liu.seSearch for publications in DiVA
Change search
Refine search result
1234 1 - 50 of 155
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Aalto, Anne
    et al.
    Linköping University, Department of Medicine and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Jaworski, M
    Gustavsson, M
    Tisell, Anders
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL. Linköping University, Faculty of Health Sciences.
    Landtblom, Anne-Marie
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Clinical and Experimental Medicine, Psychiatry. Östergötlands Läns Landsting, Sinnescentrum, Department of Neurosurgery UHL. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Effects of Betainterferon treatment in Multiple Sclerosis Studied by Quantitative 1H MRS2009Conference paper (Other academic)
  • 2.
    Abbott, Rebecca
    et al.
    Northwestern Univ, IL 60611 USA.
    Peolsson, Anneli
    Linköping University, Department of Medical and Health Sciences, Division of Physiotherapy. Linköping University, Faculty of Medicine and Health Sciences.
    West, Janne
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Medicine and Health Sciences.
    Elliott, James M.
    Northwestern Univ, IL 60611 USA; Univ Queensland, Australia; Zurich Univ Appl Sci, Switzerland.
    Åslund, Ulrika
    Linköping University, Department of Medical and Health Sciences, Division of Physiotherapy. Linköping University, Faculty of Medicine and Health Sciences.
    Karlsson, Anette
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    The qualitative grading of muscle fat infiltration in whiplash using fat and water magnetic resonance imaging2018In: The spine journal, ISSN 1529-9430, E-ISSN 1878-1632, Vol. 18, no 5, p. 717-725Article in journal (Refereed)
    Abstract [en]

    BACKGROUND CONTEXT: The development of muscle fat infiltration (MFI) in the neck muscles is associated with poor functional recovery following whiplash injury. Custom software and time-consuming manual segmentation of magnetic resonance imaging (MRI) is required for quantitative analysis and presents as a barrier for clinical translation. PURPOSE: The purpose of this work was to establish a qualitative MRI measure for MFI and evaluate its ability to differentiate between individuals with severe whiplash-associated disorder (WAD), mild or moderate WAD, and healthy controls. STUDY DESIGN/SETTING: This is a cross-sectional study. PATIENT SAMPLE: Thirty-one subjects with WAD and 31 age-and sex-matched controls were recruited from an ongoing randomized controlled trial. OUTCOME MEASURES: The cervical multifidus was visually identified and segmented into eighths in the axial fat/water images (C4-C7). Muscle fat infiltration was assessed on a visual scale: 0 for no or marginal MFI, 1 for light MFI, and 2 for distinct MFI. The participants with WAD were divided in two groups: mild or moderate and severe based on Neck Disability Index % scores. METHODS: The mean regional MFI was compared between the healthy controls and each of the WAD groups using the Mann-Whitney U test. Receiver operator characteristic (ROC) analyses were carried out to evaluate the validity of the qualitative method. RESULTS: Twenty (65%) patients had mild or moderate disability and 11 (35%) were considered severe. Inter- and intra-rater reliability was excellent when grading was averaged by level or when frequency of grade II was considered. Statistically significant differences (pamp;lt;.05) in regional MFI were particularly notable between the severe WAD group and healthy controls. The ROC curve, based on detection of distinct MFI, showed an area-under-the curve of 0.768 (95% confidence interval 0.59-0.94) for discrimination of WAD participants. CONCLUSIONS: These preliminary results suggest a qualitative MRI measure for MFI is reliable and valid, and may prove useful toward the classification of WAD in radiology practice. (C) 2017 Elsevier Inc. All rights reserved.

  • 3.
    Abrahamsson, Annelie
    et al.
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Oncology.
    Rzepecka, Anna
    Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Romu, Thobias
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Borga, Magnus
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Lundberg, Peter
    Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Dabrosin, Charlotta
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Oncology.
    Dense breast tissue in postmenopausal women is associated with a pro-inflammatory microenvironment in vivo2016In: Oncoimmunology, ISSN 2162-4011, E-ISSN 2162-402X, Vol. 5, no 10, article id e1229723Article in journal (Refereed)
    Abstract [en]

    Inflammation is one of the hallmarks of carcinogenesis. High mammographic density has been associated with increased risk of breast cancer but the mechanisms behind are poorly understood. We evaluated whether breasts with different mammographic densities exhibited differences in the inflammatory microenvironment.Postmenopausal women attending the mammography-screening program were assessed having extreme dense, n = 20, or entirely fatty breasts (nondense), n = 19, on their regular mammograms. Thereafter, the women were invited for magnetic resonance imaging (MRI), microdialysis for the collection of extracellular molecules in situ and a core tissue biopsy for research purposes. On the MRI, lean tissue fraction (LTF) was calculated for a continuous measurement of breast density. LTF confirmed the selection from the mammograms and gave a continuous measurement of breast density. Microdialysis revealed significantly increased extracellular in vivo levels of IL-6, IL-8, vascular endothelial growth factor, and CCL5 in dense breast tissue as compared with nondense breasts. Moreover, the ratio IL-1Ra/IL-1 was decreased in dense breasts. No differences were found in levels of IL-1, IL-1Ra, CCL2, leptin, adiponectin, or leptin:adiponectin ratio between the two breast tissue types. Significant positive correlations between LTF and the pro-inflammatory cytokines as well as between the cytokines were detected. Stainings of the core biopsies exhibited increased levels of immune cells in dense breast tissue.Our data show that dense breast tissue in postmenopausal women is associated with a pro-inflammatory microenvironment and, if confirmed in a larger cohort, suggests novel targets for prevention therapies for women with dense breast tissue.

  • 4.
    Agebratt, Christian
    et al.
    Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Medicine and Health Sciences.
    Ström, Edvin
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Romu, Thobias
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Borga, Magnus
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Leandersson, Per
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Occupational and Environmental Medicine Center.
    Nyström, Fredrik H.
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Endocrinology.
    A Randomized Study of the Effects of Additional Fruit and Nuts Consumption on Hepatic Fat Content, Cardiovascular Risk Factors and Basal Metabolic Rate2016In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 1, p. e0147149-Article in journal (Refereed)
    Abstract [en]

    Background

    Fruit has since long been advocated as a healthy source of many nutrients, however, the high content of sugars in fruit might be a concern.

    Objectives

    To study effects of an increased fruit intake compared with similar amount of extra calories from nuts in humans.

    Methods

    Thirty healthy non-obese participants were randomized to either supplement the diet with fruits or nuts, each at +7 kcal/kg bodyweight/day for two months. Major endpoints were change of hepatic fat content (HFC, by magnetic resonance imaging, MRI), basal metabolic rate (BMR, with indirect calorimetry) and cardiovascular risk markers.

    Results

    Weight gain was numerically similar in both groups although only statistically significant in the group randomized to nuts (fruit: from 22.15±1.61 kg/m2 to 22.30±1.7 kg/m2, p = 0.24 nuts: from 22.54±2.26 kg/m2 to 22.73±2.28 kg/m2, p = 0.045). On the other hand BMR increased in the nut group only (p = 0.028). Only the nut group reported a net increase of calories (from 2519±721 kcal/day to 2763±595 kcal/day, p = 0.035) according to 3-day food registrations. Despite an almost three-fold reported increased fructose-intake in the fruit group (from 9.1±6.0 gram/day to 25.6±9.6 gram/day, p<0.0001, nuts: from 12.4±5.7 gram/day to 6.5±5.3 gram/day, p = 0.007) there was no change of HFC. The numerical increase in fasting insulin was statistical significant only in the fruit group (from 7.73±3.1 pmol/l to 8.81±2.9 pmol/l, p = 0.018, nuts: from 7.29±2.9 pmol/l to 8.62±3.0 pmol/l, p = 0.14). Levels of vitamin C increased in both groups while α-tocopherol/cholesterol-ratio increased only in the fruit group.

    Conclusions

    Although BMR increased in the nut-group only this was not linked with differences in weight gain between groups which potentially could be explained by the lack of reported net caloric increase in the fruit group. In healthy non-obese individuals an increased fruit intake seems safe from cardiovascular risk perspective, including measurement of HFC by MRI.

  • 5.
    Ahlman, Gustav
    et al.
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Magnusson, Maria
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Increased temporal resolution in radial-Cartesian sampling of k-space by implementation of parallel imaging2011Conference paper (Refereed)
  • 6.
    Andersson, Thord
    et al.
    Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Dept. of C4ISR, Swedish Defence Research Agency, Linköping, Sweden, .
    Borga, Magnus
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Geodesic registration for interactive atlas-based segmentation using learned multi-scale anatomical manifolds2018In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 112, p. 340-345Article in journal (Refereed)
    Abstract [en]

    Atlas-based segmentation is often used to segment medical image regions. For intensity-normalized data, the quality of these segmentations is highly dependent on the similarity between the atlas and the target under the used registration method. We propose a geodesic registration method for interactive atlas-based segmentation using empirical multi-scale anatomical manifolds. The method utilizes unlabeled images together with the labeled atlases to learn empirical anatomical manifolds. These manifolds are defined on distinct scales and regions and are used to propagate the labeling information from the atlases to the target along anatomical geodesics. The resulting competing segmentations from the different manifolds are then ranked according to an image-based similarity measure. We used image volumes acquired using magnetic resonance imaging from 36 subjects. The performance of the method was evaluated using a liver segmentation task. The result was then compared to the corresponding performance of direct segmentation using Dice Index statistics. The method shows a significant improvement in liver segmentation performance between the proposed method and direct segmentation. Furthermore, the standard deviation in performance decreased significantly. Using competing complementary manifolds defined over a hierarchy of region of interests gives an additional improvement in segmentation performance compared to the single manifold segmentation.

  • 7.
    Andersson, Thord
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Romu, Thobias
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Karlsson, Anette
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Norén, Bengt
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Forsgren, Mikael
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Smedby, Örjan
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Kechagias, Stergios
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Gastroentorology.
    Almer, Sven
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Gastroentorology.
    Lundberg, Peter
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Borga, Magnus
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Consistent intensity inhomogeneity correction in water–fat MRI2015In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 42, no 2, p. 468-476Article in journal (Refereed)
    Abstract [en]

    PURPOSE:

    To quantitatively and qualitatively evaluate the water-signal performance of the consistent intensity inhomogeneity correction (CIIC) method to correct for intensity inhomogeneities METHODS: Water-fat volumes were acquired using 1.5 Tesla (T) and 3.0T symmetrically sampled 2-point Dixon three-dimensional MRI. Two datasets: (i) 10 muscle tissue regions of interest (ROIs) from 10 subjects acquired with both 1.5T and 3.0T whole-body MRI. (ii) Seven liver tissue ROIs from 36 patients imaged using 1.5T MRI at six time points after Gd-EOB-DTPA injection. The performance of CIIC was evaluated quantitatively by analyzing its impact on the dispersion and bias of the water image ROI intensities, and qualitatively using side-by-side image comparisons.

