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  • 1.
    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.

  • 2.
    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)
  • 3.
    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)
  • 4.
    Forsgren, Mikael
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Karlsson, Markus
    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).
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dahlström, Nils
    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).
    Norén, Bengt
    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).
    Romu, Thobias
    Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ignatova, Simone
    Linköping University, Department of Clinical and Experimental Medicine, Divison of Neurobiology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Clinical pathology.
    Ekstedt, Mattias
    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.
    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.
    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 Diagnostics, Medical radiation physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Cedersund, Gunnar
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Department of Clinical and Experimental Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Model-inferred mechanisms of liver function from magnetic resonance imaging data: Validation and variation across a clinically relevant cohort2019In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, PLOS COMPUTATIONAL BIOLOGY, Vol. 15, no 6, article id e1007157Article in journal (Refereed)
    Abstract [en]

    Estimation of liver function is important to monitor progression of chronic liver disease (CLD). A promising method is magnetic resonance imaging (MRI) combined with gadoxetate, a liver-specific contrast agent. For this method, we have previously developed a model for an average healthy human. Herein, we extended this model, by combining it with a patient-specific non-linear mixed-effects modeling framework. We validated the model by recruiting 100 patients with CLD of varying severity and etiologies. The model explained all MRI data and adequately predicted both timepoints saved for validation and gadoxetate concentrations in both plasma and biopsies. The validated model provides a new and deeper look into how the mechanisms of liver function vary across a wide variety of liver diseases. The basic mechanisms remain the same, but increasing fibrosis reduces uptake and increases excretion of gadoxetate. These mechanisms are shared across many liver functions and can now be estimated from standard clinical images.

    Author summary

    Being able to accurately and reliably estimate liver function is important when monitoring the progression of patients with liver disease, as well as when identifying drug-induced liver injury during drug development. A promising method for quantifying liver function is to use magnetic resonance imaging combined with gadoxetate. Gadoxetate is a liver-specific contrast agent, which is taken up by the hepatocytes and excreted into the bile. We have previously developed a mechanistic model for gadoxetate dynamics using averaged data from healthy volunteers. In this work, we extended our model with a non-linear mixed-effects modeling framework to give patient-specific estimates of the gadoxetate transport-rates. We validated the model by recruiting 100 patients with liver disease, covering a range of severity and etiologies. All patients underwent an MRI-examination and provided both blood and liver biopsies. Our validated model provides a new and deeper look into how the mechanisms of liver function varies across a wide variety of liver diseases. The basic mechanisms remain the same, but increasing fibrosis reduces uptake and increases excretion of gadoxetate.

  • 5.
    Forsgren, Mikael
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Norén, Bengt
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Kihlberg, Johan
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Kechagias, Stergios
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Gastroentorology.
    Lundberg, Peter
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Comparing 2D and 3D Magnetic Resonance Elastography Techniques in a Clinical Setting: Initial Experiences2014Conference paper (Other academic)
    Abstract [en]

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

  • 6.
    Forsgren, Mikael
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Wolfram MathCore AB, Linköping, Sweden.
    Norén, Bengt
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Kechagias, Stergios
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Gastroentorology.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Comparing hepatic 2D and 3D magnetic resonance elastography methods in a clinical setting – Initial experiences2015In: European Journal of Radiology Open, E-ISSN 2352-0477, Vol. 2, p. 66-70Article in journal (Refereed)
    Abstract [en]

    Purpose

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

    Materials and methods

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

    Results

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

    Conclusion

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

  • 7.
    Karlsson, Markus
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences.
    Ekstedt, Mattias
    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.
    Dahlström, Nils
    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).
    Forsgren, Mikael
    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).
    Ignatova, Simone
    Linköping University, Department of Clinical and Experimental Medicine, Divison of Neurobiology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Clinical pathology.
    Norén, Bengt
    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).
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    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.
    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 Diagnostics, Medical radiation physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Liver R2*is affected by both iron and fat: A dual biopsy-validated study of chronic liver disease2019In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 50, no 1, p. 325-333Article in journal (Refereed)
    Abstract [en]

    Background Liver iron content (LIC) in chronic liver disease (CLD) is currently determined by performing an invasive liver biopsy. MRI using R2* relaxometry is a noninvasive alternative for estimating LIC. Fat accumulation in the liver, or proton density fat fraction (PDFF), may be a possible confounder of R2* measurements. Previous studies of the effect of PDFF on R2* have not used quantitative LIC measurement. Purpose To assess the associations between R2*, LIC, PDFF, and liver histology in patients with suspected CLD. Study Type Prospective. Population Eighty-one patients with suspected CLD. Field Strength/Sequence 1.5 T. Multiecho turbo field echo to quantify R2*. PRESS MRS to quantify PDFF. Assessment Each patient underwent an MR examination, followed by two needle biopsies immediately following the MR examination. The first biopsy was used for conventional histological assessment of LIC, whereas the second biopsy was used to quantitatively measure LIC using mass spectrometry. R2* was correlated with both LIC and PDFF. A correction for the influence of fat on R2* was calculated. Statistical Tests Pearson correlation, linear regression, and area under the receiver operating curve. Results There was a positive linear correlation between R2* and PDFF (R = 0.69), after removing data from patients with elevated iron levels, as defined by LIC. R2*, corrected for PDFF, was the best method for identifying patients with elevated iron levels, with a correlation of R = 0.87 and a sensitivity and specificity of 87.5% and 98.6%, respectively. Data Conclusion PDFF increases R2*. Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:325-333.

