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  • 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.
    Aalto, Anne
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medical and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Sjoewall, Johanna
    Linköping University, Department of Clinical and Experimental Medicine, Clinical Immunology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medicine, Department of Infectious Diseases in Östergötland.
    Davidsson, Leif
    Linköping University, Department of Medicine and Care, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    Forsberg, Pia
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Clinical and Experimental Medicine, Infectious Diseases. Östergötlands Läns Landsting, Centre for Medicine, Department of Infectious Diseases in Östergötland.
    Smedby, Örjan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medical and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Brain magnetic resonance imaging does not contribute to the diagnosis of chronic neuroborreliosis2007In: Acta Radiologica, ISSN 0284-1851, E-ISSN 1600-0455, Vol. 48, no 7, p. 755-762Article in journal (Refereed)
    Abstract [en]

    Background: Borrelia infections, especially chronic neuroborreliosis ( NB), may cause considerable diagnostic problems. This diagnosis is based on symptoms and findings in the cerebrospinal fluid but is not always conclusive. Purpose: To evaluate brain magnetic resonance imaging ( MRI) in chronic NB, to compare the findings with healthy controls, and to correlate MRI findings with disease duration. Material and Methods: Sixteen well- characterized patients with chronic NB and 16 matched controls were examined in a 1.5T scanner with a standard head coil. T1- ( with and without gadolinium), T2-, and diffusion- weighted imaging plus fluid- attenuated inversion recovery ( FLAIR) imaging were used. Results: White matter lesions and lesions in the basal ganglia were seen in 12 patients and 10 controls ( no significant difference). Subependymal lesions were detected in patients down to the age of 25 and in the controls down to the age of 43. The number of lesions was correlated to age both in patients ( rho=0.83, P < 0.01) and in controls ( rho=0.61, P < 0.05), but not to the duration of disease. Most lesions were detected with FLAIR, but many also with T2- weighted imaging. Conclusion: A number of MRI findings were detected in patients with chronic NB, although the findings were unspecific when compared with matched controls and did not correlate with disease duration. However, subependymal lesions may constitute a potential finding in chronic NB.

  • 3. Ahlström, H.
    et al.
    Johansson, L.
    Smedby, Örjan
    Uppsala University.
    Magnusson, A.
    Raland, H.
    Wahlberg, J.
    Computed Tomography Angiography (CTA) and Magnetic Resonance Angiography (MRA) in the diagnosis of renal transplant artery stenosis1996Conference paper (Refereed)
  • 4. Ahlström, H.
    et al.
    Smedby, Örjan
    Uppsala University.
    Löfberg, AM.
    Bergkvist, D.
    Ljungman, C.
    Magnetic Resonance Angiography of Peripheral Run-off Vessels1995Conference paper (Other academic)
  • 5.
    Andersson, Malin
    et al.
    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.
    Jagervall, Karl
    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). Not Found:Linkoping Univ, Ctr Med Image Sci and Visualizat CMIV, Linkoping, Sweden; Linkoping Univ, Dept Radiol, Linkoping, Sweden; Linkoping Univ, Dept Med and Hlth Sci, Linkoping, Sweden.
    Eriksson, Per
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Region Östergötland, Heart and Medicine Center, Department of Rheumatology. Linköping University, Faculty of Medicine and Health Sciences.
    Persson, Anders
    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. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Granerus, Göran
    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 Clinical Physiology in Linköping.
    Wang, Chunliang
    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). KTH Royal Institute Technology, Sweden.
    Smedby, Örjan
    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. Linköping University, Center for Medical Image Science and Visualization (CMIV). KTH Royal Institute Technology, Sweden.
    How to measure renal artery stenosis - a retrospective comparison of morphological measurement approaches in relation to hemodynamic significance2015In: BMC Medical Imaging, ISSN 1471-2342, E-ISSN 1471-2342, Vol. 15, no 42Article in journal (Refereed)
    Abstract [en]

    Background: Although it is well known that renal artery stenosis may cause renovascular hypertension, it is unclear how the degree of stenosis should best be measured in morphological images. The aim of this study was to determine which morphological measures from Computed Tomography Angiography (CTA) and Magnetic Resonance Angiography (MRA) are best in predicting whether a renal artery stenosis is hemodynamically significant or not. Methods: Forty-seven patients with hypertension and a clinical suspicion of renovascular hypertension were examined with CTA, MRA, captopril-enhanced renography (CER) and captopril test (Ctest). CTA and MRA images of the renal arteries were analyzed by two readers using interactive vessel segmentation software. The measures included minimum diameter, minimum area, diameter reduction and area reduction. In addition, two radiologists visually judged the diameter reduction without automated segmentation. The results were then compared using limits of agreement and intra-class correlation, and correlated with the results from CER combined with Ctest (which were used as standard of reference) using receiver operating characteristics (ROC) analysis. Results: A total of 68 kidneys had all three investigations (CTA, MRA and CER + Ctest), where 11 kidneys (16.2 %) got a positive result on the CER + Ctest. The greatest area under ROC curve (AUROC) was found for the area reduction on MRA, with a value of 0.91 (95 % confidence interval 0.82-0.99), excluding accessory renal arteries. As comparison, the AUROC for the radiologists visual assessments on CTA and MRA were 0.90 (0.82-0.98) and 0.91 (0.83-0.99) respectively. None of the differences were statistically significant. Conclusions: No significant differences were found between the morphological measures in their ability to predict hemodynamically significant stenosis, but a tendency of MRA having higher AUROC than CTA. There was no significant difference between measurements made by the radiologists and measurements made with fuzzy connectedness segmentation. Further studies are required to definitely identify the optimal measurement approach.