    RESULTS:

    CIIC significantly ( P1.5T≤2.3×10-4,P3.0T≤1.0×10-6) decreased the nonphysiological intensity variance while preserving the average intensity levels. The side-by-side comparisons showed improved intensity consistency ( Pint⁡≤10-6) while not introducing artifacts ( Part=0.024) nor changed appearances ( Papp≤10-6).

    CONCLUSION:

    CIIC improves the spatiotemporal intensity consistency in regions of a homogenous tissue type. J. Magn. Reson. Imaging 2014.

  • 8.
    Andersson, Thord
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Romu, Thobias
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Norén, Bengt
    Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Forsgren, Mikael
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Almer, Sven
    Linköping University, Department of Clinical and Experimental Medicine, Gastroenterology and Hepatology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Endocrinology.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Borga, Magnus
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Self-calibrated DCE MRI using Multi Scale Adaptive Normalized Averaging (MANA)2012In: Proceedings of the annual meeting of the International Society for Magnetic Resonance in Medicine (ISMRM 2012), 2012, 2012Conference paper (Other academic)
  • 9.
    Borga, Magnus
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Andersson, Thord
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Semi-Supervised Learning of Anatomical Manifolds for Atlas-Based Segmentation of Medical Images2016In: Proceedings of the 23rd International Conference on Pattern Recognition (ICPR), IEEE Computer Society, 2016, p. 3146-3149Conference paper (Refereed)
    Abstract [en]

    This paper presents a novel method for atlas-based segmentation of medical images. The method uses semi- supervised learning of a graph describing a manifold of anatom- ical variations of whole-body images, where unlabelled data are used to find a path with small deformations from the labelled atlas to the target image. The method is evaluated on 36 whole-body magnetic resonance images with manually segmented livers as ground truth. Significant improvement (p < 0.001) was obtained compared to direct atlas-based registration. 

  • 10.
    Borga, Magnus
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dahlqvist, Leinhard Olof
    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.
    Lundberg, Peter
    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.
    Improvement in Magnetic Resonance Imaging Relating to Correction of Chemical Shift Artifact and Intensity Inhomogeneity2011Patent (Other (popular science, discussion, etc.))
    Abstract [en]

    Present invention discloses systems and methods for improvement of magnetic resonance images. Correction of a chemical shift artefact in an image acquired from a magnetic resonance imaging system is obtained by a system and a method involving iterative - compensation for the misregistration effect in an image domain. Correction of an intensity inhomogeneity in such images is obtained by a system and a method involving locating voxels corresponding to pure adipose tissue and estimating correction field from these points.

  • 11.
    Borga, Magnus
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Thomas, E. Louise
    Department of Life Sciences Faculty of Science and Technology University of Westminster, London, United Kingdom.
    Romu, Thobias
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Rosander, Johannes
    Advanced MR Analytics AB, Linköping, Sweden.
    Fitzpatrick, Julie
    Department of Life Sciences Faculty of Science and Technology University of Westminster, London, United Kingdom.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Bell, Jimmy D
    Department of Life Sciences Faculty of Science and Technology University of Westminster, London, United Kingdom.
    Validation of a Fast Method for Quantification of Intra-abdominal and Subcutaneous Adipose Tissue for Large Scale Human Studies2015In: NMR in Biomedicine, ISSN 1099-1492, Vol. 28, no 12, p. 1747-1753Article in journal (Refereed)
    Abstract [en]

    Central obesity is the hallmark of a number of non-inheritable disorders. The advent of imaging techniques such as magnetic resonance imaging (MRI) has allowed for a fast and accurate assessment of body fat content and distribution. However, image analysis continues to be one of the major obstacles for the use of MRI in large scale studies. In this study we assess the validity of the recently proposed fat-muscle-quantitation-system (AMRATM Profiler) for the quantification of intra-abdominal adipose tissue (IAAT) and abdominal subcutaneous adipose tissue (ASAT) from abdominal MR images.  Abdominal MR images were acquired from 23 volunteers with a broad range of BMIs and analysed using SliceOmatic, the current gold-standard, and the AMRATM Profiler based on a non-rigid image registration of a library of segmented atlases. The results show that there was a highly significant correlation between the fat volumes generated by both analysis methods, (Pearson correlation r = 0.97 p<0.001), with the AMRATM Profiler analysis being significantly faster (~3 mins) than the conventional SliceOmatic approach (~40 mins). There was also excellent agreement between the methods for the quantification of IAAT (AMRA 4.73 ± 1.99 vs SliceOmatic 4.73 ± 1.75 litres, p=0.97). For the AMRATM Profiler analysis, the intra-observer coefficient of variation was 1.6 % for IAAT and 1.1 % for ASAT, the inter-observer coefficient of variation was 1.4 % for IAAT and 1.2 % for ASAT, the intra-observer correlation was 0.998 for IAAT and 0.999 for ASAT, and the inter-observer correlation was 0.999 for both IAAT and ASAT. These results indicate that precise and accurate measures of body fat content and distribution can be obtained in a fast and reliable form by the AMRATM Profiler, opening up the possibility of large-scale human phenotypic studies.

  • 12.
    Borga, Magnus
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Virtanen, Kirsi A.
    Turku PET Centre, University of Turku, Finland.
    Romu, Thobias
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Persson, Anders
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Nuutila, Pirjo
    Turku PET Centre, University of Turku, Finland.
    Enerbäck, Sven
    Department of Biomedicine, University of Gothenburg, Sweden.
    Brown adipose tissue in humans: detection and functional analysis using PET (Positron Emission Tomography), MRI (Magnetic Resonance Imaging), and DECT (Dual Energy Computed Tomography)2014In: Methods in Enzymology: Methods of Adipose Tissue Biology / [ed] Ormond MacDougald, Elsevier, 2014, 1, p. 141-159Chapter in book (Other academic)
    Abstract [en]

    Research with the aim to translate findings of the beneficial effects induced by brown adipose tissue (BAT) on metabolism, as seen in various non-human experimental systems to also include human metabolism requires tools that accurately measure how BAT influences human metabolism. This review sets out to discuss such techniques, how they can be used, what they can measure and also some of their limitations. The focus is on detection and functional analysis of human BAT and how this can be facilitated by applying advanced imaging technology such as:  PET (Positron Emission Tomography), MRI (Magnetic Resonance Imaging), and DECT (Dual Energy Computed Tomography).

  • 13.
    Borga, Magnus
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    West, Janne
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Medicine and Health Sciences.
    Bell, Jimmy
    Westminster University, London, UK.
    Harvey, Nicholas
    University of Southampton, IK.
    Romu, Thobias
    Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Heymsfield, Steven
    Pennington Biomedical Research Center, Baton Rouge, LA, US.
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Advanced MR Analytics AB, Linköping, Sweden.
    Advanced body composition assessment: From body mass index to body composition profiling2018In: Journal of Investigative Medicine, ISSN 1081-5589, E-ISSN 1708-8267, Vol. 66, p. 887-895Article, review/survey (Refereed)
    Abstract [en]

    This paper gives a brief overview of common non-invasive techniques for body composition analysis and a more in-depth review of a body composition assessment method based on fat-referenced quantitative magnetic resonance imaging (MRI). Earlier published studies of this method are summarized, and a previously un-published validation study, based on 4.753 subjects from the UK Biobank imaging cohort, comparing the quantitative MRI method with dual-energy x-ray absorptiometry (DXA) is presented. For whole-body measurements of adipose tissue (AT) or fat and lean tissue (LT), DXA and quantitative MRI show excellent agreement with linear correlation of 0.99 and 0.97, and coefficient of variation (CV) of 4.5 % and 4.6 % for fat (computed from AT) and lean tissue respectively, but the agreement was found significantly lower for visceral adipose tissue, with a CV of more than 20 %. The additional ability of MRI to also measure muscle volumes, muscle AT infiltration and ectopic fat in combination with rapid scanning protocols and efficient image analysis tools make quantitative MRI a powerful tool for advanced body composition assessment. 

  • 14.
    Brandejsky, Vaclav
    et al.
    Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL. Linköping University, Faculty of Health Sciences.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Lund, Eva
    Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    A novel method for RF coil magnetic field mapping2008Conference paper (Other academic)
  • 15.
    Brandejsky, Vaclav
    et al.
    Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL. Linköping University, Faculty of Health Sciences.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Lund, Eva
    Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    New MR-scanner independent B1 field mapping technique2009Conference paper (Other academic)
  • 16.
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Quantitative magnetic resonance in diffuse liver and neurological disease2008Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Magnetic resonance (MR) has become one of the most important diagnostic tools in modern medicine. It provides superior soft tissue contrast compared to other imaging modalities, it is extremely flexible as it can be used to image all parts of the body, and it is considered to be safe for patients.

    Today almost all MR is performed in a non-quantitative manner, only by comparing neighbouring tissue in the search for pathology. It is possible to quantify the MR-signals to its physical entities, but time consuming and complicated calibration procedures have prevented this in clinical routine.

    In this work two different applications of quantitative MR-spectroscopy in diffuse liver and neurological disease, and a new rapid method for simultaneous quantification of proton density, T1 relaxation and T2* relaxation in MR-imaging are presented.

    In Paper I, absolutely quantified phosphorus MR-spectroscopy was tested as a predictive tool in order to determine the degree of fibrosis on patients with diffuse liver disease. One group with steatosis and none to moderate inflammation (n=13), one group with severe fibrosis or cirrhosis (n=16), and one group of healthy volunteers (n=13) were included in the study.

    Lower concentrations of PDE (p = 0.025), and a higher metabolic charge (AC) [42] (p < 0.001) were found in the cirrhosis group. A sensitivity and specificity of 81% and 69% respectively, were found for the discrimination between mild and advanced fibrosis using PDE concentrations, and 93% and 54% using AC. The results suggest PDE as a marker of liver fibrosis and AC as a potential clinically useful parameter in discriminating mild from advanced fibrosis.

