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  • 1.
    Abbott, Rebecca
    et al.
    Northwestern Univ, IL 60611 USA.
    Peolsson, Anneli
    Linköping University, Department of Medical and Health Sciences, Division of Physiotherapy. Linköping University, Faculty of Medicine and Health Sciences.
    West, Janne
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Medicine and Health Sciences.
    Elliott, James M.
    Northwestern Univ, IL 60611 USA; Univ Queensland, Australia; Zurich Univ Appl Sci, Switzerland.
    Åslund, Ulrika
    Linköping University, Department of Medical and Health Sciences, Division of Physiotherapy. Linköping University, Faculty of Medicine and Health Sciences.
    Karlsson, Anette
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    The qualitative grading of muscle fat infiltration in whiplash using fat and water magnetic resonance imaging2018In: The spine journal, ISSN 1529-9430, E-ISSN 1878-1632, Vol. 18, no 5, p. 717-725Article in journal (Refereed)
    Abstract [en]

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

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

    PURPOSE:

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

    RESULTS:

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

    CONCLUSION:

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

  • 3.
    Dahlqvist Leinhard, Olof
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Romu, Thobias
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Karlsson, Anette
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Borga, Magnus
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    High resolution isotropic whole-­‐body symmetrically sampled two point Dixon acquisition imaging at 3T2012In: ISMRM workshop on Fat-­‐Water Separation: Insights, Applications & Progress in MRI, 2012Conference paper (Other academic)
  • 4.
    Gerdle, Björn
    et al.
    Linköping University, Department of Medical and Health Sciences, Rehabilitation Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Anaesthetics, Operations and Specialty Surgery Center, Pain and Rehabilitation Center.
    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.
    Bengtsson, Ann
    Linköping University, Department of Clinical and Experimental Medicine, Rheumatology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Rheumatology.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Sören, B.
    Linköping University, Department of Clinical and Experimental Medicine, Rheumatology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Rheumatology.
    Karlsson, Anette
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, Faculty of Health Sciences.
    Brandejsky, Vaslav
    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.
    Lund, Eva
    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, 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.
    Decreased muscle concentrations of ATP and PCR in the quadriceps muscle of fibromyalgia patients – A 31P-MRS study2013In: European Journal of Pain, ISSN 1090-3801, E-ISSN 1532-2149, Vol. 17, no 8, p. 1205-1215Article in journal (Refereed)
    Abstract [en]

    BACKGROUND AND METHODS:

    Fibromyalgia (FMS) has a prevalence of approximately 2% in the population. Central alterations have been described in FMS, but there is not consensus with respect to the role of peripheral factors for the maintenance of FMS. 31P magnetic resonance spectroscopy (31P-MRS) has been used to investigate the metabolism of phosphagens in muscles of FMS patients, but the results in the literature are not in consensus. The aim was to investigate the quantitative content of phosphagens and pH in resting quadriceps muscle of patients with FMS (n = 19) and in healthy controls (Controls; n = 14) using (31) P-MRS. It was also investigated whether the concentrations of these substances correlated with measures of pain and/or physical capacity.

    RESULTS:

    Significantly lower concentrations of adenosine triphosphate (ATP) and phosphocreatinine (PCr; 28-29% lower) were found in FMS. No significant group differences existed with respect to inorganic phosphate (Pi), Pi/PCr and pH. The quadriceps muscle fat content was significantly higher in FMS than in Controls [FMS: 9.0 ± 0.5% vs. Controls: 6.6 ± 0.6%; (mean ± standard error); P = 0.005]. FMS had significantly lower hand and leg capacity according to specific physical test, but there were no group differences in body mass index, subjective activity level and in aerobic fitness. In FMS, the specific physical capacity in the leg and the hand correlated positively with the concentrations of ATP and PCr; no significant correlations were found with pain intensities.

    CONCLUSIONS:

    Alterations in intramuscular ATP, PCr and fat content in FMS probably reflect a combination of inactivity related to pain and dysfunction of muscle mitochondria.