  • 6.
    Andersson, Mats
    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.
    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.
    Sandborg, Michael
    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.
    Farnebäck, Gunnar
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Hans, Knutsson
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Adaptiv filtering of 4D-heart CT for image denoising and patient safety2010Conference paper (Other academic)
    Abstract [en]

    The aim of this medical image science project is to increase patient safety in terms of improved image quality and reduced exposure to ionizing radiation in CT. The means to achieve these goals is to develop and evaluate an efficient adaptive filtering (denoising/image enhancement) method that fully explores true 4D image acquisition modes. Four-dimensional (4D) medical image data are captured as a time sequence of image volumes. During 4D image acquisition, a 3D image of the patient is recorded at regular time intervals. The resulting data will consequently have three spatial dimensions and one temporal dimension. Increasing the dimensionality of the data impose a major increase the computational demands. The initial linear filtering which is the cornerstone in all adaptive image enhancement algorithms increase exponentially with the dimensionality. On the other hand the potential gain in Signal to Noise Ratio (SNR) also increase exponentially with the dimensionality. This means that the same gain in noise reduction that can be attained by performing the adaptive filtering in 3D as opposed to 2D can be expected to occur once more by moving from 3D to 4D. The initial tests on on both synthetic and clinical 4D images has resulted in a significant reduction of the noise level and an increased detail compared to 2D and 3D methods. When tuning the parameters for adaptive filtering is extremely important to attain maximal diagnostic value which not necessarily coincide with an an eye pleasing image for a layman. Although this application focus on CT the resulting adaptive filtering methods will be beneficial for a wide range of 3D/4D medical imaging modalities e.g. shorter acquisition time in MRI and improved elimination of noise in 3D or 4D ultrasound datasets.

  • 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.
    Andersson-Engels, Stefan
    et al.
    Inst för fysik Lunds Tekniska Högskola.
    Pålsson, S
    Backlund, Erik Olof
    IMT LiU.
    Sturnegk, Patrik
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Neuroscience and Locomotion, Neurosurgery. Östergötlands Läns Landsting, Reconstruction Centre, Department of Neurosurgery UHL.
    Lundberg, Peter
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Radiation Physics. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Radiation Physics. 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).
    Svanberg, K
    Eriksson, Ola
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation.
    Wårdell, Karin
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation.
    ALA-PpIX Fluorescence and spectroscopy in connection with stereotactic biopsy of human glioblastomas2005In: European Conference on Biomedical Optics,2005, 2005Conference paper (Refereed)
  • 10.
    Bernard, Olivier
    et al.
    University of Lyon 1, France.
    Bosch, Johan G.
    Erasmus MC, Netherlands.
    Heyde, Brecht
    Katholieke University of Leuven, Belgium.
    Alessandrini, Martino
    Katholieke University of Leuven, Belgium.
    Barbosa, Daniel
    University of Minho, Portugal.
    Camarasu-Pop, Sorina
    University of Lyon 1, France.
    Cervenansky, Frederic
    University of Lyon 1, France.
    Valette, Sebastien
    University of Lyon 1, France.
    Mirea, Oana
    Katholieke University of Leuven, Belgium.
    Bernier, Michel
    University of Sherbrooke, Canada.
    Jodoin, Pierre-Marc
    University of Sherbrooke, Canada.
    Santo Domingos, Jaime
    University of Oxford, England.
    Stebbing, Richard V.
    University of Oxford, England.
    Keraudren, Kevin
    University of London Imperial Coll Science Technology and Med, England.
    Oktay, Ozan
    University of London Imperial Coll Science Technology and Med, England.
    Caballero, Jose
    University of London Imperial Coll Science Technology and Med, England.
    Shi, Wei
    University of London Imperial Coll Science Technology and Med, England.
    Rueckert, Daniel
    University of London Imperial Coll Science Technology and Med, England.
    Milletari, Fausto
    Technical University of Munich, Germany.
    Ahmadi, Seyed-Ahmad
    University of Munich, Germany.
    Smistad, Erik
    Norwegian University of Science and Technology, Norway.
    Lindseth, Frank
    Norwegian University of Science and Technology, Norway.
    van Stralen, Maartje
    University of Medical Centre Utrecht, Netherlands.
    Wang, Chen
    Not Found:Linkoping Univ, Dept Med and Hlth Sci IMH, Ctr Med Imaging Sci and Visualizat CMIV, SE-58185 Linkoping, Sweden.
    Smedby, Örjan
    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. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Donal, Erwan
    University of Rennes 1, France; University of Rennes 1, France; University of Rennes 1, France.
    Monaghan, Mark
    Kings Coll Hospital NHS Fdn Trust, England.
    Papachristidis, Alex
    Kings Coll Hospital NHS Fdn Trust, England.
    Geleijnse, Marcel L.
    Erasmus MC, Netherlands.
    Galli, Elena
    University of Rennes 1, France; University of Rennes 1, France; University of Rennes 1, France.
    Dhooge, Jan
    Katholieke University of Leuven, Belgium.
    Standardized Evaluation System for Left Ventricular Segmentation Algorithms in 3D Echocardiography2016In: IEEE Transactions on Medical Imaging, ISSN 0278-0062, E-ISSN 1558-254X, Vol. 35, no 4, p. 967-977Article in journal (Refereed)
    Abstract [en]

    Real-time 3D Echocardiography (RT3DE) has been proven to be an accurate tool for left ventricular (LV) volume assessment. However, identification of the LV endocardium remains a challenging task, mainly because of the low tissue/blood contrast of the images combined with typical artifacts. Several semi and fully automatic algorithms have been proposed for segmenting the endocardium in RT3DE data in order to extract relevant clinical indices, but a systematic and fair comparison between such methods has so far been impossible due to the lack of a publicly available common database. Here, we introduce a standardized evaluation framework to reliably evaluate and compare the performance of the algorithms developed to segment the LV border in RT3DE. A database consisting of 45 multivendor cardiac ultrasound recordings acquired at different centers with corresponding reference measurements from three experts are made available. The algorithms from nine research groups were quantitatively evaluated and compared using the proposed online platform. The results showed that the best methods produce promising results with respect to the experts measurements for the extraction of clinical indices, and that they offer good segmentation precision in terms of mean distance error in the context of the experts variability range. The platform remains open for new submissions.