    In Paper II proton MR-spectroscopy was used to investigate if there were differences in the concentrations of the observable metabolites in normal appearing white matter in patients with clinically definite multiple sclerosis (MS), and with normal MR-images compared to healthy volunteers. This 'MRI-negative' group consisted of fourteen patients which were compared with fourteen healthy controls. Absolutely quantified proton MR-spectra were acquired from four different voxels in NAWM.

    Significant differences in absolute metabolite concentrations were observed between the two groups. The MS-patients had lower total N-acetyl compounds (tNA) (p=0.002) compared to the healthy controls and lower concentration of choline-containing compounds (Cho) compared to the healthy controls (p<0.001). EDSS showed a slightly positive correlation to myolns concentrations (0.14mM/EDSS,r2 = 0.06) and a slightly negative correlation to tNA concentrations (-0.41 mM/EDSS,r2 = 0.22). The finding of lower Cho concentrations has not been reported previously and was unexpected.

    In Paper III a new rapid imaging method was presented for determination of proton density, B1, T2* relaxation and T1 relaxation. The method was based on a modified Look-Locker pulse sequence with two main differences. (1) The exchange of the inversion pulse in the Lock-Looker sequence to a saturation pulse in order to enable detection of the B1 field, and (2) the introduction of a multi-echo read-out to enable the detection of T2*. The signal intensity was then scaled to proton density using the estimated B1, T1, and T2* value.

    The method was validated in vitro, using phantoms filled with solution of different T1 and T2* water relaxation values, and by comparing the results of the measurements to reference metcyods. In vivo the method was compared with literature values.

    The validation showed that the method was highly accurate, both in vitro and in vivo, and that this method enabled quantitative imaging of MR-parameters within a clinically feasible examination time. Potential applications of the method are, among a great range of possibilities, to rapidly provide all the necessary quantification parameters in MR-spectroscopy, and to simultaneously provide fast quantitative diagnostic imaging.

    List of papers
    1. Separation of advanced from mild fibrosis in diffuse liver disease using 31P magnetic resonance spectroscopy
    Open this publication in new window or tab >>Separation of advanced from mild fibrosis in diffuse liver disease using 31P magnetic resonance spectroscopy
    Show others...
    2008 (English)In: European Journal of Radiology, ISSN 0720-048X, E-ISSN 1872-7727, Vol. 66, no 2, p. 313-320Article in journal (Refereed) Published
    Abstract [en]

    31P-MRS using DRESS was used to compare absolute liver metabolite concentrations (PME, Pi, PDE, γATP, αATP, βATP) in two distinct groups of patients with chronic diffuse liver disorders, one group with steatosis (NAFLD) and none to moderate inflammation (n = 13), and one group with severe fibrosis or cirrhosis (n = 16). All patients underwent liver biopsy and extensive biochemical evaluation. A control group (n = 13) was also included. Absolute concentrations and the anabolic charge, AC = {PME}/({PME} + {PDE}), were calculated.

    Comparing the control and cirrhosis groups, lower concentrations of PDE (p = 0.025) and a higher AC (p < 0.001) were found in the cirrhosis group. Also compared to the NAFLD group, the cirrhosis group had lower concentrations of PDE (p = 0.01) and a higher AC (p = 0.009). No significant differences were found between the control and NAFLD group. When the MRS findings were related to the fibrosis stage obtained at biopsy, there were significant differences in PDE between stage F0–1 and stage F4 and in AC between stage F0–1 and stage F2–3.

    Using a PDE concentration of 10.5 mM as a cut-off value to discriminate between mild, F0–2, and advanced, F3–4, fibrosis the sensitivity and specificity were 81% and 69%, respectively. An AC cut-off value of 0.27 showed a sensitivity of 93% and a specificity of 54%.

    In conclusion, the results suggest that PDE is a marker of liver fibrosis, and that AC is a potentially clinically useful parameter in discriminating mild fibrosis from advanced.

    Place, publisher, year, edition, pages
    Elsevier, 2008
    Keywords
    Absolute quantification; Phosphorus; MRS; Steatosis; In vivo
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-43125 (URN)10.1016/j.ejrad.2007.06.004 (DOI)000256140900026 ()17646074 (PubMedID)71944 (Local ID)71944 (Archive number)71944 (OAI)
    Projects
    NILB
    Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2019-06-14Bibliographically approved
    2. Low Choline Concentrations in Normal-Appearing White Matter of Patients with Multiple Sclerosis and Normal MR Imaging Brain Scans
    Open this publication in new window or tab >>Low Choline Concentrations in Normal-Appearing White Matter of Patients with Multiple Sclerosis and Normal MR Imaging Brain Scans
    Show others...
    2007 (English)In: American Journal of Neuroradiology, ISSN 0195-6108, E-ISSN 1936-959X, Vol. 28, no 7, p. 1306-1312Article in journal (Refereed) Published
    Abstract [en]

    BACKGROUND AND PURPOSE: Spectroscopic studies (1H-MR spectroscopy) of normal-appearing white matter (NAWM) in patients with multiple sclerosis (MS) with MR imaging brain lesions have already been performed, but our intention was to investigate NAWM in MS patients who lack brain lesions to elucidate whether the same pathologic changes could be identified.

    MATERIALS AND METHODS: We checked 350 medical files of patients with MS who are registered in our institution. Fourteen patients (11 women and 3 men; mean age, 48.6 years; handicap score, Expanded Disability Status Scale [EDSS] 2.9; range, 1–6.5) with clinically definite MS and a normal MR imaging of the brain were included. 1H-MR spectroscopy was performed in 4 voxels (size approximately 17 × 17 × 17 mm3) using absolute quantification of metabolite concentrations. Fourteen healthy control subjects (11 women and 3 men; mean age, 43.3 years) were analyzed in the same way.

    RESULTS: Significant differences in absolute metabolite concentrations were observed, with the patients with MS showing a lower total concentration of N-acetyl compounds (tNA), including N-acetylaspartate and N-acetyl aspartylglutamate (13.5 mmol/L versus 14.6 mmol/L; P = .002) compared with the healthy control subjects. Unexpectedly, patients with MS presented significantly lower choline-containing compounds (Cho) compared with healthy control subjects (2.2 mmol/L versus 2.4 mmol/L; P < .001). The EDSS showed a positive correlation to myo-inositol concentrations (0.14 mmol/L per EDSS; r2 = 0.06) and a negative correlation to tNA concentrations (−0.41 mmol/L per EDSS; r2 = 0.22).

    CONCLUSION: The unexpected finding of lower Cho concentrations has not been reported previously. We suggest that patients with MS who lack lesions in the brain constitute a separate entity and may have increased protective or healing abilities.

    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-39360 (URN)10.3174/ajnr.A0580 (DOI)000249278700021 ()47991 (Local ID)47991 (Archive number)47991 (OAI)
    Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2019-06-14
    3. Novel method for rapid, simultaneous T1, T*2, and proton density quantification
    Open this publication in new window or tab >>Novel method for rapid, simultaneous T1, T*2, and proton density quantification
    2007 (English)In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 57, no 3, p. 528-537Article in journal (Refereed) Published
    Abstract [en]

    An imaging method called “quantification of relaxation times and proton density by twin-echo saturation-recovery turbo-field echo” (QRAPTEST) is presented as a means of quickly determining the longitudinal T1 and transverse T relaxation time and proton density (PD) within a single sequence. The method also includes an estimation of the B1 field inhomogeneity. High-resolution images covering large volumes can be achieved within clinically acceptable times of 5–10 min. The range of accuracy for determining T1, T, and PD values is flexible and can be optimized relative to any anticipated values. We validated the experimental results against existing methods, and provide a clinical example in which quantification of the whole brain using 1.5 mm3 voxels was achieved in less than 8 min.

    Keywords
    Proton density mapping, Quantitative mri, Rapid quantification, T1 mapping, T2* mapping
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-49979 (URN)10.1002/mrm.21165 (DOI)000244657200010 ()
    Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2019-06-14
  • 17.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Quantitative Magnetic Resonance in Diffuse Neurological and Liver Disease2010Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Introduction: Magnetic resonance (MR) imaging is one of the most important diagnostic tools in modern medicine. Compared to other imaging modalities, it provides superior soft tissue contrast of all parts of the body and it is considered to be safe for patients. Today almost all MR is performed in a nonquantitative manner, only comparing neighboring tissue in the search for pathology. It is possible to quantify MR-signals and relate them to their physical entities, but time consuming and complicated calibration procedures have prevented this being used in a practical manner for clinical routines. The aim of this work is to develop and improve quantification methods in MRspectroscopy (MRS) and MR-imaging (MRI). The techniques are intended to be applied to diffuse diseases, where conventional imaging methods are unable to perform accurate staging or to reveal metabolic changes associated with disease development.

    Methods: Proton (1H) MRS was used to characterize the white matter in the brain of multiple sclerosis (MS) patients. Phosphorus (31P) MRS was used to evaluate the energy metabolism in patients with diffuse liver disease. A new quantitative MRI (qMRI) method was invented for accurate, rapid and simultaneous quantification of B1, T1, T2, and proton density. A method for automatic assessment of visceral adipose tissue volume based on an in- and out-ofphase imaging protocol was developed. Finally, a method for quantification of the hepatobiliary uptake of liver specific T1 enhancing contrast agents was demonstrated on healthy subjects.

    Results: The 1H MRS investigations of white matter in MS-patients revealed a significant correlation between tissue concentrations of Glutamate and Creatine on the one hand and the disease progression rate on the other, as measured using the MSSS. High accuracy, both in vitro and in vivo, of the measured MR-parameters from the qMRI method was observed. 31P MRS showed lower concentrations of phosphodiesters, and a higher metabolic charge in patients with cirrhosis, compared to patients with mild fibrosis and to controls. The adipose tissue quantification method agreed with estimates obtained using manual segmentation, and enabled measurements which were insensitive to partial volume effects. The hepatobiliary uptake of Gd-EOB-DTPA and Gd-BOPTA was significantly correlated in healthy subjects.

    Conclusion: In this work, new methods for accurate quantification of MR parameters in diffuse diseases in the liver and the brain were demonstrated. Several applications were shown where quantitative MR improves the interpretation of observed signal changes in MRI and MRS in relation to underlying differences in physiology and pathophysiology.

