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  • 1.
    Kihlberg, Johan
    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.
    Magnetic Resonance Imaging of Myocardial Deformation and Scarring in Coronary Artery Disease.2017Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Although improved treatments have reduced the rates of acute complications from myocardial infarction, sequelae such as heart failure and sudden death threaten the future wellbeing of those patients. Secondary prevention after myocardial infarction is related to cardiovascular risk factors and the effect of the infarct on left ventricular function. Cardiovascular magnetic resonance imaging (CMR) is necessary to determine the size of the infarct scar and can with great precision determine left ventricular volumes, left ventricular ejection fraction, and deformation (strain and torsion). The purpose of this thesis was to improve on CMR methods to facilitate image acquisition and post processing in patients with high risk of coronary artery disease (CAD).

    In Paper 1, a three-dimensional phase-sensitive inversion-recovery (3D PSIR) sequence was modified to measure T1 during a single breath hold. The measured T1 values were used to extrapolate a map of T1 relaxation, which avoided the time-consuming manual determination of the inversion time. The data collection consisted of phantom experiments, Monte Carlo simulations of the effect of various heart rates, and clinical investigation of 18 patients with myocardial infarction. Scar images created with the modified sequence were compared to those created with the standard sequence. The 3D PSIR sequence was able to measure T1 relaxation with a high accuracy up to 800 ms, which is in the suitable range for scar imaging. Simulated arrhythmias showed that the method was robust and able to tolerate some variation in heart rate. The modified sequence provides measurements of inversion time that can be used to facilitate standard scar imaging or to reconstruct synthetic scar images. Images of infarct scar obtained with the 3D PSIR sequence bore striking similarity to images obtained with the standard sequence.

    In Paper 2, 125 patients with high risk of CAD were investigated using the displacement encoding with stimulated echoes (DENSE) sequence. Image segments with infarct scar area >50% (transmurality) could be identified with a sensitivity of 95% and a specificity of 80% based on circumferential strain calculated from the DENSE measurements. The DENSE sequence was also applied in other directions, but its sensitivity and specificity to detect scar was lower than when used for circumferential strain.

    In Paper 3, 90 patients with high risk of CAD were examined by DENSE, tagging with harmonic phase (HARP) imaging and cine imaging with feature tracking (FT), to detect cardiac abnormalities as manifested in end-systolic circumferential strain. Circumferential strain calculated with DENSE had higher sensitivity and specificity than the competing methods to detect infarction with transmurality >50%. Global circumferential strain measured by DENSE correlated better with global parameters such as left ventricular ejection fraction, myocardial wall mass, left ventricular end-diastolic and end-systolic volume; than strain measured by FT or HARP.

    In Paper 4, myocardial torsion was investigated using DENSE, HARP, and FT in 48 patients with high risk of CAD. Torsion measured by each of the three methods was correlated with other global measures such as left ventricular ejection fraction, left ventricular mass, and left ventricular end-diastolic and end-systolic volumes. The torsion measurements obtained with DENSE had a stronger relationship with left ventricular ejection fraction, left ventricular mass, and volumes than those obtained with HARP or FT.

    DENSE was superior to the other methods for strain and torsion measurement and can be used to describe myocardial deformation quantitatively and objectively.

    List of papers
    1. Rapid T1 quantification based on 3D phase sensitive inversion recovery
    Open this publication in new window or tab >>Rapid T1 quantification based on 3D phase sensitive inversion recovery
    2010 (English)In: BMC Medical Imaging, ISSN 1471-2342, E-ISSN 1471-2342, Vol. 10, no 19Article in journal (Refereed) Published
    Abstract [en]

    BACKGROUND: In Contrast Enhanced Magnetic Resonance Imaging fibrotic myocardium can be distinguished from healthy tissue using the difference in the longitudinal T1 relaxation after administration of Gadolinium, the so-called Late Gd Enhancement. The purpose of this work was to measure the myocardial absolute T1 post-Gd from a single breath-hold 3D Phase Sensitivity Inversion Recovery sequence (PSIR). Equations were derived to take the acquisition and saturation effects on the magnetization into account.

    METHODS: The accuracy of the method was investigated on phantoms and using simulations. The method was applied to a group of patients with suspected myocardial infarction where the absolute difference in relaxation of healthy and fibrotic myocardium was measured at about 15 minutes post-contrast. The evolution of the absolute R1 relaxation rate (1/T1) over time after contrast injection was followed for one patient and compared to T1 mapping using Look-Locker. Based on the T1 maps synthetic LGE images were reconstructed and compared to the conventional LGE images.