  • 11.
    Blystad, Ida
    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 Diagnostics, Department of Radiology in Linköping.
    Håkansson, I
    Tisell, Anders
    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.
    Ernerudh, J
    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.
    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.
    Larsson, EM
    Quantitative MRI for the evaluation of active MS-lesions without gadolinium based contrast agent.2014Conference paper (Other academic)
  • 12.
    Blystad, Ida
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences.
    Håkansson, Irene
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences.
    Tisell, Anders
    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, Faculty of Medicine and Health Sciences. Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences.
    Ernerudh, Jan
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Clinical Immunology and Transfusion Medicine.
    Smedby, Örjan
    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. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Lundberg, Peter
    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).
    Larsson, Elna-Marie
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Uppsala University, Sweden.
    Quantitative MRI for Analysis of Active Multiple Sclerosis Lesions without Gadolinium-Based Contrast Agent2016In: American Journal of Neuroradiology, ISSN 0195-6108, E-ISSN 1936-959X, Vol. 37, no 1, p. 94-100Article in journal (Refereed)
    Abstract [en]

    BACKGROUND AND PURPOSE: Contrast-enhancing MS lesions are important markers of active inflammation in the diagnostic work-up of MS and in disease monitoring with MR imaging. Because intravenous contrast agents involve an expense and a potential risk of adverse events, it would be desirable to identify active lesions without using a contrast agent. The purpose of this study was to evaluate whether pre-contrast injection tissue-relaxation rates and proton density of MS lesions, by using a new quantitative MR imaging sequence, can identify active lesions. MATERIALS AND METHODS: Forty-four patients with a clinical suspicion of MS were studied. MR imaging with a standard clinical MS protocol and a quantitative MR imaging sequence was performed at inclusion (baseline) and after 1 year. ROIs were placed in MS lesions, classified as nonenhancing or enhancing. Longitudinal and transverse relaxation rates, as well as proton density were obtained from the quantitative MR imaging sequence. Statistical analyses of ROI values were performed by using a mixed linear model, logistic regression, and receiver operating characteristic analysis. RESULTS: Enhancing lesions had a significantly (P &lt; .001) higher mean longitudinal relaxation rate (1.22 0.36 versus 0.89 +/- 0.24), a higher mean transverse relaxation rate (9.8 +/- 2.6 versus 7.4 +/- 1.9), and a lower mean proton density (77 +/- 11.2 versus 90 +/- 8.4) than nonenhancing lesions. An area under the receiver operating characteristic curve value of 0.832 was obtained. CONCLUSIONS: Contrast-enhancing MS lesions often have proton density and relaxation times that differ from those in nonenhancing lesions, with lower proton density and shorter relaxation times in enhancing lesions compared with nonenhancing lesions.

  • 13.
    Blystad, Ida
    et al.
    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.
    Warntjes, Jan Bertus Marcel
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Centre, Department of Clinical Physiology 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, Centre for Diagnostics, Department of Radiology in Linköping.
    Landtblom, Anne-Marie
    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. 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 Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL.
    SyntheticMRI compared with conventional MRI of the brain in a clinical setting: a pilot study, ESMRMB 2012, Lisbon, Portugal.2012Conference paper (Other academic)
  • 14.
    Blystad, Ida
    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.
    Warntjes, Jan Bertus Marcel
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology 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.
    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.
    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.
    Larsson, Elna-Marie
    Uppsala University, Sweden .
    Synthetic MRI of the brain in a clinical setting2012In: Acta Radiologica, ISSN 0284-1851, E-ISSN 1600-0455, Vol. 53, no 10, p. 1158-1163Article in journal (Refereed)
    Abstract [en]

    BACKGROUND:

    Conventional magnetic resonance imaging (MRI) has relatively long scan times for routine examinations, and the signal intensity of the images is related to the specific MR scanner settings. Due to scanner imperfections and automatic optimizations, it is impossible to compare images in terms of absolute image intensity. Synthetic MRI, a method to generate conventional images based on MR quantification, potentially both decreases examination time and enables quantitative measurements.

    PURPOSE:

    To evaluate synthetic MRI of the brain in a clinical setting by assessment of the contrast, the contrast-to-noise ratio (CNR), and the diagnostic quality compared with conventional MR images.

    MATERIAL AND METHODS:

    Twenty-two patients had synthetic imaging added to their clinical MR examination. In each patient, 12 regions of interest were placed in the brain images to measure contrast and CNR. Furthermore, general image quality, probable diagnosis, and lesion conspicuity were investigated.

    RESULTS:

    Synthetic T1-weighted turbo spin echo and T2-weighted turbo spin echo images had higher contrast but also a higher level of noise, resulting in a similar CNR compared with conventional images. Synthetic T2-weighted FLAIR images had lower contrast and a higher level of noise, which led to a lower CNR. Synthetic images were generally assessed to be of inferior image quality, but agreed with the clinical diagnosis to the same extent as the conventional images. Lesion conspicuity was higher in the synthetic T1-weighted images, which also had a better agreement with the clinical diagnoses than the conventional T1-weighted images.

    CONCLUSION:

    Synthetic MR can potentially shorten the MR examination time. Even though the image quality is perceived to be inferior, synthetic images agreed with the clinical diagnosis to the same extent as the conventional images in this study.