  • 5.
    Giambini, Hugo
    et al.
    Mayo Clin, MN 55905 USA.
    Hatta, Taku
    Mayo Clin, MN USA.
    Gorny, Krzysztof R.
    Mayo Clin, MN USA.
    Widholm, Per
    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. Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences.
    Karlsson, Anette
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Adkins, Mark C.
    Mayo Clin, MN USA.
    Zhao, Chunfeng
    Mayo Clin, MN 55905 USA; Mayo Clin, MN USA.
    An, Kai-Nan
    Mayo Clin, MN 55905 USA; Mayo Clin, MN USA.
    INTRAMUSCULAR FAT INFILTRATION EVALUATED BY MAGNETIC RESONANCE IMAGING PREDICTS THE EXTENSIBILITY OF THE SUPRASPINATUS MUSCLE2018In: Muscle and Nerve, ISSN 0148-639X, E-ISSN 1097-4598, Vol. 57, no 1, p. 129-135Article in journal (Refereed)
    Abstract [en]

    Introduction: Rotator cuff (RC) tears result in muscle atrophy and fat infiltration within the RC muscles. An estimation of muscle quality and deformation, or extensibility, is useful in selecting the most appropriate surgical procedure. We determined if noninvasive quantitative assessment of intramuscular fat using MRI could be used to predict extensibility of the supraspinatus muscle. Methods: Seventeen cadaveric shoulders were imaged to assess intramuscular fat infiltration. Extensibility and histological evaluations were then performed. Results: Quantitative fat infiltration positively correlated with histological findings and presented a positive correlation with muscle extensibility (r=0.69; P=0.002). Extensibility was not significantly different between shoulders graded with a higher fat content versus those with low fat when implementing qualitative methods. Discussion: A noninvasive prediction of whole-muscle extensibility may directly guide pre-operative planning to determine if the torn edge could efficiently cover the original footprint while aiding in postoperative evaluation of RC repair.

  • 6.
    Karlsson, Anette
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    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.
    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.
    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.
    Automated Whole Body Muscle Segmentation & Classification2012In: ISMRM workshop on Fat-­‐Water Separation: Insights, Applications & Progress in MRI, 2012Conference paper (Other academic)
  • 7.
    Karlsson, Anette
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    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.
    Vallin, Anna
    Linköping University, Center for Medical Image Science and Visualization, CMIV.
    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.
    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.
    Automated Whole Body Muscle Quantification Based on a 10 min MR-Exam2012In: Proceedings of the annual meeting of the International Society for Magnetic Resonance in Medicine (ISMRM 2012), 2012Conference paper (Other academic)
  • 8.
    Karlsson, Anette
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    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).
    Åslund, Ulrika
    Linköping University, Department of Medical and Health Sciences, Division of Physiotherapy. Linköping University, Faculty of Medicine and Health Sciences.
    West, Janne
    Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences.
    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).
    Smedby, Örjan
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV). KTH Royal Institute Technology, Sweden.
    Zsigmond, Peter
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Department of Neurosurgery.
    Peolsson, Anneli
    Linköping University, Department of Medical and Health Sciences, Division of Physiotherapy. Linköping University, Faculty of Medicine and Health Sciences.
    An Investigation of Fat Infiltration of the Multifidus Muscle in Patients With Severe Neck Symptoms Associated With Chronic Whiplash-Associated Disorder2016In: Journal of Orthopaedic and Sports Physical Therapy, ISSN 0190-6011, E-ISSN 1938-1344, Vol. 46, no 10, p. 886-893Article in journal (Refereed)
    Abstract [en]