    RESULTS: The fitting algorithm is robust against variation in acquisition flip angle, the inversion delay time and cardiac arrhythmia. The observed relaxation rate of the myocardium is 1.2 s-1, increasing to 6 - 7 s-1 after contrast injection and decreasing to 2 - 2.5 s-1 for healthy myocardium and to 3.5 - 4 s-1 for fibrotic myocardium. Synthesized images based on the T1 maps correspond very well to actual LGE images.

    CONCLUSIONS: The method provides a robust quantification of post-Gd T1 relaxation for a complete cardiac volume within a single breath-hold.

    National Category
    Engineering and Technology Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-59065 (URN)10.1186/1471-2342-10-19 (DOI)20716333 (PubMedID)
    Available from: 2010-09-08 Created: 2010-09-08 Last updated: 2017-12-12
    2. Clinical experience of strain imaging using DENSE for detecting infarcted cardiac segments
    Open this publication in new window or tab >>Clinical experience of strain imaging using DENSE for detecting infarcted cardiac segments
    Show others...
    2015 (English)In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 17, article id 50Article in journal (Refereed) Published
    Abstract [en]

    Background

    We hypothesised that myocardial deformation determined with magnetic resonance imaging (MRI) will detect myocardial scar.

    Methods

    Displacement Encoding with Stimulated Echoes (DENSE) was used to calculate left ventricular strain in 125 patients (29 women and 96 men) with suspected coronary artery disease. The patients also underwent cine imaging and late gadolinium enhancement. 57 patients had a scar area >1 % in at least one segment, 23 were considered free from coronary artery disease (control group) and 45 had pathological findings but no scar (mixed group). Peak strain was calculated in eight combinations: radial and circumferential strain in transmural, subendocardial and epicardial layers derived from short axis acquisition, and transmural longitudinal and radial strain derived from long axis acquisitions. In addition, the difference between strain in affected segments and reference segments, “differential strain”, from the control group was analysed.

    Results

    In receiver-operator-characteristic analysis for the detection of 50 % transmurality, circumferential strain performed best with area-under-curve (AUC) of 0.94. Using a cut-off value of -17 %, sensitivity was 95 % at a specificity of 80 %. AUC did not further improve with differential strain. There were significant differences between the control group and global strain circumferential direction (-17 % versus -12 %) and in the longitudinal direction (-13 % versus -10 %). Interobserver and scan-rescan reproducibility was high with an intraclass correlation coefficient (ICC) >0.93.

    Conclusions

    DENSE-derived circumferential strain may be used for the detection of myocardial segments with >50 % scar area. The repeatability of strain is satisfactory. DENSE-derived global strain agrees with other global measures of left ventricular ejection fraction.

    Place, publisher, year, edition, pages
    BioMed Central, 2015
    National Category
    Radiology, Nuclear Medicine and Medical Imaging
    Identifiers
    urn:nbn:se:liu:diva-119846 (URN)10.1186/s12968-015-0155-8 (DOI)000356652000001 ()26104510 (PubMedID)
    Available from: 2015-06-26 Created: 2015-06-26 Last updated: 2017-12-04
  • 2.
    Koppal, Sandeep
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Warntjes, Marcel
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. SyntheticMR AB, Linköping, Sweden.
    Swann, Jeremy
    School of Computing, University of Leeds, Leeds, United Kingdom.
    Dyverfeldt, Petter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences.
    Moreno, Rodrigo
    Linköping University, Center for Medical Image Science and Visualization (CMIV). KTH, Royal Institute of Technology, Stockholm, Sweden.
    Magee, Derek
    School of Computing, University of Leeds, Leeds, United Kingdom.
    Roberts, Nicholas
    Division of Brain Sciences, Department of Medicine, Institute of Neurology, Imperial College, London, United Kingdom.
    Zachrisson, Helene
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Forssell, Claes
    Region Östergötland, Heart and Medicine Center, Department of Thoracic and Vascular Surgery.
    Länne, Toste
    Linköping University, Center for Medical Image Science and Visualization (CMIV). 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 Thoracic and Vascular Surgery.
    Treanor, Darren
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences. Department of Pathology and Tumour Biology, Leeds Institute of Molecular Medicine, University of Leeds, Leeds, United Kingdom.
    de Muinck, Ebo
    Linköping University, Center for Medical Image Science and Visualization (CMIV). 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 Cardiology in Linköping.
    Quantitative Fat and R2* Mapping In Vivo to Measure Lipid-Rich Necrotic Core and Intraplaque Hemorrhage in Carotid Atherosclerosis2017In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 78, no 1, p. 285-296Article in journal (Refereed)
    Abstract [en]