    List of papers
    1. Low Choline Concentrations in Normal-Appearing White Matter of Patients with Multiple Sclerosis and Normal MR Imaging Brain Scans
    Open this publication in new window or tab >>Low Choline Concentrations in Normal-Appearing White Matter of Patients with Multiple Sclerosis and Normal MR Imaging Brain Scans
    Show others...
    2007 (English)In: American Journal of Neuroradiology, ISSN 0195-6108, E-ISSN 1936-959X, Vol. 28, no 7, p. 1306-1312Article in journal (Refereed) Published
    Abstract [en]

    BACKGROUND AND PURPOSE: Spectroscopic studies (1H-MR spectroscopy) of normal-appearing white matter (NAWM) in patients with multiple sclerosis (MS) with MR imaging brain lesions have already been performed, but our intention was to investigate NAWM in MS patients who lack brain lesions to elucidate whether the same pathologic changes could be identified.

    MATERIALS AND METHODS: We checked 350 medical files of patients with MS who are registered in our institution. Fourteen patients (11 women and 3 men; mean age, 48.6 years; handicap score, Expanded Disability Status Scale [EDSS] 2.9; range, 1–6.5) with clinically definite MS and a normal MR imaging of the brain were included. 1H-MR spectroscopy was performed in 4 voxels (size approximately 17 × 17 × 17 mm3) using absolute quantification of metabolite concentrations. Fourteen healthy control subjects (11 women and 3 men; mean age, 43.3 years) were analyzed in the same way.

    RESULTS: Significant differences in absolute metabolite concentrations were observed, with the patients with MS showing a lower total concentration of N-acetyl compounds (tNA), including N-acetylaspartate and N-acetyl aspartylglutamate (13.5 mmol/L versus 14.6 mmol/L; P = .002) compared with the healthy control subjects. Unexpectedly, patients with MS presented significantly lower choline-containing compounds (Cho) compared with healthy control subjects (2.2 mmol/L versus 2.4 mmol/L; P < .001). The EDSS showed a positive correlation to myo-inositol concentrations (0.14 mmol/L per EDSS; r2 = 0.06) and a negative correlation to tNA concentrations (−0.41 mmol/L per EDSS; r2 = 0.22).

    CONCLUSION: The unexpected finding of lower Cho concentrations has not been reported previously. We suggest that patients with MS who lack lesions in the brain constitute a separate entity and may have increased protective or healing abilities.

    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-39360 (URN)10.3174/ajnr.A0580 (DOI)000249278700021 ()47991 (Local ID)47991 (Archive number)47991 (OAI)
    Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2019-06-14
    2. Rapid magnetic resonance quantification on the brain: Optimization for clinical usage
    Open this publication in new window or tab >>Rapid magnetic resonance quantification on the brain: Optimization for clinical usage
    2008 (English)In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 60, no 2, p. 320-329Article in journal (Refereed) Published
    Abstract [en]

    A method is presented for rapid simultaneous quantification of the longitudinal T1 relaxation, the transverse T2 relaxation, the proton density (PD), and the amplitude of the local radio frequency B 1 field. All four parameters are measured in one single scan by means of a multislice, multiecho, and multidelay acquisition. It is based on a previously reported method, which was substantially improved for routine clinical usage. The improvements comprise of the use of a multislice spin-echo technique, a background phase correction, and a spin system simulation to compensate for the slice-selective RF pulse profile effects. The aim of the optimization was to achieve the optimal result for the quantification of magnetic resonance parameters within a clinically acceptable time. One benchmark was high-resolution coverage of the brain within 5 min. In this scan time the measured intersubject standard deviation (SD) in a group of volunteers was 2% to 8%, depending on the tissue (voxel size = 0.8 x 0.8 x 5 mm). As an example, the method was applied to a patient with multiple sclerosis in whom the diseased tissue could clearly be distinguished from healthy reference values. Additionally it was shown that, using the approach of synthetic MRI, both accurate conventional contrast images as well as quantification maps can be generated based on the same scan. © 2008 Wiley-Liss, Inc.

    Keywords
    quantitatie MRI, T1 mapping, T2mapping, PD mapping, B1 mapping, synthetic MRI, neurodegenerative disease
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-42804 (URN)10.1002/mrm.21635 (DOI)000258105800011 ()68904 (Local ID)68904 (Archive number)68904 (OAI)
    Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2019-06-14Bibliographically approved
    3. Is Increased Normal White Matter Glutamate Concentration a Precursor of Gliosis and Disease Progression in Multiple Sclerosis?
    Open this publication in new window or tab >>Is Increased Normal White Matter Glutamate Concentration a Precursor of Gliosis and Disease Progression in Multiple Sclerosis?
    Show others...
    (English)Manuscript (preprint) (Other academic)
    Abstract [en]

    Background: The multiple sclerosis (MS) severity scale (MSSS) is a new scoring procedure to clinically characterize the rate of disease progression in MS, rather than the disability of the patient. The latter is often characterized using the expanded disability status score (EDSS). The progress rate of the disease, magnetic resonance imaging (MRI)-based measures of ‘black hole lesions’, and atrophy have all been shown to be predicted well by MSSS. In this study we investigated possible relationships between brain metabolite concentrations, measured using proton (1H) magnetic resonance spectroscopy (MRS), and MSSS.

    Purpose: Our aims were to quantitatively investigate the metabolite concentrations in normal appearing white matter (NAWM) in MS-patients, and also to investigate possible correlations between disease subtype, EDSS and MSSS and metabolite concentrations. To minimize the interference from lesion contamination in the MRS measurement, a refined novel analysis procedure had to be developed in order to correct for partial volume effects in tissues near plaques.

    Materials and Methods: Forty eight patients with Clinically Definite MS (CDMS), and 18 normal control subjects (NC) were included retrospectively from several MRS studies. T1, T2, and proton density MRI, and four white matter 1H MRS single voxel PRESS (Point-REsolved SpectroScopy) spectra were acquired in each subject using echo time 35 ms and repetition time 6000 ms on a 1.5 T MR-scanner. A total of 108 examinations were acquired from patients and 18 from NC. Absolutely quantified NAWM metabolite concentrations were determined using a mixed linear model (MLM) analysis that included the degree of T2 lesion contamination in each voxel. The T2 lesion contamination of the MRS voxels was also used as an estimate of ‘lesion load’ at each exam. The corrected metabolite concentrations were then correlated with clinical measures of the patients’ status, including EDSS and MSSS.

    Results: The axonal marker N-acetyl aspartate (NAA) did not correlate with either EDSS or MSSS. The glial cell markers creatine and myo-inositol correlated positively with EDSS. Creatine and glutamate correlated positively with MSSS. The ‘estimated lesion load’ correlated positively not only with EDSS, but also with the number of bouts since disease onset. Importantly, it did not correlate with MSSS.

    Conclusion: The most interesting findings were the unchanged concentrations of NAA, and the concomitant increase of creatine and myo-inositol during the course of disease progression in MSpatients. These not only indicated a constant axonal density, but also that a simultaneous development of gliosis occurred. These processes are most likely linked to demyelination, as well as development of white matter atrophy, a process in which the demyelinated volume is replaced by the surrounding tissue leading to a net loss of white matter. As a consequence of this process, axons in NAWM are probably damaged, which leads to a higher concentration of glia cells relative to the axonal volume. The positive correlation that was found between MSSS, and the glutamate and creatine concentrations in NAWM, in combination with a complete lack of correlation between lesion load and MSSS, suggests that altered glutamate metabolism, and subsequent demyelination and gliosis, is an important pathophysiological mechanism in MS.

    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-54726 (URN)
    Available from: 2010-04-07 Created: 2010-04-07 Last updated: 2019-06-14Bibliographically approved
    4. Separation of advanced from mild fibrosis in diffuse liver disease using 31P magnetic resonance spectroscopy
    Open this publication in new window or tab >>Separation of advanced from mild fibrosis in diffuse liver disease using 31P magnetic resonance spectroscopy
    Show others...
    2008 (English)In: European Journal of Radiology, ISSN 0720-048X, E-ISSN 1872-7727, Vol. 66, no 2, p. 313-320Article in journal (Refereed) Published
    Abstract [en]

    31P-MRS using DRESS was used to compare absolute liver metabolite concentrations (PME, Pi, PDE, γATP, αATP, βATP) in two distinct groups of patients with chronic diffuse liver disorders, one group with steatosis (NAFLD) and none to moderate inflammation (n = 13), and one group with severe fibrosis or cirrhosis (n = 16). All patients underwent liver biopsy and extensive biochemical evaluation. A control group (n = 13) was also included. Absolute concentrations and the anabolic charge, AC = {PME}/({PME} + {PDE}), were calculated.

    Comparing the control and cirrhosis groups, lower concentrations of PDE (p = 0.025) and a higher AC (p < 0.001) were found in the cirrhosis group. Also compared to the NAFLD group, the cirrhosis group had lower concentrations of PDE (p = 0.01) and a higher AC (p = 0.009). No significant differences were found between the control and NAFLD group. When the MRS findings were related to the fibrosis stage obtained at biopsy, there were significant differences in PDE between stage F0–1 and stage F4 and in AC between stage F0–1 and stage F2–3.

    Using a PDE concentration of 10.5 mM as a cut-off value to discriminate between mild, F0–2, and advanced, F3–4, fibrosis the sensitivity and specificity were 81% and 69%, respectively. An AC cut-off value of 0.27 showed a sensitivity of 93% and a specificity of 54%.

    In conclusion, the results suggest that PDE is a marker of liver fibrosis, and that AC is a potentially clinically useful parameter in discriminating mild fibrosis from advanced.