    The full text will be freely available from 2020-09-13 14:26
  • 8.
    Karlsson, Markus
    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. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    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.
    Dahlström, Nils
    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. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Leinhard Dahlqvist, Olof
    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.
    Norén, Bengt
    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.
    Ekstedt, Mattias
    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.
    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.
    Lundberg, Peter
    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. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Diffuse Liver Disease: Measurements of Liver Trace Metal Concentrations and R2* Relaxation Rates2016Conference paper (Refereed)
    Abstract [en]

    Introduction

    Over the past decade, several methods for measuring of liver iron content (LIC) non-invasively with MRI have been developed and verified. The most promising methods uses relaxometry, measuring either R2- or R2* relaxation rate in the liver1,2. For instance, several studies have shown that there seems to be a linear relationship between R2* and LIC1. However, few of these studies have measured the liver content of other metals, which could also affect the relaxation rates. The goal of this study was to investigate if any trace metals, other than iron could affect the R2* relaxation rate in liver tissue in a patients with diffuse liver disease.

    Subjects and methods

    75 patients with suspected diffuse liver disease underwent an MRI examination followed by a liver biopsy the same day. The R2* relaxation rate of the water protons in the liver was measured using an axial 3D multi-slice fat-saturated multi-echo turbo field echo sequence (TE=4.60/9.20/13.80/18.40/23.00ms). Regions of interest (ROI) were drawn and R2* was estimated by fitting the mean signal intensity from the ROIs to a mono-exponential decay model. The biopsies were freeze dried and the concentrations of iron, manganese, copper, cobalt and gadolinium were measured using Inductively Coupled Plasma Sector Field Mass Spectrometry (ICP-SFMS). A multiple linear regression analysis was applied to determine which of the measured metals significantly affected the relaxation rate.

    Results

    A linear regression with the LIC and R2* showed a reasonable fit (Figure 1). The multiple linear regression analysis (Table 1) showed that iron as well as manganese had a significant affect on R2*. Unlike iron however, the regression coefficient of manganese was negative, meaning that an increasing manganese concentration gave a shorter R2* relaxation rate. The same trend can be seen when plotting the manganese concentration against R2* (Figure 2).

  • 9.
    Lundberg, Peter
    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. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Karlsson, Markus
    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.
    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.
    Dahlström, Nils
    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. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Leinhard Dahlqvist, Olof
    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. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Norén, Bengt
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Cedersund, Gunnar
    Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Ekstedt, Mattias
    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.
    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.
    Mechanistic modeling of qDCE-MRI data reveals increased bile excretion of Gd-EOB-DTPA in diffuse liver disease patients with severe fibrosis2016Conference paper (Refereed)
    Abstract [en]

    Introduction

    Over the past decades, several different non-invasive methods for staging hepatic fibrosis have been proposed. One such method is dynamic contrast enhanced MRI (DCE-MRI) using the contrast agent (CA) Gd-EOB-DTPA. Gd-EOB-DTPA is liver specific, which means that it is taken up specifically by the hepatocytes via the OATP3B1/B3 transporters and excreted into the bile via the MRP2 transporter. Several studies have shown that DCE-MRI and Gd-EOBDTPA can separate patients with advanced (F3-F4) from mild (F0-F2) hepatic fibrosis by measuring the signal intensity, where patients with advanced fibrosis have a lower signal intensity than the mild fibrosis cases.1 However, none of the studies up to date have been able to differentiate if the reduced signal intensity in the liver is because of an decreased uptake of CA or an increased excretion. Analyzing the DCE-MRI data with mechanistic mathematical modelling has the possibility of investigating such a differentiation.

    Subjects and methods

    88 patients with diffuse liver disease were examined using DCE-MRI (1.5 T Philips Achieva, two-point Dixon, TR=6.5 ms, TE=2.3/4.6 ms, FA=13) after a bolus injection of Gd-EOB-DTPA, followed by a liver biopsy. Regions of interest were placed within the liver, spleen and veins and a whole-body mechanistic pharmacokinetic model2 was fitted to the data. The fitted parameters in the model correspond to the rate of CA transport between different compartments, e.g. hepatocytes, blood plasma, and bile (Fig. 1).

    Results

    As can be seen in Fig. 2, the parameter corresponding to the transport of CA from the blood plasma to the hepatocytes, kph, is lower for patients with advanced fibrosis (p=0.01). Fig. 3 shows that the parameter corresponding to the CA excretion into the bile, khb, is higher for patients with advanced fibrosis (p<0.01).

    Discussion/Conclusion

    This work shows that the decreased signal intensity in DCE-MRI images in patients with advanced fibrosis depends on both a decreased uptake of CA in the hepatocytes and an increased excretion into the bile. Similar results have also been observed in a rat study3. In that study, rats with induced cirrhosis had a higher MRP2-activity than the healthy control rats.

    References

    1Norén et al: Eur. Radiol, 23(1), 174-181, 2013.

    2Forsgren et al: PloS One, 9(4): e95700, 2014.

    3Tsuda & Matsui: Radiol, 256(3): 767-773, 2010.