  • 15.
    Blystad, Ida
    et al.
    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.
    Warntjes, Marcel Jan Bertus
    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 Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Smedby, Örjan
    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. Linköping University, Center for Medical Image Science and Visualization (CMIV). KTH Royal Institute Technology, Sweden.
    Lundberg, Peter
    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).
    Larsson, Elna-Marie
    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). Uppsala University, Sweden.
    Tisell, Anders
    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).
    Quantitative MRI for analysis of peritumoral edema in malignant gliomas2017In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 12, no 5, article id e0177135Article in journal (Refereed)
    Abstract [en]

    Background and purpose Damage to the blood-brain barrier with subsequent contrast enhancement is a hallmark of glioblastoma. Non-enhancing tumor invasion into the peritumoral edema is, however, not usually visible on conventional magnetic resonance imaging. New quantitative techniques using relaxometry offer additional information about tissue properties. The aim of this study was to evaluate longitudinal relaxation R-1, transverse relaxation R-2, and proton density in the peritumoral edema in a group of patients with malignant glioma before surgery to assess whether relaxometry can detect changes not visible on conventional images. Methods In a prospective study, 24 patients with suspected malignant glioma were examined before surgery. A standard MRI protocol was used with the addition of a quantitative MR method (MAGIC), which measured R-1, R-2, and proton density. The diagnosis of malignant glioma was confirmed after biopsy/surgery. In 19 patients synthetic MR images were then created from the MAGIC scan, and ROIs were placed in the peritumoral edema to obtain the quantitative values. Dynamic susceptibility contrast perfusion was used to obtain cerebral blood volume (rCBV) data of the peritumoral edema. Voxel-based statistical analysis was performed using a mixed linear model. Results R-1, R-2, and rCBV decrease with increasing distance from the contrast-enhancing part of the tumor. There is a significant increase in R1 gradient after contrast agent injection (Pamp;lt;.0001). There is a heterogeneous pattern of relaxation values in the peritumoral edema adjacent to the contrast-enhancing part of the tumor. Conclusion Quantitative analysis with relaxometry of peritumoral edema in malignant gliomas detects tissue changes not visualized on conventional MR images. The finding of decreasing R-1 and R-2 means shorter relaxation times closer to the tumor, which could reflect tumor invasion into the peritumoral edema. However, these findings need to be validated in the future.

  • 16.
    Borgen, Lars
    et al.
    Drammen and Buskerud University of College.
    Kalra, Mannudeep K
    Harvard University.
    Laerum, Frode
    Akershus University Hospital.
    Hachette, Isabelle W
    ContextVision AB.
    Fredriksson, Carina H
    ContextVision AB, Linkoping, Sweden .
    Sandborg, Michael
    Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Smedby, Örjan
    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. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Application of adaptive non-linear 2D and 3D postprocessing filters for reduced dose abdominal CT2012In: Acta Radiologica, ISSN 0284-1851, E-ISSN 1600-0455, Vol. 53, no 3, p. 335-342Article in journal (Refereed)
    Abstract [en]

    Background: Abdominal computed tomography (an is a frequently performed imaging procedure, resulting in considerable radiation doses to the patient population. Postprocessing filters are one of several dose reduction measures that might help to reduce radiation doses without loss of image quality. less thanbrgreater than less thanbrgreater thanPurpose: To assess and compare the effect of two- and three-dimensional (2D, 3D) non-linear adaptive filters on reduced dose abdominal CT images. less thanbrgreater than less thanbrgreater thanMaterial and Methods: Two baseline abdominal CT image series with a volume computer tomography dose index (CTDI (vol)) of 12 mGy and 6 mGy were acquired for 12 patients. Reduced dose images were postprocessed with 2D and 3D filters. Six radiologists performed blinded randomized, side-by-side image quality assessments. Objective noise was measured. Data were analyzed using visual grading regression and mixed linear models. less thanbrgreater than less thanbrgreater thanResults: All image quality criteria were rated as superior for 3D filtered images compared to reduced dose baseline and 2D filtered images (P andlt; 0.01). Standard dose images had better image quality than reduced dose 3D filtered images (P andlt; 0.01), but similar image noise. For patients with body mass index (BMI) andlt; 30 kg/m(2) however, 3D filtered images were rated significantly better than normal dose images for two image criteria (P andlt; 0.05), while no significant difference was found for the remaining three image criteria (P andgt; 0.05). There were no significant variations of objective noise between standard dose and 2D or 3D filtered images. less thanbrgreater than less thanbrgreater thanConclusion: The quality of 3D filtered reduced dose abdominal CT images is superior compared to reduced dose unfiltered and 2D filtered images. For patients with BMI andlt; 30 kg/m(2), 3D filtered images are comparable to standard dose images.

  • 17.
    Brismar, T
    et al.
    Department of Radiology, CLINTEC, Stockholm, Sweden.
    Dahlström, Nils
    Linköping University, Department of Medicine and Care. Linköping University, Center for Medical Image Science and Visualization (CMIV). Department of Radiology, Hudiksvall Hospital, Sweden.
    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).
    Persson, Anders
    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).
    Albiin, N
    Department of Radiology, CLINTEC, Stockholm, Sweden.
    Liver vessel enhancement by Gd-BOPTA and Gd-EOB-DTPA- a comparison in healthy volunteers2006In: ISMRM 2006,2006, 2006Conference paper (Other academic)
  • 18.
    Brismar, Torkel
    et al.
    Karolinska Institutet, CLINTEC, Röntgenavdelningen, Karolinska Universitetssjukhuset Huddinge.
    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, Centre for Medical Imaging, Department of Radiology in Linköping.
    Edsborg, Nick
    Karolinska Institutet, CLINTEC, Röntgenavdelningen, Karolinska Universitetssjukhuset Huddinge.
    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, Centre for Medical Imaging, 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.
    Albiin, Nils
    Karolinska Institutet, CLINTEC, Röntgenavdelningen, Karolinska Universitetssjukhuset Huddinge.
    Liver Vessel Enhancement by Gd-BOPTA and Gc-EOB-DTPA – a Comparison in Healthy Volunteers.2009In: Acta Radiologica, ISSN 0284-1851, E-ISSN 1600-0455, Vol. 50, no 7, p. 709-715Article in journal (Refereed)
    Abstract [en]

