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The Colours of Diabetes: advances and novel applications of molecular optical techniques for studies of the pancreas
Umeå universitet, Medicinska fakulteten, Umeå centrum för molekylär medicin (UCMM).
2016 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
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.

Ort, förlag, år, upplaga, sidor
Umeå: Umeå universitet , 2016. , s. 55
Serie
Umeå University medical dissertations, ISSN 0346-6612 ; 1811
Nyckelord [en]
Optical projection tomography, Technique development, Near-infrared, 3D visualization, Biomedical imaging, ß-cell mass, Diabetes, Vibrational micro spectroscopy
Nationell ämneskategori
Medicinsk bioteknologi (med inriktning mot cellbiologi (inklusive stamcellsbiologi), molekylärbiologi, mikrobiologi, biokemi eller biofarmaci)
Identifikatorer
URN: urn:nbn:se:umu:diva-119845ISBN: 978-91-7601-426-4 (tryckt)OAI: oai:DiVA.org:umu-119845DiVA, id: diva2:924941
Disputation
2016-05-26, Hörsal Betula, Målpunkt L, Plan 0, Norrlands Universitets sjukhus, Umeå, 09:00 (Engelska)
Opponent
Handledare
Tillgänglig från: 2016-05-04 Skapad: 2016-04-29 Senast uppdaterad: 2018-06-07Bibliografiskt granskad
Delarbeten
1. Image processing assisted algorithms for optical projection tomography
Öppna denna publikation i ny flik eller fönster >>Image processing assisted algorithms for optical projection tomography
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2012 (Engelska)Ingår i: IEEE Transactions on Medical Imaging, ISSN 0278-0062, E-ISSN 1558-254X, Vol. 31, nr 1, s. 1-15Artikel i tidskrift (Refereegranskat) 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.

Nyckelord
artifacts, axis of rotation (AR), biomedical image processing, islets of Langerhans, optical projection tomography (OPT), pancreas, postalignment
Nationell ämneskategori
Medicin och hälsovetenskap
Identifikatorer
urn:nbn:se:umu:diva-51582 (URN)10.1109/TMI.2011.2161590 (DOI)000298782200001 ()21768046 (PubMedID)
Tillgänglig från: 2012-01-27 Skapad: 2012-01-27 Senast uppdaterad: 2018-06-08Bibliografiskt granskad
2. Near infrared optical projection tomography for assessments of beta-cell mass distribution in diabetes research
Öppna denna publikation i ny flik eller fönster >>Near infrared optical projection tomography for assessments of beta-cell mass distribution in diabetes research
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2013 (Engelska)Ingår i: Journal of Visualized Experiments, ISSN 1940-087X, E-ISSN 1940-087X, Vol. 71, artikel-id e50238Artikel i tidskrift (Refereegranskat) 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.

Nationell ämneskategori
Biomedicinsk laboratorievetenskap/teknologi
Identifikatorer
urn:nbn:se:umu:diva-64029 (URN)10.3791/50238 (DOI)000209226200052 ()23353681 (PubMedID)
Tillgänglig från: 2013-01-14 Skapad: 2013-01-14 Senast uppdaterad: 2018-06-08Bibliografiskt granskad
3. Improving signal detection in emission optical projection tomography via single source multi-exposure image fusion
Öppna denna publikation i ny flik eller fönster >>Improving signal detection in emission optical projection tomography via single source multi-exposure image fusion
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2013 (Engelska)Ingår i: Optics Express, ISSN 1094-4087, E-ISSN 1094-4087, Vol. 21, nr 14, s. 16584-16604Artikel i tidskrift (Refereegranskat) 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.

Ort, förlag, år, upplaga, sidor
Optical Society of America, 2013
Nationell ämneskategori
Annan medicinsk bioteknologi
Identifikatorer
urn:nbn:se:umu:diva-80512 (URN)10.1364/OE.21.016584 (DOI)000321819400038 ()23938510 (PubMedID)
Forskningsfinansiär
VetenskapsrådetEU, Europeiska forskningsrådet, CP-IP 228933-2
Tillgänglig från: 2013-09-19 Skapad: 2013-09-19 Senast uppdaterad: 2018-06-08Bibliografiskt granskad
4. Multivariate image analysis facilitates label‐free, biochemicalprofiling of the diabetic pancreas
Öppna denna publikation i ny flik eller fönster >>Multivariate image analysis facilitates label‐free, biochemicalprofiling of the diabetic pancreas
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(Engelska)Manuskript (preprint) (Övrigt vetenskapligt)
Nationell ämneskategori
Medicinsk bioteknologi (med inriktning mot cellbiologi (inklusive stamcellsbiologi), molekylärbiologi, mikrobiologi, biokemi eller biofarmaci)
Identifikatorer
urn:nbn:se:umu:diva-119846 (URN)
Tillgänglig från: 2016-04-29 Skapad: 2016-04-29 Senast uppdaterad: 2018-06-07

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