  • 10.
    Matthiessen, P.
    et al.
    Department of Surgery, Örebro University Hospital, S-701 85 Örebro, Sweden.
    Henriksson, M.
    Department of Radiology, Örebro University Hospital, S-701 85 Örebro, Sweden.
    Hallböök, Olof
    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.
    Grunditz, E.
    Department of Radiology, Vrinnevi Hospital, Norrköping, Sweden.
    Norén, Bengt
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Radiology . Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    Arbman, G.
    Department of Surgery, Vrinnevi Hospital, Norrköping, Sweden.
    Increase of serum C-reactive protein is an early indicator of subsequent symptomatic anastomotic leakage after anterior resection2008In: Colorectal Disease, ISSN 1462-8910, E-ISSN 1463-1318, Vol. 10, no 1, p. 75-80Article in journal (Refereed)
    Abstract [en]

    Objective: This prospective study investigated the factors which might indicate anastomotic leakage after low anterior resection.

    Method: Thirty-three patients who underwent anterior resection for rectal carcinoma (n = 32) and severe dysplasia (n = 1), were monitored daily by serum C-reactive protein (CRP) and white blood cell count (WBC) estimations until discharge from hospital. Computed tomography (CT) scans were performed on postoperative days 2 and 7 and the amount of presacral fluid collection was assessed. All patients had a pelvic drain and the volume of drainage was measured daily.

    Results: The level of the anastomosis was at a median 5 cm (3-12 cm) above the anal verge. There was no 30-day mortality. Nine (27.2%) of the 33 patients developed a symptomatic anastomotic leakage which was diagnosed at a median of 8 days (range 4-14) postoperatively. The serum CRP was increased in patients who leaked from postoperative day 2 onwards (P = 0.004 on day 2, P < 0.001 on day 3-8). The WBC was decreased in preoperatively irradiated patients on days 1-5 (P = 0.021), with no difference seen between patients with or without leakage. Patients with leakage had a larger presacral fluid collection on CT on day 7 (median 76 ml vs 52 ml, P = 0.016) and a larger increase in the fluid collection between the first and the second CT examinations (28 ml vs 3 ml, P = 0.046).

    Conclusion: An early rise in serum CRP was a strong indicator of leakage. Monitoring of CRP for possible early detection of symptomatic anastomotic leakage is recommended.

  • 11.
    Nasr, Patrik
    et al.
    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.
    Forsgren, Mikael F.
    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). Wolfram MathCore AB, Linköping, Sweden.
    Ignatova, Simone
    Linköping University, Department of Clinical and Experimental Medicine, Divison of Neurobiology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Clinical pathology.
    Dahlström, Nils
    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).
    Cedersund, Gunnar
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Department of Clinical and Experimental Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Norén, Bengt
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Medicine and Health Sciences.
    Ekstedt, Mattias
    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.
    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).
    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.
    Using a 3% Proton Density Fat Fraction as a Cut-off Value Increases Sensitivity of Detection of Hepatic Steatosis, Based on Results from Histopathology Analysis2017In: Gastroenterology, ISSN 0016-5085, E-ISSN 1528-0012, Vol. 153, no 1, p. 53-+Article in journal (Refereed)
    Abstract [en]

    It is possible to estimate hepatic triglyceride content by calculating the proton density fat fraction (PDFF), using proton magnetic resonance spectroscopy (less thansuperscriptgreater than1less than/superscriptgreater thanH-MRS), instead of collecting and analyzing liver biopsies to detect steatosis. However, the current PDFF cut-off value (5%) used to define steatosis by magnetic resonance was derived from studies that did not use histopathology as the reference standard. We performed a prospective study to determine the accuracy of less thansuperscriptgreater than1less than/superscriptgreater thanH-MRS PDFF in measurement of steatosis using histopathology analysis as the standard. We collected clinical, serologic, less thansuperscriptgreater than1less than/superscriptgreater thanH-MRS PDFF, and liver biopsy data from 94 adult patients with increased levels of liver enzymes (6 months or more) referred to the Department of Gastroenterology and Hepatology at Linköping University Hospital in Sweden from 2007 through 2014. Steatosis was graded using the conventional histopathology method and fat content was quantified in biopsy samples using stereological point counts (SPCs). We correlated less thansuperscriptgreater than1less than/superscriptgreater thanH-MRS PDFF findings with SPCs (r = 0.92; P less than.001). less thansuperscriptgreater than1less than/superscriptgreater thanH-MRS PDFF results correlated with histopathology results (ρ = 0.87; P less than.001), and SPCs correlated with histopathology results (ρ = 0.88; P less than.001). All 25 subjects with PDFF values of 5.0% or more had steatosis based on histopathology findings (100% specificity for PDFF). However, of 69 subjects with PDFF values below 5.0% (negative result), 22 were determined to have steatosis based on histopathology findings (53% sensitivity for PDFF). Reducing the PDFF cut-off value to 3.0% identified patients with steatosis with 100% specificity and 79% sensitivity; a PDFF cut-off value of 2.0% identified patients with steatosis with 94% specificity and 87% sensitivity. These findings might be used to improve non-invasive detection of steatosis.

