate the capability of IF-OPT to reveal high and low signal intensity details in challenging specimens. We further provide measurements to highlight the benefits of the new algorithm in comparison to other similar methods.

Place, publisher, year, edition, pages
Optical Society of America, 2013
National Category
Other Medical Biotechnology
Identifiers
urn:nbn:se:umu:diva-80512 (URN)10.1364/OE.21.016584 (DOI)
Funder
Swedish Research CouncilEU, European Research Council, CP-IP 228933-2
Available from: 2013-09-19 Created: 2013-09-19 Last updated: 2016-05-03Bibliographically approved
4. Multivariate image analysis facilitates label‐free, biochemicalprofiling of the diabetic pancreas
Open this publication in new window or tab >>Multivariate image analysis facilitates label‐free, biochemicalprofiling of the diabetic pancreas
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(English)Manuscript (preprint) (Other academic)
National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
urn:nbn:se:umu:diva-119846 (URN)
Available from: 2016-04-29 Created: 2016-04-29 Last updated: 2016-05-03

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The full text will be freely available from 2017-05-04 09:00
Available from 2017-05-04 09:00

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Nord, Christoffer
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