    Purpose: The aim of this work was to quantify the extent of lipid-rich necrotic core (LRNC) and intraplaque hemorrhage (IPH) in atherosclerotic plaques.

    Methods: Patients scheduled for carotid endarterectomy underwent four-point Dixon and T1-weighted magnetic resonance imaging (MRI) at 3 Tesla. Fat and R2* maps were generated from the Dixon sequence at the acquired spatial resolution of 0.60 × 0.60 × 0.70 mm voxel size. MRI and three-dimensional (3D) histology volumes of plaques were registered. The registration matrix was applied to segmentations denoting LRNC and IPH in 3D histology to split plaque volumes in regions with and without LRNC and IPH.

    Results: Five patients were included. Regarding volumes of LRNC identified by 3D histology, the average fat fraction by MRI was significantly higher inside LRNC than outside: 12.64 ± 0.2737% versus 9.294 ± 0.1762% (mean ± standard error of the mean [SEM]; P < 0.001). The same was true for IPH identified by 3D histology, R2* inside versus outside IPH was: 71.81 ± 1.276 s−1 versus 56.94 ± 0.9095 s−1 (mean ± SEM; P < 0.001). There was a strong correlation between the cumulative fat and the volume of LRNC from 3D histology (R2 = 0.92) as well as between cumulative R2* and IPH (R2 = 0.94).

    Conclusion: Quantitative mapping of fat and R2* from Dixon MRI reliably quantifies the extent of LRNC and IPH.

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

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

  • 4.
    Andersson, Charlotta
    et al.
    Region Östergötland, Center for Diagnostics, Department of Clinical Physiology in Norrköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of 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.
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Lindström, Lena
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Carlhäll, Carljohan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Engvall, Jan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Phase-contrast MRI volume flow - a comparison of breath held and navigator based acquisitions2016In: BMC Medical Imaging, ISSN 1471-2342, E-ISSN 1471-2342, Vol. 16, no 26Article in journal (Refereed)
    Abstract [en]

    Background: Magnetic Resonance Imaging (MRI) 2D phase-contrast flow measurement has been regarded as the gold standard in blood flow measurements and can be performed with free breathing or breath held techniques. We hypothesized that the accuracy of flow measurements obtained with segmented phase-contrast during breath holding, and in particular higher number of k-space segments, would be non-inferior compared to navigator phase-contrast. Volumes obtained from anatomic segmentation of cine MRI and Doppler echocardiography were used for additional reference. Methods: Forty patients, five women and 35 men, mean age 65 years (range 53-80), were randomly selected and consented to the study. All underwent EKG-gated cardiac MRI including breath hold cine, navigator based free-breathing phase-contrast MRI and breath hold phase-contrast MRI using k-space segmentation factors 3 and 5, as well as transthoracic echocardiography within 2 days. Results: In navigator based free-breathing phase-contrast flow, mean stroke volume and cardiac output were 79.7 +/- 17.1 ml and 5071 +/- 1192 ml/min, respectively. The duration of the acquisition was 50 +/- 6 s. With k-space segmentation factor 3, the corresponding values were 77.7 ml +/- 17.5 ml and 4979 +/- 1211 ml/min (p = 0.15 vs navigator). The duration of the breath hold was 17 +/- 2 s. K-space segmentation factor 5 gave mean stroke volume 77.9 +/- 16.4 ml, cardiac output 5142 +/- 1197 ml/min (p = 0.33 vs navigator), and breath hold time 11 +/- 1 s. Anatomical segmentation of cine gave mean stroke volume and cardiac output 91.2 +/- 20.8 ml and 5963 +/- 1452 ml/min, respectively. Echocardiography was reliable in 20 of the 40 patients. The mean diameter of the left ventricular outflow tract was 20.7 +/- 1.5 mm, stroke volume 78.3 ml +/- 15.2 ml and cardiac output 5164 +/- 1249 ml/min. Conclusions: In forty consecutive patients with coronary heart disease, breath holding and segmented k-space sampling techniques for phase-contrast flow produced stroke volumes and cardiac outputs similar to those obtained with free-breathing navigator based phase-contrast MRI, using less time. The values obtained agreed fairly well with Doppler echocardiography while there was a larger difference when compared with anatomical volume determinations using SSFP (steady state free precession) cine MRI.