  • 12.
    Norén, Bengt
    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.
    Book Review: Atlas of cross-sectional and projective MR cholangiopancreatography; L van Hoe, D Vanbeckevoort and W Van Seenbergen.2000In: European Journal of Surgery, ISSN 1102-4151, E-ISSN 1741-9271, Vol. 166, p. 349-349Article in journal (Other (popular science, discussion, etc.))
  • 13.
    Norén, Bengt
    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.
    MECP möjligheter, begränsningar, utveckling2002In: Läkarmöte "ERCP-Nyheter inom gallvägsdiagnostik och handläggning", Norrköping 24 sept 2002,2002, 2002Conference paper (Refereed)
  • 14.
    Norén, Bengt
    Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Non-Invasive Assessment of Liver Fibrosis with 31P-Magnetic Resonance Spectroscopy and Dynamic Contrast Enhanced Magnetic Resonance Imaging2013Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The present study aims at demonstrating phosphorus metabolite concentration changes and alterations in uptake/excretion of a hepatocyte specific contrast agent in patients with diffuse - or suspected diffuse - liver disease by applying two non-invasive quantitative MR techniques and to compare the results with histo-pathological findings, with focus on liver fibrosis.

    In the first study phosphorus-31 MR spectroscopy using slice selection (DRESS) was implemented. Patients with histopathologically proven diffuse liver disease (n = 9) and healthy individuals (n = 12) were examined. The patients had significantly lower concentrations of phosphodiesters (PDE) and ATP compared with controls. Constructing an ‘anabolic charge’ (AC) based on absolute concentrations, [PME] / ([PME] + [PDE]), the patients had a significant larger AC than the control subjects.

    The MRS technique was then, in a second study, applied on two distinct groups of patients, one group with steatosis and none-to-moderate inflammation (n = 13) and one group with severe fibrosis or cirrhosis (n = 16). A control group (n = 13) was also included. Lower concentrations of PDE and a higher AC were found in the cirrhosis group compared to the control group. Also compared to the steatosis group, the cirrhosis group had lower concentrations of PDE and a higher AC.  A significant correlation between fibrosis stage and PDE and fibrosis stage and AC was found. Using an AC cut-off value of 0.27 to discriminate between mild (stage 0-2) and advanced (stage 3-4) fibrosis yielded an AUROC value of 0.78, similar as for discriminating between F0-1 vs. F2-4.

    Dynamic contrast enhanced MRI (DCE-MRI) was performed prospectively in a third study on 38 patients referred for evaluation of elevated serum alanine aminotransferase (ALT) and/or alkaline phosphatase (ALP) levels. Data were acquired from regions of interest in the liver and spleen by using single-breath-hold symmetrically sampled two-point Dixon 3D images time-series (non-enhanced, arterial and venous portal phase; 3, 10, 20 and 30 min) following a bolus injection of Gd-EOB-DTPA (0.025 mmol/kg). A new quantification procedure for calculation of the ‘hepatocyte specific uptake rate’, KHep, was applied on a two-compartment pharmacokinetic model. Liver-to-spleen contrast ratios (LSC_N) were also calculated. AUROC values of 0.71, 0.80 and 0.78, respectively, were found for KHep, LSC_N10 and LSC_N20 with regard to severe versus mild fibrosis. Significant group differences were found for KHep (borderline), LSC_N10 and LSC_N20.

    In study four no significant correlation between visual assessments of bile ducts excretion of Gd-EOB-DTPA and histo-pathological grading of fibrosis or the quantified uptake of Gd-EOB-DTPA defined as KHep and LSC_N.

    In conclusion 31P-MRS and DCE-MRI show promising results for achieving a non-invasive approach in discriminating different levels of fibrosis from each other.

    List of papers
    1. Absolute quantification of human liver metabolite concentrations by localized in vivo 31P NMR spectroscopy in diffuse liver disease
    Open this publication in new window or tab >>Absolute quantification of human liver metabolite concentrations by localized in vivo 31P NMR spectroscopy in diffuse liver disease
    Show others...
    2005 (English)In: European Radiology, ISSN 0938-7994, E-ISSN 1432-1084, Vol. 15, no 1, p. 148-157Article in journal (Refereed) Published
    Abstract [en]

    Phosphorus-31 NMR spectroscopy using slice selection (DRESS) was used to investigate the absolute concentrations of metabolites in the human liver. Absolute concentrations provide more specific biochemical information compared to spectrum integral ratios. Nine patients with histopathologically proven diffuse liver disease and 12 healthy individuals were examined in a 1.5-T MR scanner (GE Signa LX Echospeed plus). The metabolite concentration quantification procedures included: (1) determination of optimal depth for the in vivo measurements, (2) mapping the detection coil characteristics, (3) calculation of selected slice and liver volume ratios using simple segmentation procedures and (4) spectral analysis in the time domain. The patients had significantly lower concentrations of phosphodiesters (PDE), 6.3±3.9 mM, and ATP-β, 3.6±1.1 mM, (P<0.05) compared with the control group (10.0±4.2 mM and 4.2±0.3 mM, respectively). The concentrations of phosphomonoesters (PME) were higher in the patient group, although this was not significant. Constructing an anabolic charge (AC) based on absolute concentrations, [PME]/([PME] + [PDE]), the patients had a significantly larger AC than the control subjects, 0.29 vs. 0.16 (P<0.005). Absolute concentration measurements of phosphorus metabolites in the liver are feasible using a slice selective sequence, and the technique demonstrates significant differences between patients and healthy subjects.

