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Multi-Parametric Representation of Voxel-Based Quantitative Magnetic Resonance Imaging
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0002-2167-2450
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
Linköping University, Department of Clinical and Experimental Medicine, Division of Neuroscience. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Östergötlands Läns Landsting, Local Health Care Services in Central Östergötland, Department of Neurology.
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2014 (English)Conference paper, Poster (with or without abstract) (Other academic)
Abstract [en]

The aim of the study was to explore the possibilities of multi-parametric representations of voxel-wise quantitative MRI data to objectively discriminate pathological cerebral tissue in patients with brain disorders. For this purpose, we recruited 19 patients with Multiple Sclerosis (MS) as benchmark samples and 19 age and gender matched healthy subjects as a reference group. The subjects were examined using quantitative Magnetic Resonance Imaging (MRI) measuring the tissue structure parameters: relaxation rates, R and R, and proton density. The resulting parameter images were normalized to a standard template. Tissue structure in MS patients was assessed by voxel-wise comparisons with the reference group and with correlation to a clinical measure, the Expanded Disability Status Scale (EDSS). The results were visualized by conventional geometric representations and also by multi-parametric representations. Data showed that MS patients had lower R and R, and higher proton density in periventricular white matter and in wide-spread areas encompassing central and sub-cortical white matter structures. MS-related tissue abnormality was highlighted in posterior white matter whereas EDSS correlation appeared especially in the frontal cortex. The multi-parameter representation highlighted disease-specific features. In conclusion, the proposed method has the potential to visualize both high-probability focal anomalies and diffuse tissue changes. Results from voxel-based statistical analysis, as exemplified in the present work, may guide radiologists where in the image to inspect for signs of disease. Future clinical studies must validate the usability of the method in clinical practice.

Place, publisher, year, edition, pages
2014. Vol. 9, e111688- p.
National Category
Clinical Medicine
Identifiers
URN: urn:nbn:se:liu:diva-114360DOI: 25393722PubMedID: 25393722OAI: oai:DiVA.org:liu-114360DiVA: diva2:789524
Conference
The International Society for Magnetic Resonance in Medicine (ISMRM) 2014, Milan, Italy
Available from: 2015-02-19 Created: 2015-02-19 Last updated: 2015-04-14

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Engström, MariaJan Bertus Warntje, MarcelTisell, AndersLandtblom, Anne-MarieLundberg, Peter

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Engström, MariaJan Bertus Warntje, MarcelTisell, AndersLandtblom, Anne-MarieLundberg, Peter
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Division of Radiological SciencesFaculty of Health SciencesCenter for Medical Image Science and Visualization (CMIV)Division of Cardiovascular MedicineDepartment of Clinical Physiology in LinköpingDepartment of Radiation PhysicsDivision of NeuroscienceDepartment of NeurologyDepartment of Radiology in Linköping
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