    Place, publisher, year, edition, pages
    Elsevier, 2008
    Keywords
    Absolute quantification; Phosphorus; MRS; Steatosis; In vivo
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-43125 (URN)10.1016/j.ejrad.2007.06.004 (DOI)000256140900026 ()17646074 (PubMedID)71944 (Local ID)71944 (Archive number)71944 (OAI)
    Projects
    NILB
    Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2019-06-14Bibliographically approved
    5. Quantitative Abdominal Fat Estimation Using MRI
    Open this publication in new window or tab >>Quantitative Abdominal Fat Estimation Using MRI
    Show others...
    2008 (English)In: Proceedings - International Conference on Pattern Recognition, IEEE Computer Society, 2008, p. 1-4Conference paper, Published paper (Refereed)
    Abstract [en]

    This paper introduces a new method for automaticquantification of subcutaneous, visceral and nonvisceralinternal fat from MR-images acquired usingthe two point Dixon technique in the abdominal region.The method includes (1) a three dimensionalphase unwrapping to provide water and fat images, (2)an image intensity inhomogeneity correction, and (3) amorphon based registration and segmentation of thetissue. This is followed by an integration of the correctedfat images within the different fat compartmentsthat avoids the partial volume effects associated withtraditional fat segmentation methods. The method wastested on 18 subjects before and after a period of fastfoodhyper-alimentation showing high stability andperformance in all analysis steps.

    Place, publisher, year, edition, pages
    IEEE Computer Society, 2008
    Series
    International Conference on Pattern Recognition, ISSN 1051-4651
    National Category
    Medical Laboratory and Measurements Technologies
    Identifiers
    urn:nbn:se:liu:diva-21108 (URN)10.1109/ICPR.2008.4761764 (DOI)000264729001041 ()978-1-4244-2174-9 (ISBN)978-1-4244-2175-6 (ISBN)
    Conference
    19th International Conference on Pattern Recognition, Tampa FL USA, 8-11 Dec. 2008
    Available from: 2009-09-29 Created: 2009-09-29 Last updated: 2019-06-14Bibliographically approved
    6. Quantifying differences in hepatic uptake of the liver specific contrast agents Gd-EOB-DTPA and Gd-BOPTA: a pilot study
    Open this publication in new window or tab >>Quantifying differences in hepatic uptake of the liver specific contrast agents Gd-EOB-DTPA and Gd-BOPTA: a pilot study
    Show others...
    2012 (English)In: European Radiology, ISSN 0938-7994, E-ISSN 1432-1084, Vol. 22, no 3, p. 642-653Article in journal (Refereed) Published
    Abstract [en]

    Objectives   To develop and evaluate a procedure for quantifying the hepatocyte-specific uptake of Gd-BOPTA and Gd-EOB-DTPA using dynamic contrast-enhanced (DCE) MRI. Methods   Ten healthy volunteers were prospectively recruited and 21 patients with suspected hepatobiliary disease were retrospectively evaluated. All subjects were examined with DCE-MRI using 0.025 mmol/kg of Gd-EOB-DTPA. The healthy volunteers underwent an additional examination using 0.05 mmol/kg of Gd-BOPTA. The signal intensities (SI) of liver and spleen parenchyma were obtained from unenhanced and enhanced acquisitions. Using pharmacokinetic models of the liver and spleen, and an SI rescaling procedure, a hepatic uptake rate, K Hep, estimate was derived. The K Hep values for Gd-EOB-DTPA were then studied in relation to those for Gd-BOPTA and to a clinical classification of the patient’s hepatobiliary dysfunction. Results   K Hep estimated using Gd-EOB-DTPA showed a significant Pearson correlation with K Hep estimated using Gd-BOPTA (r = 0.64; P < 0.05) in healthy subjects. Patients with impaired hepatobiliary function had significantly lower K Hep than patients with normal hepatobiliary function (K Hep = 0.09 ± 0.05 min-1 versus K Hep = 0.24 ± 0.10 min−1; P < 0.01). Conclusions   A new procedure for quantifying the hepatocyte-specific uptake of T 1-enhancing contrast agent was demonstrated and used to show that impaired hepatobiliary function severely influences the hepatic uptake of Gd-EOB-DTPA. Key Points   • The liver uptake of contrast agents may be measured with standard clinical MRI.Calculation of liver contrast agent uptake is improved by considering splenic uptake.Liver function affects the uptake of the liver-specific contrast agent Gd-EOB-DTPA.Hepatic uptake of two contrast agents (Gd-EOB-DTPA, Gd-BOPTA) is correlated in healthy individuals.This method can be useful for determining liver function, e.g. before hepatic surgery

    Place, publisher, year, edition, pages
    Springer Berlin/Heidelberg, 2012
    Keywords
    Gadolinium ethoxybenzyl diethylenetriaminepentaacetic acid – Gadobenate Dimeglumine – Dynamic contrast-enhanced MRI – Pharmacokinetics – Liver
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-73624 (URN)10.1007/s00330-011-2302-4 (DOI)000299768000018 ()21984449 (PubMedID)
    Funder
    Swedish Research Council, VR/M 2007-2884Medical Research Council of Southeast Sweden (FORSS), 12621Linköpings universitet
    Note

    The previous status of this article was Manuscript and the working titles was Liver Specific Gd-EOB-DTPA vs. Gd-BOPTA Uptake in Healthy Subjects: A Novel and Quantitative MRI Analysis of Hepatic Uptake and Vascular Enhancement and Hepatic Uptake of Gd-EOB-DTPA in Patients with Varying Degree of Hepatobiliary Disease.

    Available from: 2012-01-10 Created: 2012-01-10 Last updated: 2019-06-14
  • 18.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Cohen, L
    Lund, Eva
    Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Department of Medical and Health Sciences, Radiology. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Absolute quantification of 31P muscle MRS using B1-field mapping2005Conference paper (Other academic)
  • 19.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Dahlström, Nils
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Radiology . Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Brismar, T
    Sandström, Per
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Clinical and Experimental Medicine, Surgery . Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Surgery in Östergötland.
    Kihlberg, Johan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Smedby, Örjan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Medical Radiology. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology UHL. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics . Linköping University, Department of Medicine and Health Sciences, Radiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Radiation Physics. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    A liver function test based on measurement of liver-specific contrast agent uptake2008In: Proceedings 16th Scientific meeting, ISMRM,2008, 2008Conference paper (Other academic)
    Abstract [en]

      

  • 20.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Dahlström, Nils
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Sandström, Per
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Clinical and Experimental Medicine, Surgery.
    Brismar, Torkel
    Department of Clinical Science, Intervention and Technology at Karolinska Institutet, Division of Medical Imaging and Technology, Karolinska University Hospital in Huddinge, Stockholm, Sweden.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Quantifying differences in hepatic uptake of the liver specific contrast agents Gd-EOB-DTPA and Gd-BOPTA: a pilot study2012In: European Radiology, ISSN 0938-7994, E-ISSN 1432-1084, Vol. 22, no 3, p. 642-653Article in journal (Refereed)
    Abstract [en]

    Objectives   To develop and evaluate a procedure for quantifying the hepatocyte-specific uptake of Gd-BOPTA and Gd-EOB-DTPA using dynamic contrast-enhanced (DCE) MRI. Methods   Ten healthy volunteers were prospectively recruited and 21 patients with suspected hepatobiliary disease were retrospectively evaluated. All subjects were examined with DCE-MRI using 0.025 mmol/kg of Gd-EOB-DTPA. The healthy volunteers underwent an additional examination using 0.05 mmol/kg of Gd-BOPTA. The signal intensities (SI) of liver and spleen parenchyma were obtained from unenhanced and enhanced acquisitions. Using pharmacokinetic models of the liver and spleen, and an SI rescaling procedure, a hepatic uptake rate, K Hep, estimate was derived. The K Hep values for Gd-EOB-DTPA were then studied in relation to those for Gd-BOPTA and to a clinical classification of the patient’s hepatobiliary dysfunction. Results   K Hep estimated using Gd-EOB-DTPA showed a significant Pearson correlation with K Hep estimated using Gd-BOPTA (r = 0.64; P < 0.05) in healthy subjects. Patients with impaired hepatobiliary function had significantly lower K Hep than patients with normal hepatobiliary function (K Hep = 0.09 ± 0.05 min-1 versus K Hep = 0.24 ± 0.10 min−1; P < 0.01). Conclusions   A new procedure for quantifying the hepatocyte-specific uptake of T 1-enhancing contrast agent was demonstrated and used to show that impaired hepatobiliary function severely influences the hepatic uptake of Gd-EOB-DTPA. Key Points   • The liver uptake of contrast agents may be measured with standard clinical MRI.Calculation of liver contrast agent uptake is improved by considering splenic uptake.Liver function affects the uptake of the liver-specific contrast agent Gd-EOB-DTPA.Hepatic uptake of two contrast agents (Gd-EOB-DTPA, Gd-BOPTA) is correlated in healthy individuals.This method can be useful for determining liver function, e.g. before hepatic surgery

  • 21.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Dahlström, Nils
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Sandström, P
    Brismar, Torkel
    Karolinska institutet.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Department of Medical and Health Sciences, Radiology. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Faculty of Health Sciences.
    A liver function test based on measurement of liver specific contrast agent uptake2008Conference paper (Other academic)
  • 22.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Dahlström, Nils
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Sandström, P
    Freij, Anna
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Brismar, Torkel
    Karolinska institutet.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    The hepatic uptake of Gd-EOB-DTPA is strongly affected by the hepatobiliary function2009Conference paper (Other academic)
  • 23.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Dahlström, Nils
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Sandström, P
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Brismar, Torkel
    Karolinska institutet.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    The hepatic uptake of Gd-EOB-DTPA is strongly correlated with the uptake of Gd-BOPTA2010Conference paper (Other academic)
  • 24.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics . Linköping University, Faculty of Health Sciences.
    Jacek, J.
    Aalto, Anne
    Linköping University, Department of Medicine and Health Sciences, Radiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging.
    Grönqvist, A.
    Smedby, Örjan
    Linköping University, Department of Medicine and Health Sciences, Radiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging.
    Landtblom, Anne-Marie
    Linköping University, Department of Clinical and Experimental Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Local Health Care Services in Central Östergötland, Department of Neurology.
    Lundberg, Peter
    Linköping University, Department of Medicine and Health Sciences, Radiation Physics . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Radiation Physics.
    Is Increased Normal White Matter Glutamate Concentration a Precursor of Gliosis and Disease Progression in Multiple Sclerosis?Manuscript (preprint) (Other academic)
    Abstract [en]

    Background: The multiple sclerosis (MS) severity scale (MSSS) is a new scoring procedure to clinically characterize the rate of disease progression in MS, rather than the disability of the patient. The latter is often characterized using the expanded disability status score (EDSS). The progress rate of the disease, magnetic resonance imaging (MRI)-based measures of ‘black hole lesions’, and atrophy have all been shown to be predicted well by MSSS. In this study we investigated possible relationships between brain metabolite concentrations, measured using proton (1H) magnetic resonance spectroscopy (MRS), and MSSS.