    Keywords
    phosphorus MR spectroscopy, absolute concentrations, diffuse liver disease
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-24421 (URN)10.1007/s00330-004-2434-x (DOI)000227354900022 ()6524 (Local ID)6524 (Archive number)6524 (OAI)
    Available from: 2009-10-07 Created: 2009-10-07 Last updated: 2017-12-13
    2. Separation of advanced from mild fibrosis in diffuse liver disease using 31P magnetic resonance spectroscopy
    Open this publication in new window or tab >>Separation of advanced from mild fibrosis in diffuse liver disease using 31P magnetic resonance spectroscopy
    Show others...
    2008 (English)In: European Journal of Radiology, ISSN 0720-048X, E-ISSN 1872-7727, Vol. 66, no 2, p. 313-320Article in journal (Refereed) Published
    Abstract [en]

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

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

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

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

    Place, publisher, year, edition, pages
    Elsevier, 2008
    Keywords
    Absolute quantification; Phosphorus; MRS; Steatosis; In vivo
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-43125 (URN)10.1016/j.ejrad.2007.06.004 (DOI)000256140900026 ()17646074 (PubMedID)71944 (Local ID)71944 (Archive number)71944 (OAI)
    Projects
    NILB
    Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2019-06-14Bibliographically approved
    3. Separation of advanced from mild hepatic fibrosis by quantification of the hepatobiliary uptake of Gd-EOB-DTPA
    Open this publication in new window or tab >>Separation of advanced from mild hepatic fibrosis by quantification of the hepatobiliary uptake of Gd-EOB-DTPA
    Show others...
    2013 (English)In: European Radiology, ISSN 0938-7994, E-ISSN 1432-1084, Vol. 23, no 1, p. 174-181Article in journal (Refereed) Published
    Abstract [en]

    Objectives

    To apply dynamic contrast-enhanced (DCE) MRI on patients presenting with elevated liver enzymes without clinical signs of hepatic decompensation in order to quantitatively compare the hepatocyte-specific uptake of Gd-EOB-DTPA with histopathological fibrosis stage.

    Methods

    A total of 38 patients were prospectively examined using 1.5-T MRI. Data were acquired from regions of interest in the liver and spleen by using time series of single-breath-hold symmetrically sampled two-point Dixon 3D images (non-enhanced, arterial and venous portal phase; 3, 10, 20 and 30 min) following a bolus injection of Gd-EOB-DTPA (0.025 mmol/kg). The signal intensity (SI) values were reconstructed using a phase-sensitive technique and normalised using multiscale adaptive normalising averaging (MANA). Liver-to-spleen contrast ratios (LSC_N) and the contrast uptake rate (KHep) were calculated. Liver biopsy was performed and classified according to the Batts and Ludwig system.

    Results

    Area under the receiver-operating characteristic curve (AUROC) values of 0.71, 0.80 and 0.78, respectively, were found for KHep, LSC_N10 and LSC_N20 with regard to severe versus mild fibrosis. Significant group differences were found for KHep (borderline), LSC_N10 and LSC_N20.

    Conclusions

    Liver fibrosis stage strongly influences the hepatocyte-specific uptake of Gd-EOB-DTPA. Potentially the normalisation technique and KHep will reduce patient and system bias, yielding a robust approach to non-invasive liver function determination.

    Place, publisher, year, edition, pages
    Springer, 2013
    Keywords
    Quantification, Gd-EOB-DTPA, Dynamic contrast-enhanced MRI, Pharmacokinetics, Liver
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-87242 (URN)10.1007/s00330-012-2583-2 (DOI)000312324500022 ()
    Projects
    NILB
    Note

    Funding Agencies|Swedish Research Council|VR/M 2007-2884|Medical Research Council of South-east Sweden|FORSS 12621|Linkoping University, Linkoping University Hospital Research Foundations||County Council of Ostergotland||

    Available from: 2013-01-14 Created: 2013-01-14 Last updated: 2019-06-14
    4. Visual assessment of biliary excretion of Gd-EOB-DTPA in patients with suspected diffuse liver disease – a biopsy-controlled prospective study
    Open this publication in new window or tab >>Visual assessment of biliary excretion of Gd-EOB-DTPA in patients with suspected diffuse liver disease – a biopsy-controlled prospective study
    Show others...
    2015 (English)In: European Journal of Radiology Open, ISSN 2352-0477, Vol. 2, p. 19-25Article in journal (Refereed) Published
    Abstract [en]

    Objectives: To qualitatively evaluate late dynamic contrast phases, 10, 20 and 30 min, after administration of Gd-EOB-DTPA with regard to biliary excretion in patients presenting with elevated liver enzymes without any clinical signs of cirrhosis or hepatic decompensation and to compare the visual assessment of contrast agent excretion with histo-pathological fibrosis stage, contrast uptake parameters and blood tests.

    Methods: 29 patients were prospectively examined using 1.5-T MRI. The visually assessed presence (1) or absence (0) of contrast agent for each of five anatomical regions in randomly reviewed time-series was summarised on a four grade scale. The scores, including a total visual score, were related to the histo-pathological findings, the quantitative contrast agent uptake parameters and blood tests

    Results: No relationship between the fibrosis grade or contrast uptake parameters expressed as KHep or LSC_N could be established. A negative correlation between the visual assessment and ALP was found. Comparing a sub-group of cholestatic patients with fibrosis score and Gd-EOB-DTPAdynamic parameters did not add any additional significant correlation.

    Conclusions: In this prospective study with a limited number of patients we were not able to demonstrate a correlation between visually assessed biliary excretion of Gd-EOB-DTPA and  histo-pathological or contrast uptake parameters.