    Background: A thorough understanding of magnetic resonance (MR) contrast media dynamics makes it possible to choose the optimal contrast media for each investigation. Differences in visualizing hepatobiliary function between Gd-BOPTA and Gd-EOB-DTPA have previously been demonstrated, but less has been published regarding differences in liver vessel visualization.Purpose: To compare the liver vessel and liver parenchymal enhancement dynamics of Gd-BOPTA (MultiHance®) and Gd-EOB-DTPA (Primovist®). Material and Methods: The signal intensity of the liver parenchyma, the common hepatic artery, the middle hepatic vein, and a segmental branch of the right portal vein, was obtained in 10 healthy volunteers before contrast media administration, during arterial and portal venous phases, and 10, 20, 30, 40 and 130 minutes after intravenous contrast medium injection, but due to scanner limitations not during the hepatic venous phase. Results: Maximum enhancement of liver parenchyma was observed from the portal venous phase until 130 minutes after Gd-BOPTA administration and from 10 minutes to 40 minutes after Gd-EOB-DTPA. There was no difference in maximum enhancement of liver parenchyma between the two contrast media. When using Gd-BOPTA, the vascular contrast enhancement was still apparent 40 minutes after injection, but had vanished 10 minutes after Gd-EOB-DTPA injection. The maximum difference in signal intensity between the vessels and the liver parenchyma was significantly greater with Gd-BOPTA than with Gd-EOB-DTPA (p<0.0001). Conclusion: At the dosage used in this study Gd-BOPTA yields higher maximum enhancement of the hepatic artery, portal vein and middle hepatic vein during the arterial and the portal venous phase and during the delayed phases than Gd-EOB-DTPA does, whereas there is no difference in liver parenchymal enhancement between the two contrast agents.

  • 19.
    Chowdhury, Manish
    et al.
    KTH, School of Technology and Health, Sweden.
    Klintström, Benjamin
    Linköping University, Center for Medical Image Science and Visualization (CMIV). KTH, School of Technology and Health, Sweden.
    Klintström, Eva
    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.
    Smedby, Örjan
    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. KTH, School of Technology and Health, Sweden.
    Moreno, Rodrigo
    KTH, School of Technology and Health, Sweden.
    Granulometry-Based Trabecular Bone Segmentation2017In: Image Analysis - 20th Scandinavian Conference on Image Analysis, SCIA 2017, Proceedings / [ed] Sharma P., Bianchi F., Springer, 2017, Vol. 10270, p. 100-108Conference paper (Refereed)
    Abstract [en]

    The accuracy of the analyses for studying the three dimensionaltrabecular bone microstructure rely on the quality of the segmentationbetween trabecular bone and bone marrow. Such segmentationis challenging for images from computed tomography modalities thatcan be used in vivo due to their low contrast and resolution. For thispurpose, we propose in this paper a granulometry-based segmentationmethod. In a first step, the trabecular thickness is estimated by usingthe granulometry in gray scale, which is generated by applying the openingmorphological operation with ball-shaped structuring elements ofdifferent diameters. This process mimics the traditional sphere-fittingmethod used for estimating trabecular thickness in segmented images.The residual obtained after computing the granulometry is comparedto the original gray scale value in order to obtain a measurement ofhow likely a voxel belongs to trabecular bone. A threshold is applied toobtain the final segmentation. Six histomorphometric parameters werecomputed on 14 segmented bone specimens imaged with cone-beam computedtomography (CBCT), considering micro-computed tomography(micro-CT) as the ground truth. Otsu’s thresholding and AutomatedRegion Growing (ARG) segmentation methods were used for comparison.For three parameters (Tb.N, Tb.Th and BV/TV), the proposedsegmentation algorithm yielded the highest correlations with micro-CT,while for the remaining three (Tb.Nd, Tb.Tm and Tb.Sp), its performancewas comparable to ARG. The method also yielded the strongestaverage correlation (0.89). When Tb.Th was computed directly fromthe gray scale images, the correlation was superior to the binary-basedmethods. The results suggest that the proposed algorithm can be usedfor studying trabecular bone in vivo through CBCT.

  • 20.
    Cros, Olivier
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV). Department of Otolaryngology, Head and Neck Surgery, Aalborg Hospital, Aarhus University Hospital, Denmark.
    Gaihede, Michael L.
    Department of Otolaryngology, Head and Neck Surgery, Aalborg Hospital, Aarhus University Hospital, Denmark.
    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).
    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.
    Mastoid structural properties determined by imaging analysis of high resolution CT-scanning2010In: Hearing Research, ISSN 0378-5955, E-ISSN 1878-5891, Vol. 263, no 1-2, p. 242-243Article in journal (Refereed)
    Abstract [en]

    Hypothesis: The structure of the mastoid air cells can be described by quantitative imaging analysis of high-resolution CT-scans, which may contribute to understand its function in normal and pathological ears. Background: Negative middle ear pressure is a common factor in middle ear diseases resulting from an imbalance between mastoid gas exchange and Eustachian tube function. While the Eustachian tube function has been the main focus of research, more recent studies indicate that the mastoid may play an active role in pressure regulation. The mastoid structure with numerous air cells reflects a large area to volume ratio (AV-ratio) adapted to efficient gas exchange. Imaging analysis applied to high resolution CT-scanning can describe quantitative measures, which may reveal important information about mastoid function and its role in healthy and diseased ears. Materials and methods: Quantitative analysis was performed on a series of unselected high resolution CT-scans (voxel size: 0.29 _ 0.29 _ 0.625 mm) from 36 ears in 24 patients. Area and volume were determined using Cavalieri’s method, i.e. by summing cross-sectional areas. The AV-ratio was computed for each scan. Results: Mean area was 69 cm2 (range: 23–134cm2), mean volume was 4 cm3 (range: 1.3–10.8 cm3), and mean AV-ratio was 16 cm-1 (range: 11.2–21.0 cm-1). The area correlated linearly to the volume by A = 17.2*V-0.2. Conclusion: The area and volume values corresponded with previous studies, and the additional AV-ratio reflected the functional properties of the mastoid in terms of capability for gas exchange. Due to a series of similarities between structure and function of the lungs and mastoid, it seems likely to propose a tree-structure of dividing mastoid cells. In respiratory research, analysis describing the dimensions of series of bronchi generations has been applied, and based on current results; our aim of future research is to establish similar details of mastoid tree-structure. Funding source: Various private Danish funds.