    Purpose: Our aims were to quantitatively investigate the metabolite concentrations in normal appearing white matter (NAWM) in MS-patients, and also to investigate possible correlations between disease subtype, EDSS and MSSS and metabolite concentrations. To minimize the interference from lesion contamination in the MRS measurement, a refined novel analysis procedure had to be developed in order to correct for partial volume effects in tissues near plaques.

    Materials and Methods: Forty eight patients with Clinically Definite MS (CDMS), and 18 normal control subjects (NC) were included retrospectively from several MRS studies. T1, T2, and proton density MRI, and four white matter 1H MRS single voxel PRESS (Point-REsolved SpectroScopy) spectra were acquired in each subject using echo time 35 ms and repetition time 6000 ms on a 1.5 T MR-scanner. A total of 108 examinations were acquired from patients and 18 from NC. Absolutely quantified NAWM metabolite concentrations were determined using a mixed linear model (MLM) analysis that included the degree of T2 lesion contamination in each voxel. The T2 lesion contamination of the MRS voxels was also used as an estimate of ‘lesion load’ at each exam. The corrected metabolite concentrations were then correlated with clinical measures of the patients’ status, including EDSS and MSSS.

    Results: The axonal marker N-acetyl aspartate (NAA) did not correlate with either EDSS or MSSS. The glial cell markers creatine and myo-inositol correlated positively with EDSS. Creatine and glutamate correlated positively with MSSS. The ‘estimated lesion load’ correlated positively not only with EDSS, but also with the number of bouts since disease onset. Importantly, it did not correlate with MSSS.

    Conclusion: The most interesting findings were the unchanged concentrations of NAA, and the concomitant increase of creatine and myo-inositol during the course of disease progression in MSpatients. These not only indicated a constant axonal density, but also that a simultaneous development of gliosis occurred. These processes are most likely linked to demyelination, as well as development of white matter atrophy, a process in which the demyelinated volume is replaced by the surrounding tissue leading to a net loss of white matter. As a consequence of this process, axons in NAWM are probably damaged, which leads to a higher concentration of glia cells relative to the axonal volume. The positive correlation that was found between MSSS, and the glutamate and creatine concentrations in NAWM, in combination with a complete lack of correlation between lesion load and MSSS, suggests that altered glutamate metabolism, and subsequent demyelination and gliosis, is an important pathophysiological mechanism in MS.

  • 25.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Jarowski, J
    Gustavsson, M
    Tisell, Anders
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL.
    Gladigau, D
    Landtblom, Anne-Marie
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Clinical and Experimental Medicine, Psychiatry. Östergötlands Läns Landsting, Sinnescentrum, Department of Neurosurgery UHL.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Betainterferon treatment: Absolute quantification of white matter metabolites in patients with multiple sclerosis2008Conference paper (Other academic)
  • 26.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Jaworski, J,
    Östergötlands Läns Landsting, Local Health Care Services in Central Östergötland, Department of Neurology.
    Aalto, Anne
    Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Grönkvist, Anders
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Health Sciences.
    Tisell, Anders
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Faculty of Health Sciences.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Landtblom, Anne-Marie
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Clinical and Experimental Medicine, Neurology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Local Health Care Services in Central Östergötland, Department of Neurology. Östergötlands Läns Landsting, Local Health Care Services in West Östergötland, Department of Medical Specialist in Motala.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Is Increased normal White Matter Glutamate Concentrations a Precursor of Gliosis and Disease Progression in Multiple Sclerosis?2011In: Internationell Society for Magnetic Resonance in Medicin, 2011, 2011, p. 4089-4089Conference paper (Refereed)
  • 27.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Johansson, A
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Water-fat shift displacement artifact correction in two-point Dixon imaging2008Conference paper (Other academic)
  • 28.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Health Sciences.
    Johansson, Andreas
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Rydell, Joakim
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Health Sciences. Linköping University, Department of Medical and Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    Nyström, Fredrik H.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    Borga, Magnus
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Quantification of abdominal fat accumulation during hyperalimentation using MRI2009In: Proceedings of the ISMRM Annual Meeting (ISMRM'09), 2009, Berkeley, CA, USA: International Society for Magnetic Resonance in Medicine , 2009, p. 206-Conference paper (Other academic)
    Abstract [en]

    There is an increasing demand for imaging methods that can be used for automatic, accurate and quantitative determination of the amounts of abdominal fat. Such methods are important as they will allow the evaluation of some of the risk factors underlying the ’metabolic syndrome’. The metabolic syndrome is becoming common in large parts of the world, and it appears that a dominant risk factor for developing this syndrome is abdominal obesity. Subjects that are afflicted with the metabolic syndrome are exposed to a high risk for developing a large range of diseases such as type 2 diabetes, cardiac failure, and stroke. The aim of this work

  • 29.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Linge, Jennifer
    Advanced MR Analytics AB, Linköping, Sweden.
    West, Janne
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Medicine and Health Sciences.
    Bell, Jimmy
    Westminster University, London, UK.
    Borga, Magnus
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering.
    Body Composition Profiling using MRI - Normative Data for Subjects with Cardiovascular Disease Extracted from the UK Biobank Imaging Cohort2016Conference paper (Other academic)
    Abstract [en]

    PURPOSE

    To describe the distribution of MRI-derived body composition measurements in subjects with cardiovascular disease (CVD) compared to subjects without any history of CVD.

    METHOD AND MATERIALS

    1864 males and 2036 females with an age range from 45 to 78 years from the UK Biobank imaging study were included in the study. Visceral adipose tissue volume normalized with height2 (VATi), total abdominal adipose tissue volume normalized with height2 (ATATi), total lean thigh muscle volume normalized with body weight (muscle ratio) and liver proton density fat fraction (PDFF) were measured with a 2-point Dixon imaging protocol covering neck to knee and a 10-point Dixon single slice protocol positioned within the liver using a 1.5T MR-scanner (Siemens, Germany). The MR-images were analyzed using AMRA® Profiler research (AMRA, Sweden). 213 subjects with history of cardiovascular events (angina, heart attack, or stroke) (event group) were age and gender matched to subjects with high blood pressure (HBP group), and subjects without CVD (controls).Kruskal-Wallis and Mann-Whitney U tests were used to test the observed differences for each measurement and group without correction for multiple comparisons.

    RESULTS

    VATi in the event group was 1.73 (1.13 - 2.32) l/m2 (median, 25%-75% percentile) compared to 1.68 (1.19 - 2.23) in the HBP group, and 1.30 (0.82-1.87) in the controls. ATATi in the event group was 4.31 (2.90-5.39) l/m2 compared to 4.05 (3.07-5.12) in the HBP group, and 3.48 (2.48-4.61) in the controls. Muscle ratio in the event group was 0.13 (0.12 - 0.15) l/kg as well as in the HBP group, compared to 0.14 (0.12 - 0.15) in the controls. Liver PDFF in the event group was 2.88 (1.77 - 7.72) % compared to 3.44 (2.04-6.18) in the HBP group, and 2.50 (1.58 - 5.15) in the controls. Kruskal-Wallis test showed significant differences for all variables and group comparisons (p<0.007). The post hoc test showed significant differences comparing the controls to both the event group and the HBP group. These were more significant for VATi and ATATi (p<10-4) than for muscle ratio and PDFF (p<0.03). No significant differences were detected between the event group and the HBP group.

    CONCLUSION

    Cardiovascular disease is strongly associated with high VATi, liver fat, and ATATi, and with low muscle ratio.

    CLINICAL RELEVANCE/APPLICATION

    The metabolic syndrome component in CVD can be effectively described using MRI-based body composition profiling.

  • 30.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Linge, Jennifer
    Advanced MR Analytics AB, Linköping, Sweden.
    West, Janne
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Medicine and Health Sciences.
    Bell, Jimmy
    Westminster University, London, UK.
    Borga, Magnus
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Body Composition Profiling using MRI - Normative Data for Subjects with Diabetes Extracted from the UK Biobank Imaging Cohort2016Conference paper (Other academic)
    Abstract [en]

    PURPOSE

    To describe the distribution of MRI derived body composition measurements in subjects with diabetes mellitus (DM) compared to subjects without diabetes.

    METHOD AND MATERIALS

    3900 subjects (1864 males and 2036 females) from the UK Biobank imaging study were included in the study. The age range was 45 to 78 years. Visceral adipose tissue volume normalized with height2 (VATi), total abdominal adipose tissue volume normalized with height2 (ATATi), total lean thigh muscle volume normalized with body weight (muscle ratio) and liver proton density fat fraction (PDFF) were measured with a 6 minutes 2-point Dixon imaging protocol covering neck to knee and a 10-point Dixon single axial slice protocol positioned within the liver using a 1.5T MR-scanner (Siemens, Germany). The MR-images were analyzed using AMRA® Profiler research (AMRA, Sweden). 194 subjects with clinically diagnosed DM (DM group) were age and gender matched to subjects without DM (control group). For each variable and group, the median, 25%-percentile and 75%-percentile was calculated. Mann-Whitney U test was used to test the observed differences.

    RESULTS

    VATi in the DM group was 2.13 (1.43-2.62) l/m2 (median, 25% - 75% percentile) compared to 1.32 (0.86 - 1.79) l/m2 in the control group. ATATi in the DM group was 4.94 (3.86-6.19) l/m2 compared to 3.40 (2.56 - 4.70) l/m2 in the control group. Muscle ratio in the DM group was 0.13 (0.11 - 0.14) l/kg compared to 0.14 (0.12 - 0.15) l/kg in the control group. Liver PDFF in the DM group was 7.23 (2.68 - 13.26) % compared to 2.49 (1.53 - 4.73) % in the control group. Mann-Whitney U test detected significant differences between the DM group and the control group for all variables (p<10-5).

    CONCLUSION

    DM is strongly associated with high visceral fat, liver fat, and total abdominal fat, and low muscle ratio.

    CLINICAL RELEVANCE/APPLICATION

    Body composition profiling shows high potential to provide direct biomarkers to improve characterization and early diagnosis of DM.