    Place, publisher, year, edition, pages
    Elsevier, 2015
    Keywords
    Gd-EOB-­DTPA, Dynamic contrast enhanced MRI, Liver, Bile, Excretion
    National Category
    Radiology, Nuclear Medicine and Medical Imaging Physical Chemistry
    Identifiers
    urn:nbn:se:liu:diva-90159 (URN)10.1016/j.ejro.2014.12.004 (DOI)
    Projects
    NILB
    Available from: 2013-03-20 Created: 2013-03-20 Last updated: 2019-06-14Bibliographically approved
  • 15.
    Norén, Bengt
    Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Health Sciences.
    Quantitative 31P magnetic resonance spectroscopy in diffuse liver disease2006Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    The studies in this thesis were delineated to evaluate the diagnostic possibilities in patients with diffuse liver disease by using phosphorus-31 MR spectroscopy and comparing the results with clinical, laboratory and histopathological findings. For this purpose in all 38 patients and 25 controls without evidence of liver disease were examined.

    In the first study 31P-MRS using slice selection (DRESS) was implemented to investigate the absolute concentrations of metabolites in human liver. The metabolite concentration quantification procedures included: 1. Determination of optimal depth for the in vivo measurements, 2. Mapping the detection coil characteristics, 3. Calculation of selected slice and liver volume ratios using simple segmentation procedures, and 4. Spectral analysis in the time domain. Patients with histopathologically proven diffuse liver disease (n = 9) and healthy individuals (n = 12) were examined. The patients had significantly lower concentrations of phosphodiesters (PDE) and ATP-ß compared with the control group. Constructing an anabolic charge (AC) based on absolute concentrations, [PME] / ([PME] + [PDE]), the patients had a significant larger AC than the control subjects, 0.29 vs. 0.16 (p < 0.005).

    In the second study the MRS technique was applied on two distinct groups of patients with diffuse chronic liver disorders, one group with steatosis and none-to-moderate inflammation (n = 13) and one group with severe fibrosis or cirrhosis (n = 16). All patients underwent liver biopsy and extensive biochemical evaluation. A control group (n = 13) was also included. Lower concentrations of PDE (p = 0.025) and a higher AC (p = 0.001) were found in the cirrhosis group compared to the control group.

    Using a PDE concentration of 10.5 mM as a cut-off value to discriminate between mild (stage 0-2) and advanced (stage 3-4) fibrosis the sensitivity and specificity were 81% and 69% respectively. An AC cut-off value of 0.27 showed a sensitivity of 93% and a specificity of 54%.

    In conclusion the results indicates that a decrease in PDE concentration is a marker of liver fibrosis and that AC is a potentially clinically useful parameter indiscriminating mild fibrosis from advanced. No significant relationship between the MRS data and the degree of steatosis or inflammation was found.

    List of papers
    1. Absolute quantification of human liver metabolite concentrations by localized in vivo 31P NMR spectroscopy in diffuse liver disease
    Open this publication in new window or tab >>Absolute quantification of human liver metabolite concentrations by localized in vivo 31P NMR spectroscopy in diffuse liver disease
    Show others...
    2005 (English)In: European Radiology, ISSN 0938-7994, E-ISSN 1432-1084, Vol. 15, no 1, p. 148-157Article in journal (Refereed) Published
    Abstract [en]

    Phosphorus-31 NMR spectroscopy using slice selection (DRESS) was used to investigate the absolute concentrations of metabolites in the human liver. Absolute concentrations provide more specific biochemical information compared to spectrum integral ratios. Nine patients with histopathologically proven diffuse liver disease and 12 healthy individuals were examined in a 1.5-T MR scanner (GE Signa LX Echospeed plus). The metabolite concentration quantification procedures included: (1) determination of optimal depth for the in vivo measurements, (2) mapping the detection coil characteristics, (3) calculation of selected slice and liver volume ratios using simple segmentation procedures and (4) spectral analysis in the time domain. The patients had significantly lower concentrations of phosphodiesters (PDE), 6.3±3.9 mM, and ATP-β, 3.6±1.1 mM, (P<0.05) compared with the control group (10.0±4.2 mM and 4.2±0.3 mM, respectively). The concentrations of phosphomonoesters (PME) were higher in the patient group, although this was not significant. Constructing an anabolic charge (AC) based on absolute concentrations, [PME]/([PME] + [PDE]), the patients had a significantly larger AC than the control subjects, 0.29 vs. 0.16 (P<0.005). Absolute concentration measurements of phosphorus metabolites in the liver are feasible using a slice selective sequence, and the technique demonstrates significant differences between patients and healthy subjects.

    Keywords
    phosphorus MR spectroscopy, absolute concentrations, diffuse liver disease
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-24421 (URN)10.1007/s00330-004-2434-x (DOI)000227354900022 ()6524 (Local ID)6524 (Archive number)6524 (OAI)
    Available from: 2009-10-07 Created: 2009-10-07 Last updated: 2017-12-13
    2. Separation of advanced from mild fibrosis in diffuse liver disease using 31P magnetic resonance spectroscopy
    Open this publication in new window or tab >>Separation of advanced from mild fibrosis in diffuse liver disease using 31P magnetic resonance spectroscopy
    Show others...
    2008 (English)In: European Journal of Radiology, ISSN 0720-048X, E-ISSN 1872-7727, Vol. 66, no 2, p. 313-320Article in journal (Refereed) Published
    Abstract [en]