  • 21.
    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]

      

  • 22.
    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

  • 23.
    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)
  • 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.
    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)
  • 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.
    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)
  • 26.
    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.

  • 27.
    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)
  • 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, 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)
  • 30.
    Dahlström, N
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Brismar, TB
    Persson, Anders
    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.
    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.
    Albiin, N
    Biliary enhancement of Gd-BOPTA and Gd-EOB-DTPA - a study in healthy volunteers2006In: ISMRM,2006, 2006Conference paper (Other academic)
  • 31.
    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)
  • 32.
    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)
  • 33.
    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, Centre for Medical Imaging, Department of Radiology in Linköping.
    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, Centre for Medical Imaging, Department of Radiology in Linköping.
    Albiin, Nils
    Karolinska Institutet, CLINTEC, Röntgenavdelningen, Karolinska Universitetssjukhuset Huddinge.
    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.
    Brismar, Torkel
    Karolinska Institutet, CLINTEC, Röntgenavdelningen, Karolinska Universitetssjukhuset Huddinge.
    Contrast-enhanced magnetic resonance cholangiography with Gd-BOPTA and Gd-EOB-DTPA in healthy subjects2007In: Acta Radiologica, ISSN 0284-1851, E-ISSN 1600-0455, Vol. 48, no 4, p. 362-368Article in journal (Refereed)
    Abstract [en]

    PURPOSE: To evaluate the biliary enhancement dynamics of the two gadolinium chelates Gd-BOPTA (MultiHance) and Gd-EOB-DTPA (Primovist) in normal healthy subjects. MATERIAL AND METHODS: Ten healthy volunteers were evaluated with both agents by magnetic resonance (MR) imaging at 1.5T using a breath-hold gradient-echo T1-weighted VIBE sequence. The relative signal intensity (SI) differences between the common hepatic duct (CHD) and liver parenchyma were measured before and 10, 20, 30, 40, 130, 240, and 300 min after contrast medium injection. RESULTS: Biliary enhancement was obvious 10 min post-injection for Gd-EOB-DTPA and was noted at 20 min for Gd-BOPTA. At 40 min delay, Gd-BOPTA reached its peak biliary enhancement, but at neither 30 nor 40 min delay was there any significant difference compared with that of Gd-EOB-DTPA. At later delays, the contrast between CHD and liver continued to increase for Gd-EOB-DTPA, whereas it decreased for Gd-BOPTA. CONCLUSION: The earlier onset and longer duration of a high contrast between CHD and liver for Gd-EOB-DTPA facilitates examination of hepatobiliary excretion. Therefore, Gd-EOB-DTPA may provide adequate hepatobiliary imaging within a shorter time span than Gd-BOPTA and facilitate scheduling at the MR unit. Further studies in patients are required to compare the imaging advantages of Gd-EOB-DTPA and Gd-BOPTA in clinical practice.

  • 34.
    De Geer, Jakob
    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, Centre for Diagnostics, Department of Radiology in Linköping.
    Sandborg, Michael
    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.
    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.
    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, Centre for Diagnostics, Department of Radiology in Linköping.
    Post processing noise reduction as a way of reducing the dose in cardiac CT without sacrificing image quality: A Pilot study.2010In: European Congress of Radiology 2010, 2010Conference paper (Refereed)
  • 35.
    de Geer, Jakob
    et al.
    Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization, CMIV. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping.
    Sandborg, Michael
    Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Smedby, Örjan
    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. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Persson, Anders
    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. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    The efficacy of 2D, non-linear noise reduction filtering in cardiac imaging: a pilot study2011In: Acta Radiologica, ISSN 0284-1851, E-ISSN 1600-0455, Vol. 52, no 7, p. 716-722Article in journal (Refereed)
    Abstract [en]

    Background: Computed tomography (CT) is becoming increasingly popular as a non-invasive method for visualizing the coronary arteries but patient radiation doses are still an issue. Postprocessing filters such as 2D adaptive non-linear filters might help to reduce the dose without loss of image quality. less thanbrgreater than less thanbrgreater thanPurpose: To investigate whether the use of a 2D, non-linear adaptive noise reduction filter can improve image quality in cardiac computed tomography angiography (CCTA). less thanbrgreater than less thanbrgreater thanMaterial and Methods: CCTA examinations were performed in 36 clinical patients on a dual source CT using two patient dose levels: maximum dose during diastole and reduced dose (20% of maximum dose) during systole. One full-dose and one reduced-dose image were selected from each of the examinations. The reduced-dose image was duplicated and one copy postprocessed using a 2D non-linear adaptive noise reduction filter, resulting in three images per patient. Image quality was assessed using visual grading with three criteria from the European guidelines for assessment of image quality and two additional criteria regarding the left main artery and the overall image quality. Also, the HU value and its standard deviation were measured in the ascending and descending aorta. Data were analyzed using Visual Grading Regression and paired t-test. less thanbrgreater than less thanbrgreater thanResult: For all five criteria, there was a significant (P andlt; 0.01 or better) improvement in perceived image quality when comparing postprocessed low-dose images with low-dose images without noise reduction. Comparing full dose images with postprocessed low-dose images resulted in a considerably larger, significant (P andlt; 0.001) difference. Also, there was a significant reduction of the standard deviation of the HU values in the ascending and descending aorta when comparing postprocessed low-dose images with low-dose images without postprocessing. less thanbrgreater than less thanbrgreater thanConclusion: Even with an 80% dose reduction, there was a significant improvement in the perceived image quality when using a 2D noise-reduction filter, though not approaching the quality of full-dose images. This indicates that cardiac CT examinations could benefit from noise-reducing postprocessing with 2D non-linear adaptive filters.