    STUDY DESIGN: Cross-sectional study. BACKGROUND: Findings of fat infiltration in cervical spine multifidus, as a sign of degenerative morphometric changes due to whiplash injury, need to be verified. OBJECTIVES: To develop a method using water/fat magnetic resonance imaging (MRI) to investigate fat infiltration and cross-sectional area of multifidus muscle in individuals with whiplash associated disorders (WADS) compared to healthy controls. METHODS: Fat infiltration and cross-sectional area in the multifidus muscles spanning the C4 to C7 segmental levels were investigated by manual segmentation using water/fat-separated MRI in 31 participants with WAD and 31 controls, matched for age and sex. RESULTS: Based on average values for data spanning C4 to C7, participants with severe disability related to WAD had 38% greater muscular fat infiltration compared to healthy controls (P = .03) and 45% greater fat infiltration compared to those with mild to moderate disability related to WAD (P = .02). There were no significant differences between those with mild to moderate disability and healthy controls. No significant differences between groups were found for multifidus cross-sectional area. Significant differences were observed for both cross-sectional area and fat infiltration between segmental levels. CONCLUSION: Participants with severe disability after a whiplash injury had higher fat infiltration in the multifidus compared to controls and to those with mild/moderate disability secondary to WAD. Earlier reported findings using T1-weighted MRI were reproduced using refined imaging technology. The results of the study also indicate a risk when segmenting single cross-sectional slices, as both cross-sectional area and fat infiltration differ between cervical levels.

  • 9.
    Karlsson, Anette
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering.
    Linge, Jennifer
    Advanced MR Analytics AB.
    West, Janne
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Medicine and Health Sciences.
    Bell, Jimmy
    Westminster University, London, UK.
    Borga, Magnus
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering.
    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.
    Defining Sarcopenia with MRI - Establishing Threshold Values within a Large-Scale Population Study2016Conference paper (Other academic)
    Abstract [en]

    PURPOSE

    To identify gender specific threshold values for sarcopenia detection for lean thigh muscle tissue volume quantified using MRI.

    METHOD AND MATERIALS

    Current gender-specific thresholds for sarcopenia detection are based on quantification on appendicular lean tissue normalized with height^2 using DXA (7.26 kg/m2 for men and 5.45 kg/m2 for women). In this study 3514 subjects (1548 males and 1966 females) in the imaging subcohort of UK Biobank with paired DXA and MRI scans were included. The age range was 45 to 78 years. The total lean thigh volume normalized with height2 (TTVi) was determined with a 6 minutes neck to knee 2-point Dixon MRI protocol using a 1.5T MR-scanner (Siemens, Germany) followed by analysis with AMRA® Profiler (AMRA, Sweden). The appendicular lean tissue mass normalized with height2 (ALTMi) was assessed using DXA (GE-Lunar iDXA). Subjects with ALTMi lower than the gender specific threshold were categorized as sarcopenic. Gender specific threshold values were determined for detection of sarcopenic subjects based on TTVi optimizing sensitivity and specificity. Area under receiver operator curve (AUROC) was calculated as well as the linear correlation between TTVi and ALTMi.

    RESULTS

    A threshold value of TTVi = 3.64 l/m2 provided a sensitivity and specificity of 0.88 for sarcopenia detection in males. The AUROC was 0.96. Similarly, a TTVi < 2.76 l/m2 identified sarcopenic female subjects with a sensitivity and specificity of 0.89. The corresponding AUROC was 0.96. The linear correlation between TTVi and ALTMi was 0.93 (99%CI: 0.93-0.94).

    CONCLUSION

    MRI-based quantification of total lean thigh volume normalized with height^2 could be used to categorize sarcopenia in the study group. Threshold values are suggested.

    CLINICAL RELEVANCE/APPLICATION

    The study suggests that sarcopenia can be diagnosed using a rapid MRI scan with high sensitivity and specificity.

  • 10.
    Karlsson, Anette
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Magnusson, Maria
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
    Lundberg, Peter
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping.
    Successful Motion Correction in Reconstruction of Radial MRI2011Conference paper (Refereed)
  • 11.
    Karlsson, Anette
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Rosander, Johannes
    Advanced MR Analytics AB, Linköping, Sweden.
    Romu, Thobias
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Tallberg, Joakim
    Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Grönqvist, Anders
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Borga, Magnus
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of 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.
    Automatic and quantitative assessment of regional muscle volume by multi-atlas segmentation using whole-body water–fat MRI2015In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 41, no 6, p. 1558-1569Article in journal (Refereed)
    Abstract [en]

    Purpose

    To develop and demonstrate a rapid whole-body magnetic resonance imaging (MRI) method for automatic quantification of total and regional skeletal muscle volume.