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

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

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

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

    Place, publisher, year, edition, pages
    Elsevier, 2008
    Keywords
    Absolute quantification; Phosphorus; MRS; Steatosis; In vivo
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-43125 (URN)10.1016/j.ejrad.2007.06.004 (DOI)000256140900026 ()17646074 (PubMedID)71944 (Local ID)71944 (Archive number)71944 (OAI)
    Projects
    NILB
    Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2019-06-14Bibliographically approved
  • 16.
    Norén, Bengt
    et al.
    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.
    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.
    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.
    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.
    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.
    Prospective Evaluation of a Novel Quantification Method for the Discrimination of Mild and Severe Hepatic Fibrosis Using Gd-EOB-DTPA2012Conference paper (Other academic)
  • 17.
    Norén, Bengt
    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.
    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, Centre for Medical Imaging, Department of Radiology in Linköping. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Radiation Physics.
    Almer, Sven
    Linköping University, Department of Clinical and Experimental Medicine, Gastroenterology and Hepatology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medicine, Department of Endocrinology and Gastroenterology UHL.
    Kechagias, Stergios
    Linköping University, Department of Medical and Health Sciences, Internal Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medicine, Department of Endocrinology and Gastroenterology UHL.
    Ekstedt, Mattias
    Linköping University, Department of Clinical and Experimental Medicine, Gastroenterology and Hepatology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medicine, Department of Endocrinology and Gastroenterology UHL.
    Franzén, Lennart
    Medilab, Täby, Sweden.
    Wirell, Staffan
    Linköping University, Department of Medical and Health Sciences, Radiology. 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.
    Separation of advanced from mild fibrosis in diffuse liver disease using 31P magnetic resonance spectroscopy2008In: European Journal of Radiology, ISSN 0720-048X, E-ISSN 1872-7727, Vol. 66, no 2, p. 313-320Article in journal (Refereed)
    Abstract [en]

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

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

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

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

  • 18.
    Norén, Bengt
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Dahlström, Nils
    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.
    Forsgren, Mikael
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Kechagias, Stergios
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of 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.
    Wirell, Staffan
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences.
    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.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Visual assessment of biliary excretion of Gd-EOB-DTPA in patients with suspected diffuse liver disease – a biopsy-controlled prospective study2015In: European Journal of Radiology Open, ISSN 2352-0477, Vol. 2, p. 19-25Article in journal (Refereed)
    Abstract [en]

    Objectives: To qualitatively evaluate late dynamic contrast phases, 10, 20 and 30 min, after administration of Gd-EOB-DTPA with regard to biliary excretion in patients presenting with elevated liver enzymes without any clinical signs of cirrhosis or hepatic decompensation and to compare the visual assessment of contrast agent excretion with histo-pathological fibrosis stage, contrast uptake parameters and blood tests.

    Methods: 29 patients were prospectively examined using 1.5-T MRI. The visually assessed presence (1) or absence (0) of contrast agent for each of five anatomical regions in randomly reviewed time-series was summarised on a four grade scale. The scores, including a total visual score, were related to the histo-pathological findings, the quantitative contrast agent uptake parameters and blood tests

    Results: No relationship between the fibrosis grade or contrast uptake parameters expressed as KHep or LSC_N could be established. A negative correlation between the visual assessment and ALP was found. Comparing a sub-group of cholestatic patients with fibrosis score and Gd-EOB-DTPAdynamic parameters did not add any additional significant correlation.

    Conclusions: In this prospective study with a limited number of patients we were not able to demonstrate a correlation between visually assessed biliary excretion of Gd-EOB-DTPA and  histo-pathological or contrast uptake parameters.

  • 19.
    Norén, Bengt
    et al.
    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.
    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.
    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.
    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.
    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.
    Separation of advanced from mild hepatic fibrosis by quantification of the hepatobiliary uptake of Gd-EOB-DTPA2012Conference paper (Other academic)
  • 20.
    Norén, Bengt
    et al.
    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.
    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.
    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.
    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.
    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.
    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.
    Quantification of the hepatobiliary uptake of Gd-EOB-DTPA can separate advanced from mild fibrosis2012Conference paper (Other academic)
  • 21.
    Norén, Bengt
    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.
    Forsgren, Mikael Fredrik
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    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.
    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.
    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 Gastroentorology.
    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 Gastroentorology.
    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, Division of Radiological Sciences. 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.
    Separation of advanced from mild hepatic fibrosis by quantification of the hepatobiliary uptake of Gd-EOB-DTPA2013In: European Radiology, ISSN 0938-7994, E-ISSN 1432-1084, Vol. 23, no 1, p. 174-181Article in journal (Refereed)
    Abstract [en]

    Objectives

    To apply dynamic contrast-enhanced (DCE) MRI on patients presenting with elevated liver enzymes without clinical signs of hepatic decompensation in order to quantitatively compare the hepatocyte-specific uptake of Gd-EOB-DTPA with histopathological fibrosis stage.

    Methods

    A total of 38 patients were prospectively examined using 1.5-T MRI. Data were acquired from regions of interest in the liver and spleen by using time series of single-breath-hold symmetrically sampled two-point Dixon 3D images (non-enhanced, arterial and venous portal phase; 3, 10, 20 and 30 min) following a bolus injection of Gd-EOB-DTPA (0.025 mmol/kg). The signal intensity (SI) values were reconstructed using a phase-sensitive technique and normalised using multiscale adaptive normalising averaging (MANA). Liver-to-spleen contrast ratios (LSC_N) and the contrast uptake rate (KHep) were calculated. Liver biopsy was performed and classified according to the Batts and Ludwig system.