  • 36. Dimopoulos, P A
    et al.
    Muren, C
    Smedby, Örjan
    Department of Diagnostic Radiology, University Hospital, Uppsala, Sweden.
    Wadin, K
    Anatomical variations of the tympanic and mastoid portions of the facial nerve canal. A radioanatomical investigation1996In: Acta Radiologica, Supplement, ISSN 0365-5954, Vol. 403, p. 49-59Article in journal (Refereed)
    Abstract [en]

    The measurement results agree with those of previous investigations. The course of the tympanic portion is S-shaped and has an impression on its upper surface. High resolution CT reproduces dehiscences of the bony canal in a percentage similar to that of microscopical methods and in relevant sites. Pneumatization does not influence the dimensions of the 2 portions.

  • 37. Dimopoulos, P A
    et al.
    Smedby, Örjan
    Department of Diagnostic Radiology, University Hospital, Uppsala.
    Wilbrand, H F
    Anatomical variations of the human vestibular aqueduct: Part I. A radioanatomical study1996In: Acta Radiologica, Supplement, ISSN 0365-5954, Vol. 403, p. 21-32Article in journal (Refereed)
    Abstract [en]

    Variations in the size and shape of the human vestibular aqueduct were evaluated in 118 plastic casts of unselected specimens of human temporal bones. They were examined by conventional radiography and by high resolution CT. The degree of the mastoid and perilabyrinthine pneumatization was defined and classified into 3 types. The dimensions of the peripheral portion of the aqueduct were found to be related to the extent of the perilabyrinthine pneumatization.

  • 38. Dimopoulos, P A
    et al.
    Smedby, Örjan
    Department of Diagnostic Radiology, University Hospital, Uppsala.
    Wilbrand, H F
    Anatomical variations of the human vestibular aqueduct: Part II. A radioanatomical study1996In: Acta Radiologica, Supplement, ISSN 0365-5954, Vol. 403, p. 33-41Article in journal (Refereed)
    Abstract [en]

    The human vestibular aqueducts are classified into 3 types and into the types hyper-, normo- and hypoplastic. The types correspond with each other up to over 85%. For a better understanding of the radioanatomy and for the proper interpretation of radiograms, we describe the presence of a flat recess-like widening of the peripheral portion of the aqueduct, as well as other findings.

  • 39. Edvardson, Hannes
    et al.
    Smedby, Örjan
    Uppsala University.
    Registration of 3D binary images through polynomial expansion1999In: CARS '99: Proceedings of the 13th International Congress and Exhibition / [ed] Lemke, H. U. , Vannier, M. W. , Inamura, K. , Farman, A. G., Amsterdam, Netherlands: Elsevier, 1999, p. 223-227Conference paper (Refereed)
  • 40. Edvardsson, Hannes
    et al.
    Smedby, Örjan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Radiology. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology UHL. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Compact and efficient 3D shape description through radial function approximation2003In: Computer Methods and Programs in Biomedicine, ISSN 0169-2607, E-ISSN 1872-7565, Vol. 72, no 2, p. 89-97Article in journal (Refereed)
    Abstract [en]

    A fast and simple method for three-dimensional shape description is described. The method views a 3D object as a radial distance function on the unit sphere, and thus reduces the dimensionality of the description problem by one. The radial distance function is approximated by Fourier methods in the basis of the spherical harmonic polynomials. The necessary integration is carried out on the object boundary, rather than on the unit sphere. Consequently, there is no need of a parameterisation of the object surface. The description makes it possible to compare shapes in a computationally very simple way. Solutions on how to cope with translated and rotated objects are discussed. The method is developed for star-shaped objects, but is stable even if the input image is non-star-shaped. The method is tested in a data set from magnetic resonance imaging (MRI) of the brain. Potential medical applications are discussed. ⌐ 2002 Elsevier Science Ireland Ltd. All rights reserved.

  • 41.
    Ehsan Saffari, Seyed
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Sabzevar University of Medical Science, Iran.
    Love, Askell
    Lund University, Sweden; Landspitali University Hospital, Iceland; University of Iceland, Iceland.
    Fredrikson, Mats
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences.
    Smedby, Örjan
    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. Linköping University, Center for Medical Image Science and Visualization (CMIV). KTH Royal Institute Technology, Sweden.
    Regression models for analyzing radiological visual grading studies - an empirical comparison2015In: BMC Medical Imaging, ISSN 1471-2342, E-ISSN 1471-2342, Vol. 15, no 49Article in journal (Refereed)
    Abstract [en]

    Background: For optimizing and evaluating image quality in medical imaging, one can use visual grading experiments, where observers rate some aspect of image quality on an ordinal scale. To analyze the grading data, several regression methods are available, and this study aimed at empirically comparing such techniques, in particular when including random effects in the models, which is appropriate for observers and patients. Methods: Data were taken from a previous study where 6 observers graded or ranked in 40 patients the image quality of four imaging protocols, differing in radiation dose and image reconstruction method. The models tested included linear regression, the proportional odds model for ordinal logistic regression, the partial proportional odds model, the stereotype logistic regression model and rank-order logistic regression (for ranking data). In the first two models, random effects as well as fixed effects could be included; in the remaining three, only fixed effects. Results: In general, the goodness of fit (AIC and McFaddens Pseudo R-2) showed small differences between the models with fixed effects only. For the mixed-effects models, higher AIC and lower Pseudo R-2 was obtained, which may be related to the different number of parameters in these models. The estimated potential for dose reduction by new image reconstruction methods varied only slightly between models. Conclusions: The authors suggest that the most suitable approach may be to use ordinal logistic regression, which can handle ordinal data and random effects appropriately.