  • 5.
    Kihlberg, Johan
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Haraldsson, Henrik
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV). Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA .
    Sigfridsson, Andreas
    Department of Clinical Physiology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden .
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Engvall, Jan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Clinical experience of strain imaging using DENSE for detecting infarcted cardiac segments2015In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 17, article id 50Article in journal (Refereed)
    Abstract [en]

    Background

    We hypothesised that myocardial deformation determined with magnetic resonance imaging (MRI) will detect myocardial scar.

    Methods

    Displacement Encoding with Stimulated Echoes (DENSE) was used to calculate left ventricular strain in 125 patients (29 women and 96 men) with suspected coronary artery disease. The patients also underwent cine imaging and late gadolinium enhancement. 57 patients had a scar area >1 % in at least one segment, 23 were considered free from coronary artery disease (control group) and 45 had pathological findings but no scar (mixed group). Peak strain was calculated in eight combinations: radial and circumferential strain in transmural, subendocardial and epicardial layers derived from short axis acquisition, and transmural longitudinal and radial strain derived from long axis acquisitions. In addition, the difference between strain in affected segments and reference segments, “differential strain”, from the control group was analysed.

    Results

    In receiver-operator-characteristic analysis for the detection of 50 % transmurality, circumferential strain performed best with area-under-curve (AUC) of 0.94. Using a cut-off value of -17 %, sensitivity was 95 % at a specificity of 80 %. AUC did not further improve with differential strain. There were significant differences between the control group and global strain circumferential direction (-17 % versus -12 %) and in the longitudinal direction (-13 % versus -10 %). Interobserver and scan-rescan reproducibility was high with an intraclass correlation coefficient (ICC) >0.93.

    Conclusions

    DENSE-derived circumferential strain may be used for the detection of myocardial segments with >50 % scar area. The repeatability of strain is satisfactory. DENSE-derived global strain agrees with other global measures of left ventricular ejection fraction.

  • 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.
    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)

  • 8.
    Kihlberg, Johan
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences. Region Östergötland, Center for Diagnostics.
    Haraldsson, Henrik
    Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Engvall, Jan
    Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Practical Application of DENSE in Ischemic Heart Disease.2013Conference paper (Refereed)
  • 9.
    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.

  • 10.
    Björck, Hanna M.
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Physiology. Linköping University, Faculty of Health Sciences.
    Renner, Johan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology.
    Maleki, Shohreh
    Atherosclerosis Research Unit, Center for Molecular Medicine, Department of Medicine, Karolinska Institute, Sweden.
    Nilsson, Siv F.E.
    Linköping University, Department of Medical and Health Sciences, Pharmacology. Linköping University, Faculty of Health Sciences.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences.
    Folkersen, Lasse
    Atherosclerosis Research Unit, Center for Molecular Medicine, Department of Medicine, Karolinska Institute, Sweden.
    Karlsson, Matts
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology.
    Ebbers, Tino
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Centre, Department of Clinical Physiology UHL.
    Eriksson, Per
    Atherosclerosis Research Unit, Center for Molecular Medicine, Department of Medicine, Karolinska Institute, Sweden.
    Länne, Toste
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Centre, Department of Thoracic and Vascular Surgery in Östergötland.
    Characterization of Shear-Sensitive Genes in the NormalRat Aorta Identifies Hand2 as a Major Flow-ResponsiveTranscription Factor2012In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 7, no 12Article in journal (Refereed)
    Abstract [en]

    Objective: Shear forces play a key role in the maintenance of vessel wall integrity. Current understanding regarding shear-dependent gene expression is mainly based on in vitro or in vivo observations with experimentally deranged shear, hence reflecting acute molecular events in relation to flow. Our objective was to determine wall shear stress (WSS) in the rat aorta and study flow-dependent vessel wall biology under physiological conditions.

    Methods and Results: Animal-specific aortic WSS magnitude and vector direction were estimated using computational fluid dynamic simulation based on aortic geometry and flow information acquired by MRI. Two distinct flow pattern regions were identified in the normal rat aorta; the distal part of the inner curvature being exposed to low WSS and a non-uniform vector direction, and a region along the outer curvature being subjected to markedly higher levels of WSS and a uniform vector direction. Microarray analysis revealed a strong differential expression between the flow regions, particularly associated with transcriptional regulation. In particular, several genes related to Ca2+-signalling, inflammation, proliferation and oxidative stress were among the most highly differentially expressed.

    Conclusions: Microarray analysis validated the CFD-defined WSS regions in the rat aorta, and several novel flow-dependent genes were identified. The importance of these genes in relation to atherosusceptibility needs further investigation.

  • 11.
    Dahlström, Nils
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Quick, Petter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Forsgren, Mikael
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Persson, Anders
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Dual-Energy CT Detects Standard-Dose Gd-EOB-DTPA in the Hepatobiliary and Renal Systems of Patients Having Undergone Liver MRI2012Conference paper (Other academic)
  • 12.
    Kihlberg, Johan
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Haraldsson, Henrik
    Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Engvall, Jan
    Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Myocardial deformation (“Strain”) measured by DENSE reliably detects myocardial scar.2012Conference paper (Refereed)
  • 13.
    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)
  • 14.
    Forsgren, Mikael
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Ekstedt, Mattias
    Linköping University, Department of Clinical and Experimental Medicine, Gastroenterology and Hepatology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Endocrinology and Gastroenterology UHL.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Andregård, O.
    Dahlström, Nils
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Kechagias, Stergios
    Linköping University, Department of Medical and Health Sciences, Internal Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Endocrinology and Gastroenterology UHL.
    Almer, Sven
    Linköping University, Department of Clinical and Experimental Medicine, Gastroenterology and Hepatology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Endocrinology and Gastroenterology UHL.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences.
    Prospective evaluation of liver steatosis comparing stereological point-counting biopsy analysis and 1H MRS2012Conference paper (Other academic)
  • 15.
    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)
  • 16.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Dahlström, Nils
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Sandström, Per
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Clinical and Experimental Medicine, Surgery.
    Brismar, Torkel
    Department of Clinical Science, Intervention and Technology at Karolinska Institutet, Division of Medical Imaging and Technology, Karolinska University Hospital in Huddinge, Stockholm, Sweden.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Quantifying differences in hepatic uptake of the liver specific contrast agents Gd-EOB-DTPA and Gd-BOPTA: a pilot study2012In: European Radiology, ISSN 0938-7994, E-ISSN 1432-1084, Vol. 22, no 3, p. 642-653Article in journal (Refereed)
    Abstract [en]

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

  • 17.
    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)
  • 18.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Romu, Thobias
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences.
    Gjellan, Solveig
    Linköping University, Department of Medical and Health Sciences, Internal Medicine. Linköping University, Faculty of Health Sciences.
    Zanjani, Sepehr
    Linköping University, Department of Medical and Health Sciences, Internal Medicine. Linköping University, Faculty of Health Sciences.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping.
    Nyström, Fredrik
    Linköping University, Department of Medical and Health Sciences, Internal Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Centre, Department of Endocrinology.
    Borga, Magnus
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Validation of whole-­‐body adipose tissue quantification using air displacement plethysmometry2012In: ISMRM workshop on Fat-­‐Water Separation: Insights, Applications & Progress in MRI, 2012Conference paper (Other academic)
  • 19.
    Kechagias, Stergios
    et al.
    Linköping University, Department of Medical and Health Sciences, Internal Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Centre, Department of Endocrinology and Gastroenterology UHL.
    Zanjani, Sepehr
    Linköping University, Department of Medical and Health Sciences, Internal Medicine. Linköping University, Faculty of Health Sciences.
    Gjellan, Solveig
    Linköping University, Department of Medical and Health Sciences, Internal Medicine. Linköping University, Faculty of Health Sciences.
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Kihlberg, Johan
    Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization, CMIV. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping.
    Johansson, Lars
    Uppsala University.
    Kullberg, Joel
    Uppsala University.
    Ahlstrom, Hakan
    Uppsala University.
    Lindström, Torbjörn
    Linköping University, Department of Medical and Health Sciences, Internal Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Centre, Department of Endocrinology and Gastroenterology UHL.
    Nyström, Fredrik
    Linköping University, Department of Medical and Health Sciences, Internal Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Centre, Department of Endocrinology and Gastroenterology UHL.
    Effects of moderate red wine consumption on liver fat and blood lipids: a prospective randomized study2011In: Annals of Medicine, ISSN 0785-3890, E-ISSN 1365-2060, Vol. 43, no 7, p. 545-554Article in journal (Refereed)
    Abstract [en]

    Background : There have been no human prospective randomized studies of the amount of alcohol that can induce hepatic steatosis. less thanbrgreater than less thanbrgreater thanMethods : Thirty-two healthy women and twelve healthy men (34 +/- 9 years of age) were randomized to consume 150 ml of red wine/day for women (16 g ethanol/day) or double that amount for men (33 g ethanol/day), or to alcohol abstention for 90 days. Participants underwent proton-nuclear magnetic-resonance spectroscopy for measurement of hepatic triglyceride content (HTGC). Blood samples for assessment of cardiovascular risk were drawn before and after the intervention. less thanbrgreater than less thanbrgreater thanResults: After exclusion of three subjects with steatosis at baseline a trend towards increased HTGC was apparent for red wine (before median: 1.1%, range 0.2-3.9%, after median: 1.1%, range 0.5-5.2%, P = 0.059) a difference that was statistically significant compared with abstainers (p = 0.02). However, no subject developed hepatic steatosis. Low-density lipoprotein (LDL)-cholesterol was lowered by red wine (-0.3 mmol/l, SE-0.1, 95% CI-0.6 to -0.04). less thanbrgreater than less thanbrgreater thanConclusions: Moderate consumption of red wine during three months increased HTGC in subjects without steatosis at baseline. However, since not a single participant developed steatosis we suggest that the threshold of alcohol consumption to define nonalcoholic fatty liver disease should not be lower than the amount in our study.

  • 20.
    Dahlström, Nils
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Sandström, Per
    Linköping University, Department of Clinical and Experimental Medicine, Surgery. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Surgery in Östergötland.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Brismar, Torkel
    Karolinska Huddinge.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Quantified hepatobiliary Gd-EOB-DTPA uptake rate reflects hepatobiliary function in patients2011Conference paper (Refereed)
  • 21.
    Jackowski, Christian
    et al.
    Universität Zürich, Inst für Rechtsmedizin, Winterthurerstrasse 190/52, CH-8057 Zürich, Switzerland.
    Warntjes, Marcel
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Berge, Johan
    Rättsmedicinalverket, Rättsmedicinska avdelningen, Artillerigatan 12, 587 58 Linköping.
    Thali, Michael J.
    Univ Bern, Inst Forensic Medicine, Ctr Forens Imaging & Virtopsy, CH-3012 Bern, Switzerland.
    Persson, Anders
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences.
    Quantitative MRI in Isotropic Spatial Resolution for Forensic Soft Tissue Documentation. Why and How?2011In: Journal of Forensic Sciences, ISSN 0022-1198, E-ISSN 1556-4029, Vol. 56, no 1, p. 208-215Article in journal (Refereed)
    Abstract [en]

    A quantification of T1, T2, and PD in high isotropic resolution was performed on corpses. Isotropic and quantified postmortem magnetic resonance (IQpmMR) enables sophisticated 3D postprocessing, such as reformatting and volume rendering. The body tissues can be characterized by the combination of these three values. The values of T1, T2, and PD were given as coordinates in a T1-T2-PD space where similar tissue voxels formed clusters. Implementing in a volume rendering software enabled color encoding of specific tissues and pathologies in 3D models of the corpse similar to computed tomography, but with distinctively more powerful soft tissue discrimination. From IQpmMR data, any image plane at any contrast weighting may be calculated or 3D color-encoded volume rendering may be carried out. The introduced approach will enable future computer-aided diagnosis that, e.g., checks corpses for a hemorrhage distribution based on the knowledge of its T1-T2-PD vector behavior in a high spatial resolution.

  • 22.
    Kihlberg, Johan
    et al.
    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.
    Kalra, Mannudeep
    Massachusetts General Hospital, Boston, USA.
    Dahlström, Nils
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    De Geer, Jakob
    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.
    Rönn, Martin
    ContextVision, Linköping.
    Persson, Anders
    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.
    Olofsson, Fredrik
    ContextVision, Linköping.
    Bäck, Anni
    ContextVision, Linköping.
    Applying 2D and 3D Postprocessing Algorithms to MR Images: Does Image Quality Improve? Can MR Imaging Duration Be Reduced?2010In: In Proceedings of RSNA 2010, SSM22, 2010Conference paper (Refereed)
  • 23.
    Eriksson, Per
    et al.
    Linköping University, Department of Medicine and Health Sciences, Internal Medicine . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medicine, Department of Nephrology UHL.
    Mohammed, Ahmed Abdulilah
    Linköping University, Department of Medicine and Health Sciences, Radiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    De Geer, Jakob
    Linköping University, Department of Medicine and Health Sciences, Radiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    Persson, Anders
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    Granerus, Göran
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Nyström, Fredrik
    Linköping University, Department of Medicine and Health Sciences, Internal Medicine . Linköping University, Faculty of Health Sciences.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    Non-invasive investigations of potential renal artery stenosis in renal insufficiency2010In: Nephrology, Dialysis and Transplantation, ISSN 0931-0509, E-ISSN 1460-2385, Vol. 25, no 11, p. 3607-3614Article in journal (Refereed)
    Abstract [en]

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

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

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

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

  • 24.
    Warntjes, Marcel JB
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    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, Centre for Medical Imaging, Department of Radiology in Linköping.
    Engvall, Jan
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Rapid T1 quantification based on 3D phase sensitive inversion recovery2010In: BMC Medical Imaging, ISSN 1471-2342, E-ISSN 1471-2342, Vol. 10, no 19Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: In Contrast Enhanced Magnetic Resonance Imaging fibrotic myocardium can be distinguished from healthy tissue using the difference in the longitudinal T1 relaxation after administration of Gadolinium, the so-called Late Gd Enhancement. The purpose of this work was to measure the myocardial absolute T1 post-Gd from a single breath-hold 3D Phase Sensitivity Inversion Recovery sequence (PSIR). Equations were derived to take the acquisition and saturation effects on the magnetization into account.

    METHODS: The accuracy of the method was investigated on phantoms and using simulations. The method was applied to a group of patients with suspected myocardial infarction where the absolute difference in relaxation of healthy and fibrotic myocardium was measured at about 15 minutes post-contrast. The evolution of the absolute R1 relaxation rate (1/T1) over time after contrast injection was followed for one patient and compared to T1 mapping using Look-Locker. Based on the T1 maps synthetic LGE images were reconstructed and compared to the conventional LGE images.

    RESULTS: The fitting algorithm is robust against variation in acquisition flip angle, the inversion delay time and cardiac arrhythmia. The observed relaxation rate of the myocardium is 1.2 s-1, increasing to 6 - 7 s-1 after contrast injection and decreasing to 2 - 2.5 s-1 for healthy myocardium and to 3.5 - 4 s-1 for fibrotic myocardium. Synthesized images based on the T1 maps correspond very well to actual LGE images.

    CONCLUSIONS: The method provides a robust quantification of post-Gd T1 relaxation for a complete cardiac volume within a single breath-hold.

  • 25.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Dahlström, Nils
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Sandström, P
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Brismar, Torkel
    Karolinska institutet.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    The hepatic uptake of Gd-EOB-DTPA is strongly correlated with the uptake of Gd-BOPTA2010Conference paper (Other academic)
  • 26.
    Kihlberg, Johan
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    Klintström, Eva
    Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping. 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.
    Dahlgren, A-C
    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.
    Which Orthodontic Brackets Are Most Suitable for MRI?2010Conference paper (Refereed)
  • 27.
    Kihlberg, Johan
    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.
    Fransson, Sven-Göran
    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.
    Engvall, Jan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Maret, Eva
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Warntjes, Marcel
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Rommel, Franz
    Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Haematology UHL.
    Ackumulering av överskottsjärn kan bestämmas med MR2009In: Ackumulering av överskottsjärn kan bestämmas med MR, 2009Conference paper (Refereed)
    Abstract [sv]

    Järnöverskott kan vara toxiskt i kroppen. Järnöverskott ses fr a efter multipla blodtransfusioner vid vissa blodsjukdomar. Internationellt är den vanligaste orsaken thalassemi. Antalet patienter med denna problematik är i Sverige ännu begränsat. Järnöverskott kan leda till allvarlig, svårbehandlad hjärtsvikt man kan behandlas med chelaterande perorala läkemedel och styrs då i allmänhet utifrån ferritin/s. Vår hypotes var att överensstämmelsen mellan järnöverskott och transferrin är låg, att järnöverskott bättre karaktäriseras med MR som också kan differentiera mellan järnöverskott i  hjärta respektive lever.

  • 28.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Health Sciences.
    Johansson, Andreas
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Rydell, Joakim
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Health Sciences. Linköping University, Department of Medical and Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    Nyström, Fredrik H.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    Borga, Magnus
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Quantification of abdominal fat accumulation during hyperalimentation using MRI2009In: Proceedings of the ISMRM Annual Meeting (ISMRM'09), 2009, Berkeley, CA, USA: International Society for Magnetic Resonance in Medicine , 2009, p. 206-Conference paper (Other academic)
    Abstract [en]

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

  • 29.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Dahlström, Nils
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Sandström, P
    Freij, Anna
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Brismar, Torkel
    Karolinska institutet.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    The hepatic uptake of Gd-EOB-DTPA is strongly affected by the hepatobiliary function2009Conference paper (Other academic)
  • 30.
    Sandström, Per
    et al.
    Linköping University, Department of Clinical and Experimental Medicine, Surgery. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Surgery in Östergötland.
    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.
    Freij, Anna
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences.
    Brismar, Torkel
    Karolinska University Hospital, Stockholm, Sweden .
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Upptag i levern av kontrastmedlet Gd-EOB-DTPA påverkas kraftigt av leverfunktionen2009Conference paper (Other academic)
  • 31.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Dahlström, Nils
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Sandström, P
    Brismar, Torkel
    Karolinska institutet.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Department of Medical and Health Sciences, Radiology. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Faculty of Health Sciences.
    A liver function test based on measurement of liver specific contrast agent uptake2008Conference paper (Other academic)
  • 32.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Dahlström, Nils
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Radiology . Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Brismar, T
    Sandström, Per
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Clinical and Experimental Medicine, Surgery . Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Surgery in Östergötland.
    Kihlberg, Johan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Smedby, Örjan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Medical Radiology. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology UHL. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics . Linköping University, Department of Medicine and Health Sciences, Radiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Radiation Physics. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    A liver function test based on measurement of liver-specific contrast agent uptake2008In: Proceedings 16th Scientific meeting, ISMRM,2008, 2008Conference paper (Other academic)
    Abstract [en]

      

  • 33.
    Dahlström, Nils
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Brismar, Torkel
    Karolinska institutet.
    Sandström, P
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiation Physics. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Radiology. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Leverfunktionsundersökning med leverspecifikt MR-kontrastmedel2008Conference paper (Other academic)
  • 34.
    Larsson, Martin
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Health Sciences.
    Persson, Anders
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    Eriksson, Per
    Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medicine, Department of Nephrology.
    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.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    Renal artery stenosis: extracting quantitative parameters with a mathematical model fitted to magnetic resonance blood flow data2008In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 27, no 1, p. 140-147Article in journal (Refereed)
    Abstract [en]

    Purpose: To investigate the feasibility of quantitative parameter extraction from a mathematical model fitted to renal artery magnetic resonance flow data.

    Material and methods: Sixteen subjects, 8 patients and 8 normal controls, were examined with cine phase-contrast velocity measurements, and blood flow data from the aorta and both renal arteries were extracted by means of contour detection. A mathematical model with eight parameters describing the time, duration and amplitude of the systolic acceleration and the diastolic deceleration was fitted to the aorta and renal artery blood flow data from each subject. The curve fitting was evaluated with R2 values. Statistical analysis was performed with unpaired Wilcoxon tests and stepwise logistic regression.

    Results: Three data sets out of 48 yielded R2 values below 0.80 and were considered unreliable for parameter estimation. Basal flow was significantly, and systolic peak amplitude almost significantly, lower in stenotic arteries. Logistic regression indicated that two parameters describing basal flow and the duration of acceleration can accurately predict stenosis.

    Conclusion: The results suggest that it is technically feasible to fit a mathematical model to renal blood flow data, extracting quantitative parameters that may prove useful for quantification and diagnosis of renal artery stenosis.

1 - 34 of 34
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