    Results

    Area under the receiver-operating characteristic curve (AUROC) values of 0.71, 0.80 and 0.78, respectively, were found for KHep, LSC_N10 and LSC_N20 with regard to severe versus mild fibrosis. Significant group differences were found for KHep (borderline), LSC_N10 and LSC_N20.

    Conclusions

    Liver fibrosis stage strongly influences the hepatocyte-specific uptake of Gd-EOB-DTPA. Potentially the normalisation technique and KHep will reduce patient and system bias, yielding a robust approach to non-invasive liver function determination.

  • 22.
    Norén, Bengt
    et al.
    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.
    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).
    Ressner, Marcus
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Wirell, Staffan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Medical Radiology.
    Almer, Sven
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Molecular and Clinical Medicine, Gastroenterology and Hepatology. Östergötlands Läns Landsting, Centre for Medicine, Department of Endocrinology and Gastroenterology UHL.
    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).
    Absolute quantification of human liver metabolite concentrations by localized in vivo 31P NMR spectroscopy in diffuse liver disease2005In: European Radiology, ISSN 0938-7994, E-ISSN 1432-1084, Vol. 15, no 1, p. 148-157Article in journal (Refereed)
    Abstract [en]

    Phosphorus-31 NMR spectroscopy using slice selection (DRESS) was used to investigate the absolute concentrations of metabolites in the human liver. Absolute concentrations provide more specific biochemical information compared to spectrum integral ratios. Nine patients with histopathologically proven diffuse liver disease and 12 healthy individuals were examined in a 1.5-T MR scanner (GE Signa LX Echospeed plus). The metabolite concentration quantification procedures included: (1) determination of optimal depth for the in vivo measurements, (2) mapping the detection coil characteristics, (3) calculation of selected slice and liver volume ratios using simple segmentation procedures and (4) spectral analysis in the time domain. The patients had significantly lower concentrations of phosphodiesters (PDE), 6.3±3.9 mM, and ATP-β, 3.6±1.1 mM, (P<0.05) compared with the control group (10.0±4.2 mM and 4.2±0.3 mM, respectively). The concentrations of phosphomonoesters (PME) were higher in the patient group, although this was not significant. Constructing an anabolic charge (AC) based on absolute concentrations, [PME]/([PME] + [PDE]), the patients had a significantly larger AC than the control subjects, 0.29 vs. 0.16 (P<0.005). Absolute concentration measurements of phosphorus metabolites in the liver are feasible using a slice selective sequence, and the technique demonstrates significant differences between patients and healthy subjects.

  • 23.
    Norén, Bengt
    et al.
    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.
    Morales, Olallo
    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.
    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.
    Renhet och kontrastbeslag - jämförelse mellan två tarmrengöringsmetoder vid colonröntgen2001In: Medicinska Riksstämman i Stockholm/Älvsjö,2001, 2001, p. 254-254Conference paper (Refereed)
  • 24.
    Norén, Bengt
    et al.
    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.
    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.
    Ressner, Marcus
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Lundberg, Peter
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Radio Physics. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Radiation Physics. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Quantification of liver metabolites with phosphorus-31 Magnetic Resonance Spectroscopy2002In: European Congress of Radiology March 1-5, 2002,2002, 2002, p. 353-353Conference paper (Refereed)
  • 25.
    Sörstedt, Erik
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Medical Radiology.
    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.
    Norén, Bengt
    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.
    Björnlert, U
    Malcherek, Per
    Linköping University, Department of Medicine and Care. Linköping University, Faculty of Health Sciences.
    Axelsson, Mathias
    Linköping University, Department of Medicine and Care. Linköping University, Faculty of Health Sciences.
    Johansson, James
    Linköping University, Department of Medicine and Care. Linköping University, Faculty of Health Sciences.
    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.
    Computed tomographic colonography: Comparison of two workstations2005In: Acta Radiologica, ISSN 0284-1851, E-ISSN 1600-0455, Vol. 46, no 7, p. 671-678Article in journal (Refereed)
    Abstract [en]

    Purpose: To compare two commercially available computed tomography (CT) colonography systems with respect to interobserver variability, the influence of level of expertise, and the gradual reduction of reviewing time for each system. Material and Methods: Two residents and two radiologists using Siemens CTAPP Colography software and Viatronix V3DColon software reviewed supine and prone CT acquisitions from 24 patients in a primary 3D endoluminal view. The observers graded each case with respect to technical quality and diagnostic value, assessed the presence of pathology, and indicated the time spent on the viewing. Results: Significant differences were found in technical quality ( P <0.001) and diagnostic value ( P <0.001) depending on which system was used, with higher scores for the Viatronix software. The agreement between specialists tended to be higher than that between residents (κ = 0.63 (0.30-0.95) vs. κ = 0.51 (0.21-0.81)), and the residents gave significantly ( P <0.001) higher scores of technical quality. However, the level of expertise had no significant impact on the assessments. We noted extensive variability in pathological lesions found by the different observers. The number of findings did not differ between workstations, but the viewers tended to report larger polyp sizes with the Viatronix software. The time needed for viewing decreased significantly from the first to the last examination viewed by each observer. Conclusion: Both the evaluated systems present trustworthy images of the human colon, but in a primary 3D setting the Viatronix software is favored owing to the userfriendly interface, higher experienced technical quality, and better diagnostic value. © 2005 Taylor & Francis.

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