  • 42. Eklöf, H.
    et al.
    Smedby, Örjan
    Uppsala University.
    Ahlström, H.
    Ljungman, C.
    MRA evaluation of lower leg arteries in patients with critical ischemia1996Conference paper (Other academic)
  • 43. Eklöf, H
    et al.
    Smedby, Örjan
    Department of Radiology, University Hospital, Uppsala, Sweden.
    Ljungman, C
    Karacagil, S
    Bergqvist, D
    Ahlström, H
    2D inflow MR angiography in severe chronic leg ischemia1998In: Acta Radiologica, ISSN 0284-1851, E-ISSN 1600-0455, Vol. 39, no 6, p. 663-668Article in journal (Refereed)
    Abstract [en]

    The agreement between MRA and XRA was good in the calf but questionable in the foot.

  • 44. Erikson, U
    et al.
    Smedby, Örjan
    Department of Diagnostic Radiology, Uppsala University.
    Amidotrizoate and Iohexol in Left Coronary Arteriography and Left Ventricular Angiography: Effects upon Myocardial Blood Flow and Ejection Fraction1987In: In Contrast Media from the Past to the Future / [ed] R. Felix et al, Georg Thieme Verlag , 1987Chapter in book (Other academic)
  • 45.
    Eriksson, Per
    et al.
    Linköping University, Department of Medicine and Health Sciences, Internal Medicine . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medicine, Department of Nephrology UHL.
    Mohammed, Ahmed Abdulilah
    Linköping University, Department of Medicine and Health Sciences, Radiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    De Geer, Jakob
    Linköping University, Department of Medicine and Health Sciences, Radiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    Persson, Anders
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    Granerus, Göran
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Nyström, Fredrik
    Linköping University, Department of Medicine 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 Medicine and Health Sciences, Radiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    Non-invasive investigations of potential renal artery stenosis in renal insufficiency2010In: Nephrology, Dialysis and Transplantation, ISSN 0931-0509, E-ISSN 1460-2385, Vol. 25, no 11, p. 3607-3614Article in journal (Refereed)
    Abstract [en]

    Background. The diagnostic value of non-invasive methods for diagnosing renal artery stenosis in patients with renal insufficiency is incompletely known.

    Methods. Forty-seven consecutive patients with moderately impaired renal function and a clinical suspicion of renal artery stenosis were investigated with computed tomography angiography (CTA), gadolinium-enhanced magnetic resonance angiography (MRA), contrast-enhanced Doppler ultrasound and captopril renography. The primary reference standard was stenosis reducing the vessel diameter by at least 50% on CTA, and an alternative reference standard (‘morphological and functional stenosis’) was defined as at least 50% diameter reduction on CTA or MRA, combined with a positive finding from ultrasound or captopril renography.

    Results. The frequency of positive findings, calculated on the basis of individual patients, was 70% for CTA, 60% for MRA, 53% for ultrasound and 30% for captopril renography. Counting kidneys rather than patients, corresponding frequencies were 53%, 41%, 29% and 15%, respectively. In relation to the CTA standard, the sensitivity (and specificity) at the patient level was 0.81 (0.79) for MRA, 0.70 (0.89) for ultrasound and 0.42 (1.00) for captopril renography, and at the kidney level 0.76 (0.82), 0.53 (0.81) and 0.30 (0.86), respectively. Relative to the alternative reference standard, corresponding values at the patient level were 1.00 (0.62) for CTA, 0.90 (0.69) for MRA, 0.91 (1.00) for ultrasound and 0.67 (1.00) for captopril renography, and at the kidney level 0.96 (0.76), 0.85 (0.79), 0.71 (0.97) and 0.50 (0.97), respectively.

    Conclusions. CTA and MRA are superior to ultrasound and captopril renography at diagnosing morphological stenosis, but ultrasound may be useful as a screening method and captopril renography for verifying renin-dependent hypertension.

  • 46.
    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)
  • 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.
    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.

  • 48.
    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)
  • 49.
    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)
  • 50.
    Hadimeri, Ursula
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Department of Radiology, Kärnsjukhuset, Skövde, Sverige.
    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). Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Fransson, Sven-Göran
    Public Health and Clinical Medicine, Umea University, Umea - Sweden.
    Stegmayr, Bernd
    Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.
    Hadimeri, Henrik
    Department of Nephrology, Kärnsjukhuset, Skövde, Sweden.
    Fistula diameter correlates with echocardiographic characteristics in stable hemodialysis patients2015In: Nephrology @ Point of Care, ISSN 2059-3007, Vol. 1, no 1, p. e44-e48Article in journal (Refereed)
    Abstract [en]

    Left ventricular hypertrophy (LVH) is a common finding in hemodialysis patients. The aim of the present study was to investigate if the diameter of the distal radiocephalic fistula could influence left ventricular variables in stable hemodialysis patients.

    Methods

    Nineteen patients were investigated. Measurements of the diameter of the arteriovenous (AV) fistula were performed in 4 different locations. The patients were investigated using M-mode recordings and measurements in the 2D image. Doppler ultrasound was also performed. Transonic measurements were performed after ultrasound investigation.

    Results

    Fistula mean and maximal diameter correlated with left ventricular characteristics. Fistula flow correlated neither with the left ventricular characteristics nor with fistula diameters.

    Conclusions

    The maximal diameter of the distal AV fistula seems to be a sensitive marker of LVH in stable hemodialysis patients.

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