  • 31.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Motsch, Johann
    Clinical Research, University of Heidelberg, Heidelberg, Germany.
    van der Meulen, Jan
    Clinical Epidemiology, Department of Health Services Research and Policy, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London,UK.
    Clinical News: Body composition study reveals link between specific fat distributions and metabolic diseases2018In: British Journal of Hospital Medicine, ISSN 1750-8460, Vol. 79, no 6, p. 308-308Article in journal (Other academic)
  • 32.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Romu, Thobias
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Karlsson, Anette
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Borga, Magnus
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    High resolution isotropic whole-­‐body symmetrically sampled two point Dixon acquisition imaging at 3T2012In: ISMRM workshop on Fat-­‐Water Separation: Insights, Applications & Progress in MRI, 2012Conference paper (Other academic)
  • 33.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Romu, Thobias
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences.
    Gjellan, Solveig
    Linköping University, Department of Medical and Health Sciences, Internal Medicine. Linköping University, Faculty of Health Sciences.
    Zanjani, Sepehr
    Linköping University, Department of Medical and Health Sciences, Internal Medicine. Linköping University, Faculty of Health Sciences.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping.
    Nyström, Fredrik
    Linköping University, Department of Medical and Health Sciences, Internal Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Centre, Department of Endocrinology.
    Borga, Magnus
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Validation of whole-­‐body adipose tissue quantification using air displacement plethysmometry2012In: ISMRM workshop on Fat-­‐Water Separation: Insights, Applications & Progress in MRI, 2012Conference paper (Other academic)
  • 34.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Warntjes, Marcel
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Whole volume three dimensional B1 mapping in 10 second2008Conference paper (Other academic)
  • 35.
    Dahlström, Nils
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Brismar, Torkel
    Karolinska institutet.
    Sandström, P
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Leverfunktionsundersökning med leverspecifikt MR-kontrastmedel2008Conference paper (Other academic)
  • 36.
    Dahlström, Nils
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Quick, Petter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Forsgren, Mikael
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Persson, Anders
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Dual-Energy CT Detects Standard-Dose Gd-EOB-DTPA in the Hepatobiliary and Renal Systems of Patients Having Undergone Liver MRI2012Conference paper (Other academic)
  • 37.
    Dahlström, Nils
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Sandström, Per
    Linköping University, Department of Clinical and Experimental Medicine, Surgery. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Surgery in Östergötland.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Brismar, Torkel
    Karolinska Huddinge.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Quantified hepatobiliary Gd-EOB-DTPA uptake rate reflects hepatobiliary function in patients2011Conference paper (Refereed)
  • 38.
    Engström, Maria
    et al.
    Linköping University, Department of Medicine and Health Sciences, Radiology. Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Faculty of Health Sciences.
    Tisell, Anders
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL. Linköping University, Faculty of Health Sciences.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Karlsson, T
    Vigren, P
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping.
    Landtblom, Anne-Marie
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Clinical and Experimental Medicine, Psychiatry. Östergötlands Läns Landsting, Sinnescentrum, Department of Neurosurgery UHL. Linköping University, Faculty of Health Sciences.
    Kleine-Levin Syndrom (KLS) – A bipolar disorder?2009Conference paper (Other academic)
  • 39.
    Erlingsson, Styrbjörn
    et al.
    Linköping University, Department of Medical and Health Sciences, Internal Medicine. Linköping University, Faculty of Health Sciences.
    Herard, Sebastian
    Linköping University, Department of Medical and Health Sciences, Internal Medicine. Linköping University, Faculty of Health Sciences.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Lindström, Torbjörn
    Linköping University, Department of Medical and Health Sciences, Internal Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medicine, Department of Endocrinology and Gastroenterology UHL.
    Länne, Toste
    Linköping University, Department of Medical and Health Sciences, Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Borga, Magnus
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Nyström, Fredrik
    Linköping University, Department of Medical and Health Sciences, Internal Medicine. Linköping University, Faculty of Health Sciences.
    Men develop more intraabdominal obesity and signs of the metabolic syndrome after hyperalimentation than women2009In: Metabolism: Clinical and Experimental, ISSN 0026-0495, E-ISSN 1532-8600, Vol. 58, no 7, p. 995-1001Article in journal (Refereed)
    Abstract [en]

    We prospectively studied the effects of fast food-based hyperalimentation on insulin sensitivity and components of the metabolic syndrome and analyzed this with respect to sex. Twelve nonobese men and 6 nonobese women (26 +/- 6.6 years old), and an age-matched control group were recruited. Subjects in the intervention group aimed for 5% to 15% weight increase by doubling their regular caloric intake based on at least 2 fast food meals a day while also adopting a sedentary lifestyle for 4 weeks (andlt;5000 steps a day). Weight of Subjects in the intervention group increased from 67.6 +/- 9.1 to 74.0 +/- 11 kg (P andlt;.001), with no sex difference with regard to this or with respect to changes of total abdominal fat volumes or waist circumferences. Fasting insulin (men: before, 3.8 +/- 1.7 mu U/mL, after, 7.4 +/- 3.1 mu U/mL; P=.004; women: before, 4.9 +/- 2.3 mu U/mL; after, 5.9 +/- 2.8 mu U/mL; P =.17), systolic blood pressure (men: before, 117 +/- 13 mm Hg; after, 127 +/- 9.1 mm Hg; P =.002; women: before, 102 +/- 5.1 mm Hg; after, 98 +/- 5.4 mm Hg; P =.39), serum low-density lipoprotein cholesterol, and apolipoprotein B increased only in the men of the intervention group. The sex differences in the metabolic responses to the intervention were linked to a considerable difference in the fat accumulation pattern; 41.4% +/- 9.2% of the increase of the fat volume in the abdominal region was accumulated intraabdominally in men and 22.7 +/- 6.5% in women (P andlt;.0001). This Study thus showed that women are protected, compared with men, against developing intraabdominal obesity when adopting a standardized obesity-provoking lifestyle. Our findings suggest that it is not different lifestyles and/or behaviors that underlie the fact that men have a higher cardiovascular risk at the same level of percentage of body fat than women.

  • 40.
    Forsgren, Mikael
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Bengtsson, Ann
    Linköping University, Department of Clinical and Experimental Medicine, Rheumatology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Rheumatology.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Sören, Birgitta
    Linköping University, Department of Medical and Health Sciences, Physiotherapy. Linköping University, Faculty of Health Sciences.
    Brandejsky, Vaclav
    Depts Clinical Research and Radiology, University Bern, Bern, Switzerland.
    Lund, Eva
    Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    31P MRS as a Potential Biomarker for Fibromyalgia2012In: Proceedings of the 20th Annaal Meeting & Exhibition, 5-11 May, Melbourne, Australia, 2012, p. 1493-1493Conference paper (Refereed)
    Abstract [en]

    Major clinical symptoms in fibromyalgia (FM) are muscle pain, stiffness and fatigue. Studies have shown reduced voluntary strength and exercise capacity, lower endurance and more muscular pain even at low workload. An impaired muscle energy metabolism has therefore been proposed as a result of the disease. An earlier study using magnetic resonance spectroscopy (MRS) showed that at maximal dynamic and static contractions the concentration of inorganic phosphate was lower in FM [1]. A decrease in ATP, ADP and PCr and an increase in AMP and creatine was found in FM biopsies [2]. The purpose of this study was to non-invasively analyze the quantitative content of  phosphagens in the resting muscle in FM in comparison to healthy controls using 31P MRS of the quadriceps muscle.

  • 41.
    Forsgren, Mikael
    et al.
    Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Cedersund, Gunnar
    Linköping University, Department of Clinical and Experimental Medicine, Cell Biology. Linköping University, Faculty of Health Sciences.
    Dahlström, Nils
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Brismar, Torkel
    Department of Radiology, Karolinska University Hospital, Stockholm, Sweden.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    The First Human Whole Body Pharmacokinetic Minimal Model for the Liver Specific Contrast Agent Gd-EOB-DTPA2011In: Proc. Intl. Soc. Mag. Reson. Med. 19 (2011), 2011, p. 3016-3016Conference paper (Refereed)
  • 42.
    Forsgren, Mikael
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Cedersund, Gunnar
    Linköping University, Department of Clinical and Experimental Medicine, Cell Biology. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    AdHoc Constraints on Complex Liver DCE-MRI Models Can Reduce Parameter Uncertainty2012Conference paper (Other academic)
  • 43.
    Forsgren, Mikael
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dahlström, Nils
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Cedersund, Gunnar
    Linköping University, Department of Clinical and Experimental Medicine, Division of Cell Biology. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    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. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Physiologically Realistic and Validated Mathematical Liver Model Revels Hepatobiliary Transfer Rates for Gd-EOB-DTPA Using Human DCE-MRI Data2014In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 9, no 4, p. 0095700-Article in journal (Refereed)
    Abstract [en]

    Objectives: Diffuse liver disease (DLD), such as non-alcoholic fatty liver disease (NASH) and cirrhosis, is a rapidly growing problem throughout the Westernized world. Magnetic resonance imaging (MRI), based on uptake of the hepatocyte-specific contrast agent (CA) Gd-EOB-DTPA, is a promising non-invasive approach for diagnosing DLD. However, to fully utilize the potential of such dynamic measurements for clinical or research purposes, more advanced methods for data analysis are required. Methods: A mathematical model that can be used for such data-analysis was developed. Data was obtained from healthy human subjects using a clinical protocol with high spatial resolution. The model is based on ordinary differential equations and goes beyond local diffusion modeling, taking into account the complete system accessible to the CA. Results: The presented model can describe the data accurately, which was confirmed using chi-square statistics. Furthermore, the model is minimal and identifiable, meaning that all parameters were determined with small degree of uncertainty. The model was also validated using independent data. Conclusions: We have developed a novel approach for determining previously undescribed physiological hepatic parameters in humans, associated with CA transport across the liver. The method has a potential for assessing regional liver function in clinical examinations of patients that are suffering of DLD and compromised hepatic function.