    Materials and Methods

    The method was based on a multi-atlas segmentation of intensity corrected water–fat separated image volumes. Automatic lean muscle tissue segmentations were achieved by nonrigid registration of atlas datasets with 10 different manually segmented muscle groups. Ten subjects scanned at 1.5 T and 3.0 T were used as atlases, initial validation and optimization. Further validation used 11 subjects scanned at 3.0 T. The automated and manual segmentations were compared using intraclass correlation, true positive volume fractions, and delta volumes.

    Results

    For the 1.5 T datasets, the intraclass correlation, true positive volume fractions (mean ± standard deviation, SD), and delta volumes (mean ± SD) were 0.99, 0.91 ± 0.02, −0.10 ± 0.70L (whole body), 0.99, 0.93 ± 0.02, 0.01 ± 0.07L (left anterior thigh), and 0.98, 0.80 ± 0.07, −0.08 ± 0.15L (left abdomen). The corresponding values at 3.0 T were 0.97, 0.92 ± 0.03, −0.17 ± 1.37L (whole body), 0.99, 0.93 ± 0.03, 0.03 ± 0.08L (left anterior thigh), and 0.89, 0.90 ± 0.04, −0.03 ± 0.42L (left abdomen). The validation datasets showed similar results.

    Conclusion

    The method accurately quantified the whole-body skeletal muscle volume and the volume of separate muscle groups independent of field strength and image resolution. 

  • 12.
    Karlsson, Anette
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Rosander, Johannes
    Advanced MR Analytics AB, Linköping, Sweden.
    Romu, Thobias
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Tallberg, Joakim
    Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Grönqvist, Anders
    Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Borga, Magnus
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of 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.
    Automatic and Quantitative Assessment of Total and Regional Muscle Tissue Volume using Multi-Atlas Segmentation2014Conference paper (Other academic)
    Abstract [en]

    Accurate and precise assessment of human muscle tissue is important for further understanding of different muscle diseases and syndromes. We present a rapid whole body MR method for automatic quantification of total and regional muscle volume. The method is based on multi-atlas segmentation of intensity corrected water-fat separated images. The method was validated with a leave-one-out approach, using manually segmented atlases from 10 subjects as ground truth. The result gave a coefficient of variation on total muscle volume equal to 1.25±1.35 % (mean ± standard deviation). The method enables cost-efficient large-scale studies, investigating conditions such as sarcopenia and muscular dystrophies.

  • 13.
    Karlsson, Anette
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Rosander, Johannes
    Advanced MR Analytics AB, Linköping, Sweden.
    Tallberg, Joakim
    Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Grönqvist, Anders
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    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. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Automatic and Quantitative Assessment of Total and Regional Muscle Tissue Volume using Multi-Atlas Segmentation2015In: International Society for Magnetic Resonance in Medicince Annual Meeting: Proceedings, 2015Conference paper (Other academic)
    Abstract [en]

    The purpose is to develop and demonstrate a rapid whole-body MRI method for automatic quantification of total and regional lean skeletal muscle volume. Quantitative water and fat separated image volumes of the whole body are manually segmented and used as atlases. The atlases are non-rigidly registered onto to a new image volume and the muscle groups are classified using a voting scheme. A leave-one-out approach with subjects scanned in a 1.5 T and a 3.0 T scanner is used for validation. The method quantifies the whole-body skeletal muscle volumes and the volumes of separate muscle groups independently of image resolution.

  • 14.
    Karlsson, Anette
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Rosander, Johannes
    Tallberg, Joakim
    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.
    Borga, Magnus
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Whole Body Muscle Classification using Multiple Prototype Voting2013Conference paper (Other academic)
  • 15.
    Peolsson, Anneli
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Physiotherapy. Linköping University, Faculty of Medicine and Health Sciences.
    Karlsson, Anette
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ghafouri, Bijar
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Pain and Rehabilitation Center.
    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).
    Engström, Maria
    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).
    Jönsson, Margaretha
    Linköping University, Department of Medical and Health Sciences, Division of Physiotherapy. Linköping University, Faculty of Medicine and Health Sciences. Herrgardets Vardcentral, Sweden.
    Wåhlén, Karin
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Pain and Rehabilitation Center.
    Romu, Thobias
    Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Borga, Magnus
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Kristjansson, Eythor
    Univ Iceland, Iceland.
    Bahat, Hilla Sarig
    Univ Haifa, Israel.
    German, Dmitry
    Univ Haifa, Israel.
    Zsigmond, Peter
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Department of Neurosurgery.
    Peterson, Gunnel
    Linköping University, Department of Medical and Health Sciences, Division of Physiotherapy. Linköping University, Faculty of Medicine and Health Sciences. Uppsala Univ, Sweden.
    Pathophysiology behind prolonged whiplash associated disorders: study protocol for an experimental study2019In: BMC Musculoskeletal Disorders, ISSN 1471-2474, E-ISSN 1471-2474, Vol. 20, article id 51Article in journal (Refereed)
    Abstract [en]

    BackgroundThere is insufficient knowledge of pathophysiological parameters to understand the mechanism behind prolonged whiplash associated disorders (WAD), and it is not known whether or not changes can be restored by rehabilitation. The aims of the projects are to investigate imaging and molecular biomarkers, cervical kinaesthesia, postural sway and the association with pain, disability and other outcomes in individuals with longstanding WAD, before and after a neck-specific exercise intervention. Another aim is to compare individuals with WAD with healthy controls.MethodsParticipants are a sub-group (n=30) of individuals recruited from an ongoing randomized controlled study (RCT). Measurements in this experimental prospective study will be carried out at baseline (before intervention) and at a three month follow-up (end of physiotherapy intervention), and will include muscle structure and inflammation using magnetic resonance imaging (MRI), brain structure and function related to pain using functional MRI (fMRI), muscle function using ultrasonography, biomarkers using samples of blood and saliva, cervical kinaesthesia using the butterfly test and static balance test using an iPhone app. Association with other measures (self-reported and clinical measures) obtained in the RCT (e.g. background data, pain, disability, satisfaction with care, work ability, quality of life) may be investigated. Healthy volunteers matched for age and gender will be recruited as controls (n=30).DiscussionThe study results may contribute to the development of improved diagnostics and improved rehabilitation methods for WAD.Trial registrationClinicaltrial.gov Protocol ID: NCT03664934, initial release 09/11/2018.

  • 16.
    Thomas, Marianna S
    et al.
    Department of Radiology, Norfolk & Norwich University Hospital, Norwich, UK..
    Newman, David
    Department of Radiology, Norfolk & Norwich University Hospital, Norwich, UK..
    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.
    Karlsson, Anette
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Rosander, Johannes
    Advanced MR Analytics AB, Linköping, Sweden.
    Kasmai, Bahman
    Department of Radiology Norfolk & Norwich University Hospital, United Kingdom.
    Greenwood, Richard
    Department of Radiology Norfolk & Norwich University Hospital, United Kingdom.
    Malcolm, Paul N
    Department of Radiology Norfolk & Norwich University Hospital, United Kingdom.
    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.
    Toms, Andoni P
    Department of Radiology Norfolk & Norwich University Hospital, United Kingdom.
    Test-retest reliability of automated whole body and compartmental muscle volume measurements on a wide bore 3T MR system2014In: European Radiology, ISSN 0938-7994, E-ISSN 1432-1084, Vol. 24, no 9, p. 2279-2291Article in journal (Refereed)
    Abstract [en]

    PURPOSE:

    To measure the test-retest reproducibility of an automated system for quantifying whole body and compartmental muscle volumes using wide bore 3 T MRI.

    MATERIALS AND METHODS:

    Thirty volunteers stratified by body mass index underwent whole body 3 T MRI, two-point Dixon sequences, on two separate occasions. Water-fat separation was performed, with automated segmentation of whole body, torso, upper and lower leg volumes, and manually segmented lower leg muscle volumes.

    RESULTS:

    Mean automated total body muscle volume was 19·32 L (SD9·1) and 19·28 L (SD9·12) for first and second acquisitions (Intraclass correlation coefficient (ICC) = 1·0, 95 % level of agreement -0·32-0·2 L). ICC for all automated test-retest muscle volumes were almost perfect (0·99-1·0) with 95 % levels of agreement 1.8-6.6 % of mean volume. Automated muscle volume measurements correlate closely with manual quantification (right lower leg: manual 1·68 L (2SD0·6) compared to automated 1·64 L (2SD 0·6), left lower leg: manual 1·69 L (2SD 0·64) compared to automated 1·63 L (SD0·61), correlation coefficients for automated and manual segmentation were 0·94-0·96).

    CONCLUSION:

    Fully automated whole body and compartmental muscle volume quantification can be achieved rapidly on a 3 T wide bore system with very low margins of error, excellent test-retest reliability and excellent correlation to manual segmentation in the lower leg.

    KEY POINTS:

    • Sarcopaenia is an important reversible complication of a number of diseases. • Manual quantification of muscle volume is time-consuming and expensive. • Muscles can be imaged using in and out of phase MRI. • Automated atlas-based segmentation can identify muscle groups. • Automated muscle volume segmentation is reproducible and can replace manual measurements.

  • 17.
    West, Janne
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Medicine and Health Sciences.
    Romu, Thobias
    Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Adv MR Analyt AB, Linkoping, Sweden.
    Thorell, Sofia
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Sweden.
    Lindblom, Hanna
    Linköping University, Department of Medical and Health Sciences, Division of Physiotherapy. Linköping University, Faculty of Medicine and Health Sciences.
    Berin, Emilia
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences.
    Spetz Holm, Anna-Clara
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center of Paediatrics and Gynaecology and Obstetrics, Department of Gynaecology and Obstetrics in Linköping.
    Lindh Åstrand, Lotta
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center of Paediatrics and Gynaecology and Obstetrics, Department of Gynaecology and Obstetrics in Linköping.
    Karlsson, Anette
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Borga, Magnus
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Adv MR Analyt AB, Linkoping, Sweden.
    Hammar, Mats
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center of Paediatrics and Gynaecology and Obstetrics, Department of Gynaecology and Obstetrics in Linköping.
    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). Adv MR Analyt AB, Linkoping, Sweden.
    Precision of MRI-based body composition measurements of postmenopausal women2018In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 13, no 2, article id e0192495Article in journal (Refereed)
    Abstract [en]

    Objectives To determine precision of magnetic resonance imaging (MRI) based fat and muscle quantification in a group of postmenopausal women. Furthermore, to extend the method to individual muscles relevant to upper-body exercise. Materials and methods This was a sub-study to a randomized control trial investigating effects of resistance training to decrease hot flushes in postmenopausal women. Thirty-six women were included, mean age 56 +/- 6 years. Each subject was scanned twice with a 3.0T MR-scanner using a whole-body Dixon protocol. Water and fat images were calculated using a 6-peak lipid model including R2*-correction. Body composition analyses were performed to measure visceral and subcutaneous fat volumes, lean volumes and muscle fat infiltration (MFI) of the muscle groups thigh muscles, lower leg muscles, and abdominal muscles, as well as the three individual muscles pectoralis, latissimus, and rhomboideus. Analysis was performed using a multi-atlas, calibrated water-fat separated quantification method. Liver-fat was measured as average proton density fat-fraction (PDFF) of three regions-of-interest. Precision was determined with Bland-Altman analysis, repeatability, and coefficient of variation. Results All of the 36 included women were successfully scanned and analysed. The coefficient of variation was 1.1% to 1.5% for abdominal fat compartments (visceral and subcutaneous), 0.8% to 1.9% for volumes of muscle groups (thigh, lower leg, and abdomen), and 2.3% to 7.0% for individual muscle volumes (pectoralis, latissimus, and rhomboideus). Limits of agreement for MFI was within +/- 2.06% for muscle groups and within +/- 5.13% for individual muscles. The limits of agreement for liver PDFF was within +/- 1.9%. Conclusion Whole-body Dixon MRI could characterize a range of different fat and muscle compartments with high precision, including individual muscles, in the study-group of postmenopausal women. The inclusion of individual muscles, calculated from the same scan, enables analysis for specific intervention programs and studies.

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