  • 44.
    Forsgren, Mikael
    et al.
    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.
    Dahlström, Nils
    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 Diagnostics, Department of Radiology in Linköping.
    Karlsson, Markus
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, The Institute of Technology. Linköping University, Department of Clinical and Experimental Medicine, Division of Neuroscience.
    Dahlqvist Leinhard, Olof
    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.
    Smedby, Örjan
    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 Diagnostics, Department of Radiology in Linköping.
    Cedersund, Gunnar
    Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    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. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Whole Body Mechanistic Minimal Model for Gd-EOB-DTPA Contrast Agent Pharmacokinetics in Evaluation of Diffuse Liver Disease2014Conference paper (Other academic)
    Abstract [en]

    Purpose: Aiming for non-invasive diagnostic tools to decrease the need for biopsy in diffuse liver disease and to quantitatively describe liver function, we applied a mechanistic pharmacokinetic modelling analysis of liver MRI with Gd-EOB-DTPA. This modelling method yields physiologically relevant parameters and was compared to previously developed methods in a patient group with diffuse liver disease. Materials and Methods: Using data from healthy volunteers undergoing liver MRI, an identifiable mechanistic model was developed, based on compartments described by ordinary differential equations and kinetic expressions, and validated with independent data including Gd-EOB-DTPA concentration measurements in blood samples. Patients (n=37) with diffuse liver disease underwent liver biopsy and MRI with Gd-EOB-DTPA. The model was used to derive pharmacokinetic parameters which were then compared with other quantitative estimates in their ability to separate mild from severe liver fibrosis. Results: The estimations produced by the mechanistic model allowed better separation between mild and severe fibrosis than previously described methods for quantifying hepatic Gd-EOB-DTPA uptake. Conclusions: With a mechanistic pharmacokinetic modelling approach, the estimation of liver uptake function and its diagnostic information can be improved compared to current methods.

  • 45.
    Forsgren, Mikael
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Ekstedt, Mattias
    Linköping University, Department of Clinical and Experimental Medicine, Gastroenterology and Hepatology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Endocrinology and Gastroenterology UHL.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Andregård, O.
    Dahlström, Nils
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Kechagias, Stergios
    Linköping University, Department of Medical and Health Sciences, Internal Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Endocrinology and Gastroenterology UHL.
    Almer, Sven
    Linköping University, Department of Clinical and Experimental Medicine, Gastroenterology and Hepatology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Endocrinology and Gastroenterology UHL.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences.
    Prospective evaluation of liver steatosis comparing stereological point-counting biopsy analysis and 1H MRS2012Conference paper (Other academic)
  • 46.
    Forsgren, Mikael F
    et al.
    Linköping University. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Norén, Bengt
    Linköping University, Department of Medical and Health Sciences, Radiology. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Kechagias, Stergios
    Linköping University, Department of Medical and Health Sciences, Internal Medicine. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Endocrinology and Gastroenterology UHL. Linköping University, Faculty of Health Sciences.
    Nyström, Fredrik
    Linköping University, Department of Medical and Health Sciences, Physiology. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Faculty of Health Sciences.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Department of Medical and Health Sciences, Radiology. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    On the Evaluation of 31P MRS Human Liver Protocols2010Conference paper (Other academic)
  • 47.
    Forsgren, Mikael
    et al.
    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.
    Norén, Bengt
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Kihlberg, Johan
    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 Diagnostics, Department of Radiology in Linköping.
    Dahlqvist Leinhard, Olof
    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.
    Kechagias, Stergios
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Gastroentorology.
    Lundberg, Peter
    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. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Comparing 2D and 3D Magnetic Resonance Elastography Techniques in a Clinical Setting: Initial Experiences2014Conference paper (Other academic)
    Abstract [en]

    Purpose: It has been shown that liver fibrosis, and even cirrhosis, may be reversible in humans. For this reason there is a great need for the imminent introduction of non-invasive and clinically useful methods in order to monitor fibrosis in patients [1, 2]. A body of evidence points to the fact that MRE is a highly useful candidate towards this end [3]. However, before using such techniques more widely, it is important to verify that comparable physical measures are provided by alternative and clinically relevant MRE approaches. The aim of this pilot study was to compare 2D and 3D MRE, also known as MR Rheology, using a commercially available 2D system, with an acoustic transducer, and 3D MRE research system, with an electromagnetic transducer, with respect to liver stiffness and elasticity in patients with diffuse or suspected diffuse liver disease. Materials and Methods: Seven patients, referred to our hospital for evaluation of elevated serum alanine aminotransferase (ALT) and/or alkaline phosphatase (ALP) levels but without signs of cirrhosis on physical examination, were recruited from a previous study [4], and examined in the course of one day. Fibrosis staging from prior biopsy were gained from [4], see Table 1. The 3D MRE method included an active electromagnetic transducer generating waves at 56 Hz, and a 1.5 T Philips Achieva MR-scanner, with a phased array body coil (Sense TorsoXL, all 16 coil elements), GRE sequence parameters include; FOV = 320x256 mm2, matrix = 80x38, slice thickness = 4 mm, # slices = 9, FA = 15°, TR = 112 ms, TE = 9.21 ms, SENSE = 2. The 2D MRE method included a passive acoustic transducer generating waves at 60 Hz, and a 1.5 T GE 450W MR-scanner, with a phased array body coil (HD8 Torso, all 8 coil elements), GRE sequence parameters include; FOV = 440x440 mm2, matrix = 256x64, slice thickness = 10 mm, # slices = 4, FA = 30°, TR = 50 ms, TE = 21.7 ms, ASSET = 2. The transducers were on both systems placed on the anterior chest wall to the right of xiphoid process (patient in a supine position), the time between each MRE acquisition was dependent on how long it took to transfer the patient between the two MR systems in the hospital (<10 min) A region of interest (ROI) was placed in an appropriate single 10 mm slice acquired using the GE MR-scanner. A corresponding ROI for the Philips system, covering the same anatomical region, was placed over three slices (4 mm thickness each). This yielded a total cranio-caudal coverage of the ROIs equal to 10 mm (on the GE data) and 12 mm (on the Philips data). The mean and standard deviations of the stiffness (GE), elasticity (Philips) and Gabs,Elastic (Philips) were calculated. Gabs,Elastic is the absolute value of the shear modulus, which in principle is equivalent to the viscoelastic property, shear stiffness. In the 3D method the shear waves were obtained by applying the curl operator and using the Voigt rheological model to obtain shear elasticity maps [5, 6]. In the 2D method the GE system provided the stiffness maps. Statistics was performed using Mathematica 9. ROI drawing and quantification of the data from the GE system was performed using Sectra PACS IDS7, and ROI drawing and quantification of the data from the Philips system was performed using a custom software package implemented in ROOT, generously provided by R. Sinkus (Kings College, London, UK). Results: The measured values are presented in Table 1. Both elasticity and Gabs,Elastic correlates well with the stiffness measurement carried out in the GE system (Fig. 1), as was shown by the elasticity and stiffness correlation R2 = 0.96 (P < 0.001) slope = 1.08 (P < 0.001), intercept = 0.61 kPa (P = 0.08), Gabs,Elastic and stiffness correlation R2 = 0.96 (P < 0.001), slope = 0.95 (P< 0.001) intercept = 0.28 kPa (P = 0.43)

  • 48.
    Forsgren, Mikael
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Wolfram MathCore AB, Linköping, Sweden.
    Norén, Bengt
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Kechagias, Stergios
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Gastroentorology.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Comparing hepatic 2D and 3D magnetic resonance elastography methods in a clinical setting – Initial experiences2015In: European Journal of Radiology Open, E-ISSN 2352-0477, Vol. 2, p. 66-70Article in journal (Refereed)
    Abstract [en]

    Purpose

    Continuous monitoring of liver fibrosis progression in patients is not feasible with the current diagnostic golden standard (needle biopsy). Recently, magnetic resonance elastography (MRE) has emerged as a promising method for such continuous monitoring. Since there are different MRE methods that could be used in a clinical setting there is a need to investigate whether measurements produced by these MRE methods are comparable. Hence, the purpose of this pilot study was to evaluate whether the measurements of the viscoelastic properties produced by 2D (stiffness) and 3D (elasticity and ‘Gabs,Elastic’) MRE are comparable.

    Materials and methods

    Seven patients with diffuse or suspect diffuse liver disease were examined in the same day with the two MRE methods. 2D MRE was performed using an acoustic passive transducer, with a 1.5 T GE 450 W MR system. 3D MRE was performed using an electromagnetic active transducer, with a 1.5 T Philips Achieva MR system. Finally, mean viscoelastic values were extracted from the same anatomical region for both methods by an experienced radiologist.

    Results

    Stiffness correlated well with the elasticity, R2 = 0.96 (P < 0.001; slope = 1.08, intercept = 0.61 kPa), as well as with ‘Gabs,ElasticR2 = 0.96 (P < 0.001; slope = 0.95, intercept = 0.28 kPa).

    Conclusion

    This pilot study shows that different MRE methods can produce comparable measurements of the viscoelastic properties of the liver. The existence of such comparable measurements is important, both from a clinical as well as a research perspective, since it allows for equipment-independent monitoring of disease progression.

  • 49.
    Forsgren, Mikael
    et al.
    Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Weber, Patrick
    Linköping University, Department of Clinical and Experimental Medicine, Rheumatology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Rheumatology.
    Janzén, David
    Linköping University, Department of Clinical and Experimental Medicine, Cell Biology. Linköping University, Faculty of Health Sciences.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Pena, José
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Cedersund, Gunnar
    Linköping University, Department of Clinical and Experimental Medicine, Cell Biology. Linköping University, Faculty of Health Sciences.
    Bayesian mixed-effect modeling of contrast agent data for decision-support when diagnosing diffuse liver disease2012Conference paper (Other academic)
  • 50.
    Friman, O.
    et al.
    MeVis Research, Bremen, Germany.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Radiation Physics.
    Borga, Magnus
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    A General Method for Correction of Intensity Inhomogeniety in Two Point Dixon Imaging2008In: Proceedings of the International Society for Magnetic Resonance in Medicine annual meeting (ISMRM'08), International Society for Magnetic Resonance in Medicine , 2008, article id 4637Conference paper (Other academic)
    Abstract [en]

    Two point Dixon imaging can be used for quantitative fat estimation. However, field inhomogeneities pose a problem that needs to be corrected for before quantitative measurements can be obtained. We present a general framework for field inhomogeneitiy correction by fitting a set of smooth 3D spatial basis functions to voxels with high fat content. By choosing the number of basis functions, the smoothness constraint of the field can be controlled. The method is evaluated by measuring the FWHM of the fat peak in histograms for different number of basis functions. It is also compared to a previous method with good results.

1234 1 - 50 of 155
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf