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  • 1.
    Bolger, Ann F
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Heiberg, Einar
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Dyverfeldt, Petter
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Carlsson, Mats
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Johansson, P
    Markenroth, K
    Sigfridsson, Andreas
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Engvall, Jan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Ebbers, Tino
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Arheden, H
    Tredimensionellt MR-blodflöde och diastolisk kinetisk energi kvantiferat med magnetisk resonanstomografi efter kirurgisk vänsterkammarrekonstruktion. Ny teknik för utvärdering av kammarfunktion.2007In: Riksstämman,2007, 2007Conference paper (Other academic)
  • 2.
    Bolger, Ann F
    et al.
    Linköping University, Department of Medicine and Care, Center for Medical Image Science and Visualization. Linköping University, Faculty of Health Sciences.
    Heiberg, Einar
    Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Department of Medicine and Care, Center for Medical Image Science and Visualization. Linköping University, Faculty of Health Sciences.
    Karlsson, Matts
    Linköping University, Department of Biomedical Engineering. Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Wigström, Lars
    Linköping University, Department of Medicine and Care, Center for Medical Image Science and Visualization. Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Engvall, Jan
    Linköping University, Department of Medicine and Care, Center for Medical Image Science and Visualization. Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Sigfridsson, Andreas
    Linköping University, Department of Medicine and Care, Center for Medical Image Science and Visualization. Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Ebbers, Tino
    Linköping University, Department of Medicine and Care, Center for Medical Image Science and Visualization. Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Escobar Kvitting, John-Peder
    Linköping University, Department of Medicine and Care, Center for Medical Image Science and Visualization. Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Carlhäll, Carljohan
    Linköping University, Department of Medicine and Care, Center for Medical Image Science and Visualization. Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Wranne, Bengt
    Linköping University, Department of Medicine and Care, Center for Medical Image Science and Visualization. Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Transit of blood flow through thehuman left ventricle mapped by cardiovascular magnetic resonance2007In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 9, no 5, p. 741-747Article in journal (Refereed)
    Abstract [en]

    BACKGROUND:

    The transit of blood through the beating heart is a basic aspect of cardiovascular physiology which remains incompletely studied. Quantification of the components of multidirectional flow in the normal left ventricle (LV) is lacking, making it difficult to put the changes observed with LV dysfunction and cardiac surgery into context.

    METHODS:

    Three dimensional, three directional, time resolved magnetic resonance phase-contrast velocity mapping was performed at 1.5 Tesla in 17 normal subjects, 6 female, aged 44+/-14 years (mean+/-SD). We visualized and measured the relative volumes of LV flow components and the diastolic changes in inflowing kinetic energy (KE). Of total diastolic inflow volume, 44+/-11% followed a direct, albeit curved route to systolic ejection (videos 1 and 2), in contrast to 11% in a subject with mildly dilated cardiomyopathy (DCM), who was included for preliminary comparison (video 3). In normals, 16+/-8% of the KE of inflow was conserved to the end of diastole, compared with 5% in the DCM patient. Blood following the direct route lost or transferred less of its KE during diastole than blood that was retained until the next beat (1.6+/-1.0 millijoules vs 8.2+/-1.9 millijoules, p<0.05); whereas, in the DCM patient, the reduction in KE of retained inflow was 18-fold greater than that of the blood tracing the direct route.

    CONCLUSION:

    Multidimensional flow mapping can measure the paths, compartmentalization and kinetic energy changes of blood flowing into the LV, demonstrating differences of KE loss between compartments, and potentially between the flows in normal and dilated left ventricles.

  • 3.
    Brun, Anders
    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). Centre for Image Analysis, SLU, Uppsala, Sweden.
    Martin-Fernandez, Marcos
    Universidad de Valladolid Laboratorio de Procesado de Imagen (LPI), Dept. Teoría de la Señal y Comunicaciones e Ingeniería Telemática Spain.
    Acar, Burac
    Boğaziçi University 5 Electrical & Electronics Engineering Department Istanbul Turkey.
    Munoz-Moreno, Emma
    Universidad de Valladolid Laboratorio de Procesado de Imagen (LPI), Dept. Teoría de la Señal y Comunicaciones e Ingeniería Telemática Spain.
    Cammoun, Leila
    Signal Processing Institute (ITS), Ecole Polytechnique Fédérale Lausanne (EPFL) Lausanne Switzerland.
    Sigfridsson, Andreas
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV). Center for Technology in Medicine, Dept. Señales y Comunicaciones, University of Las Palmas de Gran Canaria, Spain.
    Sosa-Cabrera, Dario
    Center for Technology in Medicine, Dept. Señales y Comunicaciones, University of Las Palmas de Gran Canaria, Spain.
    Svensson, Björn
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Herberthson, Magnus
    Linköping University, Department of Mathematics, Applied Mathematics. Linköping University, The Institute of Technology.
    Knutsson, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Similar Tensor Arrays - A Framework for Storage of Tensor Array Data2009In: Tensors in Image Processing and Computer Vision / [ed] Santiago Aja-Fern´andez, Rodrigo de Luis Garc´ıa, Dacheng Tao, Xuelong Li, Springer Science+Business Media B.V., 2009, 1, p. 407-428Chapter in book (Refereed)
    Abstract [en]

    This chapter describes a framework for storage of tensor array data, useful to describe regularly sampled tensor fields. The main component of the framework, called Similar Tensor Array Core (STAC), is the result of a collaboration between research groups within the SIMILAR network of excellence. It aims to capture the essence of regularly sampled tensor fields using a minimal set of attributes and can therefore be used as a “greatest common divisor” and interface between tensor array processing algorithms. This is potentially useful in applied fields like medical image analysis, in particular in Diffusion Tensor MRI, where misinterpretation of tensor array data is a common source of errors. By promoting a strictly geometric perspective on tensor arrays, with a close resemblance to the terminology used in differential geometry, (STAC) removes ambiguities and guides the user to define all necessary information. In contrast to existing tensor array file formats, it is minimalistic and based on an intrinsic and geometric interpretation of the array itself, without references to other coordinate systems.

  • 4.
    Dyverfeldt, Petter
    et al.
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Eriksson, Jonatan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Sigfridsson, Andreas
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Escobar Kvitting, John-Peder
    Linköping University, Department of Medical and Health Sciences, Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Carlhäll, Carljohan
    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.
    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.
    Bolger, Ann F.
    University of California San Francisco, San Francisco, California, USA.
    Ebbers, Tino
    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.
    Extending 4D Flow Visualization to the Human Right Ventricle2009In: Proceedings of International Society for Magnetic Resonance in Medicine: 17th Scientific Meeting 2009, International Society for Magnetic Resonance in Medicine , 2009, p. 3860-3860Conference paper (Refereed)
    Abstract [en]

    The right ventricle has an important role in cardiovascular disease. However, because of the complex geometry and the sensitivity to the respiratory cycle, imaging of the right ventricle is challenging. We investigated whether 3D cine phase-contrast MRI can provide data with sufficient accuracy for visualizations of the 4D blood flow in the right ventricle. Whole-heart 4D flow measurements with optimized imaging parameters and post-processing tools were made in healthy volunteers. Pathlines emitted from the right atrium could be traced through the right ventricle to the pulmonary artery without leaving the blood pool and thereby met our criteria for sufficient accuracy.

    Download full text (pdf)
    Extending 4D Flow Visualization to the Human Right Ventricle
  • 5.
    Dyverfeldt, Petter
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Escobar Kvitting, John Peder
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology. Linköping University, Department of Medicine and Health Sciences, Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Boano, G.
    Östergötlands Läns Landsting.
    Carlhäll, Carljohan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Sigfridsson, Andreas
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Hermansson, Ulf
    Linköping University, Department of Medicine and Health Sciences, Thoracic Surgery. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Bolger, A.F.
    University of California, San Fransisco, San Franisco, California, United States.
    Engvall, Jan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Ebbers, Tino
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Turbulence Mapping Extends the Utility of Phase-Contrast MRI in Mitral Valve Regurgitation2009In: Proc. Intl. Soc. Mag. Reson. Med., 2009, p. 3939-Conference paper (Refereed)
    Download full text (pdf)
    Turbulence Mapping Extends the Utility of Phase-Contrast MRI in Mitral Valve Regurgitation
  • 6.
    Dyverfeldt, Petter
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Faculty of Health Sciences. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology. Linköping University, Department of Medical and Health Sciences, Physiology.
    Escobar Kvitting, John-Peder
    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 Thoracic and Vascular Surgery.
    Carlhäll, Carl Johan
    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.
    Boano, Gabriella
    Östergötlands Läns Landsting, Heart Centre, Department of Cardiology.
    Sigfridsson, Andreas
    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.
    Hermansson, Ulf
    Linköping University, Department of Medical and Health Sciences, Thoracic Surgery. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Bolger, Ann F.
    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.
    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.
    Ebbers, Tino
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Faculty of Health Sciences. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology. Linköping University, Department of Medical and Health Sciences, Physiology.
    Hemodynamic aspects of mitral regurgitation assessed by generalized phase-contrast MRI2011In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 33, no 3, p. 582-588Article in journal (Refereed)
    Abstract [en]

    Purpose: Mitral regurgitation creates a high velocity jet into the left atrium (LA), contributing both volume andpressure; we hypothesized that the severity of regurgitation would be reflected in the degree of LA flowdistortion.

    Material and Methods: Three-dimensional cine PC-MRI was applied to determine LA flow patterns andturbulent kinetic energy (TKE) in seven subjects (five patients with posterior mitral leaflet prolapse, two normalsubjects). In addition, the regurgitant volume and the time-velocity profiles in the pulmonary veins weremeasured.

    Results: The LA flow in the mitral regurgitation patients was highly disturbed with elevated values of TKE.Peak TKE occurred consistently at late systole. The total LA TKE was closely related to the regurgitant volume.LA flow patterns were characterized by a pronounced vortex in proximity to the regurgitant jet. In some patients,pronounced discordances were observed between individual pulmonary venous inflows, but these could not berelated to the direction of the flow jet or parameters describing global LA hemodynamics.

    Conclusion: PC-MRI permits investigations of atrial and pulmonary vein flow patterns and TKE in significantmitral regurgitation, reflecting the impact of the highly disturbed blood flow that accompanies this importantvalve disease.

    Download full text (pdf)
    fulltext
  • 7.
    Dyverfeldt, Petter
    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. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology.
    Escobar Kvitting, John-Peder
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Sigfridsson, Andreas
    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.
    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.
    Bolger, Ann F
    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.
    Ebbers, Tino
    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.
    Assessment of fluctuating velocities in disturbed cardiovascular blood flow: in vivo feasibility of generalized phase-contrast MRI2008In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 28, no 3, p. 655-663Article in journal (Refereed)
    Abstract [en]

    Purpose

    To evaluate the feasibility of generalized phase-contrast magnetic resonance imaging (PC-MRI) for the noninvasive assessment of fluctuating velocities in cardiovascular blood flow.

    Materials and Methods

    Multidimensional PC-MRI was used in a generalized manner to map mean flow velocities and intravoxel velocity standard deviation (IVSD) values in one healthy aorta and in three patients with different cardiovascular diseases. The acquired data were used to assess the kinetic energy of both the mean (MKE) and the fluctuating (TKE) velocity field.

    Results

    In all of the subjects, both mean and fluctuating flow data were successfully acquired. The highest TKE values in the patients were found at sites characterized by abnormal flow conditions. No regional increase in TKE was found in the normal aorta.

    Conclusion

    PC-MRI IVSD mapping is able to detect flow abnormalities in a variety of human cardiovascular conditions and shows promise for the quantitative assessment of turbulence. This approach may assist in clarifying the role of disturbed hemodynamics in cardiovascular diseases.

    Download full text (pdf)
    fulltext
  • 8.
    Dyverfeldt, Petter
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Escobar Kvitting, John-Peder
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Surgery in Östergötland.
    Sigfridsson, Andreas
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Engvall, Jan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Bolger, Ann F
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology.
    Ebbers, Tino
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Assessment of Turbulent Flow using Magnetic Resonance Imaging2007In: IX Svenska Kardiovaskulära Vårmötet,2007, 2007Conference paper (Other academic)
    Abstract [en]

      

  • 9.
    Dyverfeldt, Petter
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Escobar Kvitting, John-Peder
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Surgery in Östergötland.
    Sigfridsson, Andreas
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Engvall, Jan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Bolger, Ann F
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Ebbers, Tino
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Improved image acquisition and processing allow accurate 4D flow investigations of the right ventricle2008In: Medicinteknikdagarna,2008, 2008Conference paper (Other academic)
    Abstract [en]

      

  • 10.
    Dyverfeldt, Petter
    et al.
    Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics .
    Escobar Kvitting, John-Peder
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Surgery in Östergötland. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Sigfridsson, Andreas
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Engvall, Jan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Bolger, Ann F
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Ebbers, Tino
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    In-vivo quantification of turbulent velocity fluctuations2007In: 15th Int Soc Magn Reson Med,2007, 2007Conference paper (Other academic)
  • 11.
    Dyverfeldt, Petter
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Escobar Kvitting, John-Peder
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Surgery in Östergötland.
    Sigfridsson, Andreas
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Engvall, Jan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Bolger, Ann F
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Ebbers, Tino
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Non-invsive assessment of turbulent flow using magnetic resonance imaging2007In: Medicinteknikdagarna,2007, 2007Conference paper (Other academic)
  • 12.
    Dyverfeldt, Petter
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Escobar Kvitting, John-Peder
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Thoracic Surgery. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Surgery in Östergötland.
    Sigfridsson, Andreas
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Engvall, Jan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Ebbers, Tino
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Mätning och visualisering av blodflödet i höger kammare med tidsupplöst tredimensionell MR2007In: Riksstämman,2007, 2007Conference paper (Other academic)
    Abstract [sv]

       

  • 13.
    Dyverfeldt, Petter
    et al.
    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.
    Escobar Kvitting, John-Peder
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Sigfridsson, Andreas
    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.
    Franzén, Stefan
    Linköping University, Department of Medicine and Health Sciences, Thoracic Surgery. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Bolger, Ann F.
    University of California San Fransisco, San Fransisco, California, United States.
    Ebbers, Tino
    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.
    In-Vitro Turbulence Mapping in Prosthetic Heart Valves using Generalized Phase-Contrast MRI2009In: Proc. Intl. Soc. Mag. Reson. Med., 2009, p. 3941-Conference paper (Refereed)
    Download full text (pdf)
    In-Vitro Turbulence Mapping in Prosthetic Heart Valves using Generalized Phase-Contrast MRI
  • 14.
    Dyverfeldt, Petter
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Gårdhagen, Roland
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics . Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology.
    Sigfridsson, Andreas
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Karlsson, Matts
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics . Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology.
    Ebbers, Tinno
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    MRI Turbulence Quantification2009In: Proc. Intl. Soc. Mag. Reson. Med., 2009, p. 1858-Conference paper (Refereed)
    Download full text (pdf)
    MRI Turbulence Quantification
  • 15.
    Dyverfeldt, Petter
    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. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology.
    Gårdhagen, Roland
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology.
    Sigfridsson, Andreas
    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.
    Karlsson, Matts
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology.
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology.
    On MRI turbulence quantification2009In: Magnetic Resonance Imaging, ISSN 0730-725X, E-ISSN 1873-5894, Vol. 27, no 7, p. 913-922Article in journal (Refereed)
    Abstract [en]

    Turbulent flow, characterized by velocity fluctuations, accompanies many forms of cardiovascular disease and may contribute to their progression and hemodynamic consequences. Several studies have investigated the effects of turbulence on the magnetic resonance imaging (MRI) signal. Quantitative MRI turbulence measurements have recently been shown to have great potential for application both in human cardiovascular flow and in engineering flow. In this article, potential pitfalls and sources of error in MRI turbulence measurements are theoretically and numerically investigated. Data acquisition strategies suitable for turbulence quantification are outlined. The results show that the sensitivity of MRI turbulence measurements to intravoxel mean velocity variations is negligible, but that noise may degrade the estimates if the turbulence encoding parameter is set improperly. Different approaches for utilizing a given amount of scan time were shown to influence the dynamic range and the uncertainty in the turbulence estimates due to noise. The findings reported in this work may be valuable for both in vitro and in vivo studies employing MRI methods for turbulence quantification.

    Download full text (pdf)
    FULLTEXT01
  • 16.
    Dyverfeldt, Petter
    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. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology.
    Sigfridsson, Andreas
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Escobar Kvitting, John-Peder
    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 Thoracic and Vascular Surgery.
    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. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology.
    Quantification of intravoxel velocity standard deviation and turbulence intensity by generalizing phase-contrast MRI2006In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 56, no 4, p. 850-858Article in journal (Refereed)
    Abstract [en]

    Turbulent flow, characterized by velocity fluctuations, is a contributing factor to the pathogenesis of several cardiovascular diseases. A clinical noninvasive tool for assessing turbulence is lacking, however. It is well known that the occurrence of multiple spin velocities within a voxel during the influence of a magnetic gradient moment causes signal loss in phase-contrast magnetic resonance imaging (PC-MRI). In this paper a mathematical derivation of an expression for computing the standard deviation (SD) of the blood flow velocity distribution within a voxel is presented. The SD is obtained from the magnitude of PC-MRI signals acquired with different first gradient moments. By exploiting the relation between the SD and turbulence intensity (TI), this method allows for quantitative studies of turbulence. For validation, the TI in an in vitro flow phantom was quantified, and the results compared favorably with previously published laser Doppler anemometry (LDA) results. This method has the potential to become an important tool for the noninvasive assessment of turbulence in the arterial tree.

    Download full text (pdf)
    fulltext
  • 17.
    Dyverfeldt, Petter
    et al.
    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.
    Sigfridsson, Andreas
    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.
    Escobar Kvitting, John-Peder
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Ebbers, Tino
    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.
    Quantification of Turbulance Intensity by Generalizing Phase-Contrast MRI2006Conference paper (Refereed)
    Download full text (pdf)
    Quantification of Turbulance Intensity by Generalizing Phase-Contrast MRI
  • 18.
    Dyverfeldt, Petter
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Sigfridsson, Andreas
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Escobar Kvitting, John-Peder
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Surgery in Östergötland.
    Ebbers, Tino
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Quantification of Turbulence Intensity by Generalizing Phase-Contrast MRI2006In: Proc. Intl. Soc. Mag. Reson. Med. 14,2006, 2006, p. 870-870Conference paper (Refereed)
    Abstract [en]

      

  • 19.
    Dyverfeldt, Petter
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Sigfridsson, Andreas
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Knutsson, Hans
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, The Institute of Technology. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    A Novel MRI Framework for the Quantification of Any Moment of Arbitrary Velocity Distributions.2010In: Proc. Intl. Soc. Mag. Reson. Med. 18 (2010), ISMRM , 2010, p. 1359-1359Conference paper (Other academic)
    Abstract [en]

    Under the assumption that the intravoxel velocity distribution is symmetric about its mean, the well-known MRI phase-difference method permits an estimation of the mean velocity of a voxel. The mean velocity corresponds to the first moment of the velocity distribution. Here, a novel framework for the quantification of any moment of arbitrary spin velocity distributions is presented. Simulations on realistic velocity distributions demonstrate its application. The presented moment framework may assist in improving the understanding of existing MRI methods for the quantification of flow and motion and serve as a basis for the development of new methods.

  • 20.
    Dyverfeldt, Petter
    et al.
    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.
    Sigfridsson, Andreas
    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.
    Knutsson, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Ebbers, Tino
    Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology. Linköping University, Department of Medical and Health Sciences, Physiology. Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics.
    A novel MRI framework for the quantification of any moment of arbitrary velocity distributions2011In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 65, no 3, p. 725-731Article in journal (Refereed)
    Abstract [en]

    MRI can measure several important hemodynamic parameters but might not yet have reached its full potential. The most common MRI method for the assessment of flow is phase-contrast MRI velocity mapping that estimates the mean velocity of a voxel. This estimation is precise only when the intravoxel velocity distribution is symmetric. The mean velocity corresponds to the first raw moment of the intravoxel velocity distribution. Here, a generalized MRI framework for the quantification of any moment of arbitrary velocity distributions is described. This framework is based on the fact that moments in the function domain (velocity space) correspond to differentials in the Fourier transform domain (kv-space). For proof-of-concept, moments of realistic velocity distributions were estimated using finite difference approximations of the derivatives of the MRI signal. In addition, the framework was applied to investigate the symmetry assumption underlying phase-contrast MRI velocity mapping; we found that this assumption can substantially affect phase-contrast MRI velocity estimates and that its significance can be reduced by increasing the velocity encoding range.

    Download full text (pdf)
    fulltext
  • 21.
    Dyverfeldt, Petter
    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 Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Sigfridsson, Andreas
    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 Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Knutsson, Hans
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. 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, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    MR flow imaging beyond the mean velocity: Estimation of the skew  and kurtosis of intravoxel velocity distributions2011In: ISMRM 2011, International Society for Magnetic Resonance in Medicine ( ISMRM ) , 2011Conference paper (Other academic)
  • 22.
    Ebbers, Tino
    et al.
    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.
    Dyverfeldt, Petter
    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.
    Sigfridsson, Andreas
    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.
    Escobar Kvitting, John-Peder
    Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences.
    Quantification of Mean and Fluctuating Flow2006Conference paper (Refereed)
  • 23.
    Ebbers, Tino
    et al.
    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.
    Haraldsson, Henrik
    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.
    Dyverfeldt, Petter
    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.
    Sigfridsson, Andreas
    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.
    Warntjes, Marcel Jan Bertus
    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.
    Wigström, Lars
    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.
    Higher order weighted least-squares phase offset correction for improved accuracy in phase-contrast MRI2008Conference paper (Refereed)
    Abstract [en]

    Phase-contrast magnetic resonance imaging has the ability to accurately measure blood flow and myocardial velocities in the human body. Unwanted spatially varying phase offsets are, however, always present and may deteriorate the measurements significantly. Some of these phase offsets can be estimated based on the pulse sequence (1), but effects caused by eddy currents are more difficult to predict. A linear fit of the phase values is often estimated from either a number of manually defined areas containing stationary tissue or by semi-automatic detection of stationary tissue using the

    Download full text (pdf)
    Higer order weighted least-squares phase offset correction for improved accuracy in phase-contrast MRI
  • 24.
    Escobar Kvitting, John-Peder
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Surgery in Östergötland.
    Dyverfeldt, Petter
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Boano, G
    Sigfridsson, Andreas
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Engvall, Jan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Bolger, Ann F
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Ebbers, Tino
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Multidimensional Turbulence Mapping in Mitral Insufficiency2008In: Soc Cardiovascular Magn Reson. 11th Scientific Sessions,2008, 2008Conference paper (Other academic)
  • 25.
    Escobar Kvitting, John-Peder
    et al.
    Linköping University, Department of Medicine and Health Sciences, Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Dyverfeldt, Petter
    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.
    Carlhäll, Carljohan
    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.
    Sigfridsson, Andreas
    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.
    F Bolger, Ann
    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.
    Ebbers, Tino
    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.
    Engvall, Jan
    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.
    MR allows a unique possibility to see how the blood flow affects the cardiovascular system [MR ger unik möjlighet se hur blodflödet inverkar på hjärtkärlsystemet.]2009In: Läkartidningen, ISSN 0023-7205, E-ISSN 1652-7518, Vol. 106, no 30-31, p. 1901-1904Article, review/survey (Refereed)
    Abstract [en]

    [No abstract available]

  • 26.
    Escobar Kvitting, John-Peder
    et al.
    Linköping University, Department of Medicine and Health Sciences, Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Dyverfeldt, Petter
    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.
    Sigfridsson, Andreas
    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.
    Franzen, Stefan
    Linköping University, Department of Medicine and Health Sciences, Thoracic Surgery. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Wigström, Lars
    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.
    Bolger, Ann F
    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.
    Ebbers, Tino
    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.
    In Vitro Assessment of Flow Patterns and Turbulence Intensity in Prosthetic Heart Valves Using Generalized Phase-Contrast MRI2010In: JOURNAL OF MAGNETIC RESONANCE IMAGING, ISSN 1053-1807, Vol. 31, no 5, p. 1075-1080Article in journal (Refereed)
    Abstract [en]

    Purpose: To assess in vitro the three-dimensional mean velocity field and the extent and degree of turbulence intensity (TI) in different prosthetic heart valves using a generalization of phase-contrast MRI (PC-MRI). Materials and Methods: Four 27-mm aortic valves (Bjork-Shiley Monostrut tilting-disc, St. Jude Medical Standard bileaflet, Medtronic Mosaic stented and Freestyle stentless porcine valve) were tested under steady inflow conditions in a Plexiglas phantom. Three-dimensional PC-MRI data were acquired to measure the mean velocity field and the turbulent kinetic energy (TKE), a direction-independent measure of TI. Results: Velocity and TI estimates could be obtained up and downstream of the valves, except where metallic structure in the valves caused signal void. Distinct differences in the location, extent, and peak values of velocity and TI were observed between the valves tested. The maximum values of TKE varied between the different valves: tilting disc, 100 J/m(3); bileaflet, 115 J/m(3); stented, 200 J/m(3); stentless, 145 J/m(3). Conclusion: The TI downstream from a prosthetic heart valve is dependent on the specific valve design. Generalized PC-MRI can be used to quantify velocity and TI downstream from prosthetic heart valves, which may allow assessment of these aspects of prosthetic valvular function in postoperative patients.

  • 27.
    Escobar Kvitting, John-Peder
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Dyverfeldt, Petter
    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. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics . Linköping University, The Institute of Technology.
    Sigfridsson, Andreas
    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.
    Franzén, Stefan
    Östergötlands Läns Landsting, Heart Centre, Department of Cardiology.
    Wigström, Lars
    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.
    Bolger, Ann F.
    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.
    Ebbers, Tino
    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. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics . Linköping University, The Institute of Technology.
    In Vitro Assessment of Flow Patterns and Turbulence Intensity in Prosthetic Heart Valves Using Generalized Phase-Contrast Magnetic Resonance ImagingManuscript (preprint) (Other academic)
    Abstract [en]

    Purpose: To assess in vitro the three-dimensional mean velocity field and the extent and degree of turbulenceintensity in different prosthetic heart valves using a generalization of phase-contrast magnetic resonance imaging(PC-MRI).

    Material and Methods: Four 27 mm aortic valves (Björk-Shiley Monostrut tilting-disc, St. Jude MedicalStandard bileaflet, Medtronic Mosaic stented and Freestyle stentless porcine valve) were tested under steadyinflow conditions in a Plexiglas phantom. Three-dimensional PC-MRI data were acquired to measure the meanvelocity field and the turbulent kinetic energy (TKE), a direction-independent measure of turbulence intensity.

    Results: Velocity and turbulence intensity estimates could be obtained up and downstream of the valves, exceptwhere metallic structure in the valves caused signal void. Distinct differences in the location, extent and peakvalues of velocity and turbulence intensity were observed between the valves tested. The maximum values ofTKE varied between the different valves: tilting disc, 100 J/m3; bileaflet, 115 J/m3; stented, 200 J/m3; stentless,145 J/m3.

    Conclusion: The turbulence intensity downstream from a prosthetic heart valve is dependent on the specificvalve design. Generalized PC-MRI can be used to quantify velocity and turbulence intensity downstream fromprosthetic heart valves, which may allow assessment of these aspects of prosthetic valvular function inpostoperative patients.

  • 28.
    Escobar Kvitting, John-Peder
    et al.
    Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences. 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.
    Sigfridsson, Andreas
    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.
    Wigström, Lars
    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.
    Bolger, A.F.
    University of California, San Fransisco, San Fransisco, USA.
    Karlsson, Matts
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Biomedical Engineering, Biomedical Modelling and Simulation. Linköping University, The Institute of Technology.
    Virtual makers for noninvasive assessment of myocardial dynamics2005Conference paper (Refereed)
    Abstract [en]

       

     

     

     

     

     

     

     

     

     

     

     

     

      

     

    Download full text (pdf)
    Virtual makers for noninvasive assessment of nyocardial dynamics
  • 29.
    Haraldsson, Henrik
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Sigfridsson, A.
    Mie University, Tsu, Mie, Japan.
    Sakuma, H.
    Mie University, Tsu, Mie, Japan.
    Ebbers, Tino
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Comparison of DENSE Reference Strategies2009In: Proceedings of the International Society for Magnetic Resonance in Medicine, 2009, p. 819-819Conference paper (Refereed)
    Download full text (pdf)
    Comparison of DENSE Reference Strategies
  • 30.
    Haraldsson, Henrik
    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.
    Sigfridsson, Andreas
    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.
    Sakuma, Hajime
    Engvall, Jan
    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.
    Ebbers, Tino
    Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, Department of Medical and Health Sciences, Physiology. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Influence of the FID and off-resonance effects in dense MRI2011In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 65, no 4, p. 1104-1112Article in journal (Refereed)
    Abstract [en]

    Accurate functional measurement in cardiovascular diseases is important as inaccuracy may compromise diagnostic decisions. Cardiac function can be assessed using displacement encoding with stimulated echoes, resulting in three signal components. The free induction decay (FID), arising from spins undergoing T1-relaxation, is not displacement encoded and impairs the displacement acquired. Techniques for suppressing the FID exist; however, a residual will remain. The effect of the residual is difficult to distinguish and investigate in vitro and in vivo. In this work, the influence of the FID as well as of off-resonance effects is evaluated by altering the phase of the FID in relation to the stimulated echo. The results show that the FID and off-resonance effects can impair the accuracy of the displacement measurement acquired. The influence of the FID can be avoided by using an encoded reference. We therefore recommend the assessment of this influence of the FID for each displacement encoding with stimulated echoes protocol.

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    fulltext
  • 31.
    Kihlberg, Johan
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Gupta, Vikas
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and 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 Cardiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Sigfridsson, Andreas
    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. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Sarvari, Sebastian
    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).
    Identification of the best CMR technique for quantitative assessment of myocardial salvage using a systematic comparison.2017In: Insights into Imaging, E-ISSN 1869-4101, Vol. 8, no Supplement 1Article in journal (Refereed)
  • 32.
    Kindberg, Katarina
    et al.
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics . Linköping University, The Institute of Technology.
    Haraldsson, Henrik
    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.
    Sigfridsson, Andreas
    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.
    Engvall, Jan
    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.
    Ingels, Neil B.
    dDepartment of Cardiothoracic Surgery, School of Medicine, Stanford University, Stanford, CA 94305, USA.
    Ebbers, Tino
    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.
    Karlsson, Matts
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics . Linköping University, The Institute of Technology.
    Myocardial strains from 3D DENSE magnetic resonance imagingManuscript (preprint) (Other academic)
    Abstract [en]

    The ability to measure and quantify myocardial motion and deformation provides a useful tool to assist in the diagnosis, prognosis and management of heart disease. The recent development of magnetic resonance imaging methods, such as harmonic phase and displacement encoding with stimulated echoes (DENSE), make detailed non-invasive 3D transmural kinematic analyses of human myocardium possible in the clinic and for research purposes. As data acquisition technologies improve, quantification methods for cardiac kinematics need to be adapted and validated on the new types of data. In the present paper, a previously presented polynomial method for cardiac strain quantification is extended to quantify 3D strains from DENSE magnetic resonance imaging data. The method yields accurate results when validated against an analytical standard, and is applied to in vivo data from a healthy  human heart. The polynomial field is capable of resolving the measured material positions from the in vivo data, and the obtained in vivo strains agree

  • 33.
    Kindberg, Katarina
    et al.
    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.
    Haraldsson, Henrik
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Sigfridsson, Andreas
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Engvall, Jan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Ingels, Neil B.
    Stanford University, CA, USA .
    Ebbers, Tino
    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. Linköping University, Department of Science and Technology, Media and Information Technology.
    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.
    Myocardial strains from 3D displacement encoded magnetic resonance imaging2012In: BMC Medical Imaging, ISSN 1471-2342, E-ISSN 1471-2342, Vol. 12, no 9Article in journal (Refereed)
    Abstract [en]

    Background

    The ability to measure and quantify myocardial motion and deformation provides a useful tool to assist in the diagnosis, prognosis and management of heart disease. The recent development of magnetic resonance imaging methods, such as harmonic phase analysis of tagging and displacement encoding with stimulated echoes (DENSE), make detailed non-invasive 3D kinematic analyses of human myocardium possible in the clinic and for research purposes. A robust analysis method is required, however.

    Methods

    We propose to estimate strain using a polynomial function which produces local models of the displacement field obtained with DENSE. Given a specific polynomial order, the model is obtained as the least squares fit of the acquired displacement field. These local models are subsequently used to produce estimates of the full strain tensor.

    Results

    The proposed method is evaluated on a numerical phantom as well as in vivo on a healthy human heart. The evaluation showed that the proposed method produced accurate results and showed low sensitivity to noise in the numerical phantom. The method was also demonstrated in vivo by assessment of the full strain tensor and to resolve transmural strain variations.

    Conclusions

    Strain estimation within a 3D myocardial volume based on polynomial functions yields accurate and robust results when validated on an analytical model. The polynomial field is capable of resolving the measured material positions from the in vivo data, and the obtained in vivo strains values agree with previously reported myocardial strains in normal human hearts.

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  • 34.
    Kindberg, Katarina
    et al.
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Haraldsson, Henrik
    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. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Sigfridsson, Andreas
    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. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Sakuma, Hajime
    Department of Radiology, Mie University, 2-174 Edobashi, Tsu, Mie 514-8507, Japan.
    Ebbers, Tino
    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. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Karlsson, Matts
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Temporal 3D Lagrangian strain from 2D slice followed cine DENSE MRI2012In: Clinical Physiology and Functional Imaging, ISSN 1475-0961, E-ISSN 1475-097X, Vol. 32, no 2, p. 139-144Article in journal (Refereed)
    Abstract [en]

    A quantitative analysis of myocardial mechanics is fundamental to the understanding of cardiac function, diagnosis of heart disease and assessment of therapeutic intervention. In the clinical situation, where limited scan time often is important, a detailed analysis of the myocardium in a specific region might be more applicable than a full 3D measurement of the entire left ventricle. This paper presents a method to obtain temporal evolutions of transmural 3D Lagrangian strains from two intersecting 2D planes of slice followed cine displacement encoding with stimulated echoes (DENSE) data using a bilinear-cubic polynomial element to resolve strain from the displaced myocardial positions. The method demonstrates accurate results when validated in an analytical model, and has been applied to in vivo data acquired on a 3 T magnetic resonance (MR) system from a healthy volunteer to quantify systolic strains at the anterior-basal region of left ventricular myocardium. The in vivo results agree within experimental accuracy with values reported in the literature.

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    fulltext
  • 35.
    Knutsson, Hans
    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).
    Andersson, Mats
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Wigström, Lars
    Linköping University, Department of Medicine and Care, Clinical Physiology. 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).
    Sigfridsson, Andreas
    Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Motion artifact reduction in MRI through generalized DFT2004In: Biomedical Imaging: Nano to Macro, 2004. IEEE International Symposium on, IEEE , 2004, p. 896-899 vol.1Conference paper (Refereed)
    Abstract [en]

    This paper presents a method that dramatically reduces artifacts caused by respiratory (and similar types of) patient motion in magnetic resonance imaging (MRI). The basis for the method is the observation that affine deformations of an object will correspond to a different but unique affine coordinate transform (plus phase shift) of the Fourier representation of the object. The resulting sample points will be irregularly distributed prohibiting the use of standard IFFT to reconstruct the object. The object can however be reconstructed through the use of a weighted regularized pseudo inverse. A standard pseudo inverse is, however, not possible due to excessive computational demands. For this reason a novel fast sequential pseudo inverse algorithm is also presented. Significantly improved results are obtained on both synthetic and clinical data.

  • 36.
    Kvitting, John-Peder Escobar
    et al.
    Linköping University, Department of Medicine and Health Sciences, Thoracic Surgery. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery. Linköping University, Faculty of Health Sciences.
    Dyverfeldt, Petter
    Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Carlhäll, Carljohan
    Linköping University, Department of Medicine and Health Sciences, Thoracic Surgery. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Sigfridsson, Andreas
    Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Bolger, Ann F
    Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Ebbers, Tino
    Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Engvall, Jan
    Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Magnetresonanstomografi ger unika möjligheter att bedöma blodflödet och dess inverkan på hjärt och kärlsystemet.2009In: Läkartidningen, ISSN 0023-7205, E-ISSN 1652-7518, Vol. 106, p. 1901-1904Article in journal (Other academic)
  • 37.
    Kvitting, J.P.
    et al.
    Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Sigfridsson, A.
    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.
    Wigström, L.
    Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences.
    Bolger, A.F.
    Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Karlsson, Matts
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics . Linköping University, The Institute of Technology.
    Analysis of human myocardial dynamics using virtual markers based on magnetic resonance imaging2010In: Clinical Physiology and Functional Imaging, ISSN 1475-0961, E-ISSN 1475-097X, Vol. 30, no 1, p. 23-29Article in journal (Refereed)
    Abstract [en]

    Background: Myocardial dynamics are three-dimensional (3D) and time-varying. Cineradiography of surgically implanted makers in animals or patients is accurate for assessing these events, but this invasive method potentially alters myocardial motion. The aim of the study was to quantify myocardial motion using magnetic resonance imaging (MRI) and hence to provide a non-invasive approach to characterize 3D myocardial dynamics.

    Methods: Myocardial motion was quantified in ten normal volunteers by tracking the Lagrangian motion of individual points (i.e. virtual markers), based on time-resolved 3D phase-contrast MRI data and Fourier tracking. Nine points in the myocardium were tracked over the entire cardiac cycle, allowing a wire frame model to be generated and systolic and diastolic events identified.

    Results: Radius of curvature of the left ventricular (LV) wall was calculated from the virtual markers; the ratio between the anterior–posterior (AP) and septal–lateral (SL) walls in the LV shows an oval shape of the apical short axis plane at end systole (ES) and more circular at end diastole (ED). The AP/SL ratio for the basal plane shows an oval shape at ES and ED. We found that the rotation of the basal plane in ES was less compared to the apical plane [−2·0 ± 2·2 versus 4·1 ± 2·6 degrees (P<0·005)]. The apical plane rotated counter clock wise as viewed from the apex.

    Conclusion: This new non-invasive tool, despite current limitations in temporal and spatial resolution, may provide a comprehensive set of virtual myocardial markers throughout the entire LV without the confounding effects introduced by surgical implantation.

  • 38.
    Petersson, Sven
    et al.
    Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dyverfeldt, Petter
    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. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Sigfridsson, Andreas
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Lantz, Jonas
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology.
    Carlhäll, Carl-Johan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Quantification of Stenotic Flow Using Spiral 3D Phase-Contrast MRI2013Manuscript (preprint) (Other academic)
    Abstract [en]

    Purpose: To evaluate the feasibility of spiral 3D phase contrast MRI for the assessment of velocity, volume flow rate, peak velocity and turbulent kinetic energy in stenotic flow.

    Materials and Methods: A-stack-of-spirals 3D phase contrast MRI sequence was evaluated in-vitro against a conventional Cartesian sequence. Measurements were made in a flow phantom with a 75% stenosis. Both spiral and Cartesian imaging were performed using different scan orientations and flow rates. Volume flow rate, peak velocity and turbulent kinetic energy (TKE) were computed for both methods. For further validation, the estimated TKE was compared to computational fluid dynamics (CFD) data.

    Results: The volume flow rate, peak velocity and TKE obtained with spiral 4D flow MRI agreed well with Cartesian data and CFD data. As expected, the short echo time of the spiral sequence resulted in less prominent displacement artifacts compared to the Cartesian sequence. However, both spiral and Cartesian flow rate estimates were sensitive to displacement when the flow was oblique to the encoding directions.

    Conclusion: Spiral 3D phase contrast MRI appears favorable for the assessment of stenotic flow. The spiral sequence was more than three times faster and less sensitive to displacement artifacts when compared to a conventional Cartesian sequence.

  • 39.
    Petersson, Sven
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine.
    Sigfridsson, Andreas
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Center for Medical Image Science and Visualization (CMIV). Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Faculty of Medicine and Health Sciences.
    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.
    Carlhäll, Carl-Johan
    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.
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Retrospectively Gated Intra-cardiac 4D Flow MRI using Spiral Trajectories2016In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 75, no 1, p. 196-206Article in journal (Refereed)
    Abstract [en]

    Background: Four-dimensional (4D) flow MRI is a powerful tool for the quantification of blood flow and enables calculation of a range of unique hemodynamic parameters. However, the application of cardiac 4D flow MRI is limited by long scan times (20-40 minutes). The high efficiency of spiral readouts can be used to reduce scan times without sacrificing SNR. The aim of this work was to develop and validate a retrospectively gated 4D flow MRI sequence using spiral readouts for the measurement of intra-cardiac velocities.

    Methods: A retrospectively ECG gated 4D flow sequence using stacks of spiral readouts was implemented on a clinical 1.5 T MRI scanner. The spiral 4D flow MRI sequence was validated in-vivo by comparisons with a two-dimensional (2D) through-plane velocity measurement and a conventional Cartesian 4D flow acquisition (SENSE factor 2) in 7 healthy volunteers (age 27 ± 3 years, four men) and 2 patients (age 19 and 52, women, only spiral 4D flow and 2D). Net volume flow was estimated from all three acquisition approaches and compared using one-way ANOVA. A quantitative pathline based validation was performed on the Cartesian and the spiral 4D flow MRI acquisitions by comparing the left ventricular inflow and outflow (two-tailed paired t-tests).

    Results: The scan time of the spiral 4D flow sequence was 44±6% of the Cartesian counterpart. Compared to time-resolved 2D flow in the aorta, the spiral and Cartesian 4D flow acquisitions provided similarly good data, as there was no significant difference between the net volume flow for all acquisitions (Spiral: 89±14 ml, Cartesian: 93±11 ml, 2D: 93±18 ml, p=0.878). There was no significant difference between pathline-based calculations of inflow and outflow with either Cartesian (In: 88±15, Out: 85±16, p = 0.168) or spiral (In: 93±17 ml, Out: 84±18, p = 0.055) 4D flow acquisitions.

    Conclusions: Retrospectively gated spiral cardiac 4D flow MRI permits more than two-fold reduction in scan time compared to conventional Cartesian 4D flow MRI without notable loss in data quality. The time-savings offered by spiral trajectories could provide a step towards the expanded clinical use of 4D flow MRI.

  • 40. Order onlineBuy this publication >>
    Sigfridsson, Andreas
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Multidimensional MRI of Cardiac Motion: Acquisition, Reconstruction and Visualization2006Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Methods for measuring deformation and motion of the human heart in-vivo are crucial in the assessment of cardiac function. Applications ranging from basic physiological research, through early detection of disease to follow-up studies, all benefit from improved methods of measuring the dynamics of the heart. This thesis presents new methods for acquisition, reconstruction and visualization of cardiac motion and deformation, based on magnetic resonance imaging.

    Local heart wall deformation can be quantified in a strain rate tensor field. This tensor field describes the local deformation excluding rigid body translation and rotation. The drawback of studying this tensor-valued quantity, as opposed to a velocity vector field, is the high dimensionality of the tensor. The problem of visualizing the tensor field is approached by combining a local visualization that displays all degrees of freedom for a single tensor with an overview visualization using a scalar field representation of the complete tensor field. The scalar field is obtained by iterated adaptive filtering of a noise field.

    Several methods for synchronizing the magnetic resonance imaging acquisition to the heart beat have previously been used to resolve individual heart phases from multiple cardiac cycles. In the present work, one of these techniques is extended to resolve two temporal dimensions simultaneously, the cardiac cycle and the respiratory cycle. This is combined with volumetric imaging to produce a five-dimensional data set. Furthermore, the acquisition order is optimized in order to reduce eddy current artifacts.

    The five-dimensional acquisition either requires very long scan times or can only provide low spatiotemporal resolution. A method that exploits the variation in temporal bandwidth over the imaging volume, k-t BLAST, is described and extended to two simultaneous temporal dimensions. The new method, k-t2 BLAST, allows simultaneous reduction of scan time and improvement of spatial resolution.

    List of papers
    1. Tensor Field Visualisation using Adaptive Filtering of Noise Fields combined with Glyph Rendering
    Open this publication in new window or tab >>Tensor Field Visualisation using Adaptive Filtering of Noise Fields combined with Glyph Rendering
    2002 (English)In: IEEE Visualization 2002 Conference, IEEE , 2002, p. 371-378Conference paper, Published paper (Refereed)
    Abstract [en]

    While many methods exist for visualising scalar and vector data, visualisation of tensor data is still troublesome. We present a method for visualising second order tensors in three dimensions using a hybrid between direct volume rendering and glyph rendering.

    An overview scalar field is created by using three-dimensional adaptive filtering of a scalar field containing noise. The filtering process is controlled by the tensor field to be visualised, creating patterns that characterise the tensor field. By combining direct volume rendering of the scalar field with standard glyph rendering methods for detailed tensor visualisation, a hybrid solution is created.

    A combined volume and glyph renderer was implemented and tested with both synthetic tensors and strain-rate tensors from the human heart muscle, calculated from phase contrast magnetic resonance image data. A comprehensible result could be obtained, giving both an overview of the tensor field as well as detailed information on individual tensors.

    Place, publisher, year, edition, pages
    IEEE, 2002
    Keywords
    Tensor, Visualisation, Volume rendering, Glyph rendering, Hybrid rendering, Strain-rate
    National Category
    Medical and Health Sciences Medical Laboratory and Measurements Technologies
    Identifiers
    urn:nbn:se:liu:diva-14011 (URN)
    Available from: 2006-10-04 Created: 2006-10-04 Last updated: 2013-09-03Bibliographically approved
    2. Five-dimensional MRI Incorporating Simultaneous Resolution of Cardiac and Respiratory Phases for Volumetric Imaging
    Open this publication in new window or tab >>Five-dimensional MRI Incorporating Simultaneous Resolution of Cardiac and Respiratory Phases for Volumetric Imaging
    2006 (English)In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 25, no 1, p. 113-121Article in journal (Refereed) Published
    Abstract [en]

    Purpose

    To develop a new volumetric imaging method resolved over both the cardiac and respiratory cycles, to enable future physiological and pathophysiological studies of respiratory-related cardiac motion.

    Materials and Methods

    An acquisition scheme is proposed whereby the k-space acquisition order is controlled in real-time by the current cardiac and respiratory phases. To reduce eddy-current effects induced by sudden jumps in k-space, the acquisition order is further optimized by the use of a Hilbert curve trajectory in the ky-kz plane. A complete three-dimensional (3D) k-space is acquired for all combinations of cardiac and respiratory phases, yielding a five-dimensional (5D) data set after retrospective reconstruction.

    Results

    Left (LV) and right ventricular (RV) wall excursion was measured in a healthy volunteer. Diastolic LV diameter was shown to increase during expiration and decrease during inspiration, as expected from previous echocardiography studies. The LV volume was estimated for all cardiac and respiratory phases with the use of a fully 3D segmentation tool. The results confirmed that the diastolic LV volume increased during expiration and decreased during inspiration.

    Conclusion

    With its ability to measure motion anywhere in the heart, the described technique provides a promising approach for in-depth description of interventricular coupling, including 3D ventricular volumes, during both the cardiac and respiratory cycles.

    Keywords
    respiration, septal motion, interventricular coupling, volumetric MRI, cine imaging
    National Category
    Medical and Health Sciences Medical Laboratory and Measurements Technologies
    Identifiers
    urn:nbn:se:liu:diva-14012 (URN)10.1002/jmri.20820 (DOI)000243250800014 ()
    Available from: 2006-10-04 Created: 2006-10-04 Last updated: 2017-12-13Bibliographically approved
    3. k-t2 BLAST: Exploiting spatiotemporal structure in simultaneously cardiac and respiratory time-resolved volumetric imaging
    Open this publication in new window or tab >>k-t2 BLAST: Exploiting spatiotemporal structure in simultaneously cardiac and respiratory time-resolved volumetric imaging
    2007 (English)In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 58, no 5, p. 922-930Article in journal (Refereed) Published
    Abstract [en]

    Multidimensional imaging resolving both the cardiac and respiratory cycles simultaneously has the potential to describe important physiological interdependences between the heart and pulmonary processes. A fully five-dimensional acquisition with three spatial and two temporal dimensions is hampered, however, by the long acquisition time and low spatial resolution. A technique is proposed to reduce the scan time substantially by extending the k-t BLAST framework to two temporal dimensions. By sampling the k-t space sparsely in a lattice grid, the signal in the transform domain, x-f space, can be densely packed, exploiting the fact that large regions in the field of view have low temporal bandwidth. A volumetric online prospective triggering approach with full cardiac and respiratory cycle coverage was implemented. Retrospective temporal interpolation was used to refine the timing estimates for the center of k-space, which is sampled for all cardiac and respiratory time frames. This resulted in reduced reconstruction error compared with conventional k-t BLAST reconstruction. The k-t2 BLAST technique was evaluated by decimating a fully sampled five-dimensional data set, and feasibility was further demonstrated by performing sparsely sampled acquisitions. Compared to the fully sampled data, a fourfold improvement in spatial resolution was accomplished in approximately half the scan time.

    Keywords
    Cine imaging, k-t BLAST, Respiration, Volumetric MRI
    National Category
    Engineering and Technology Medical Laboratory and Measurements Technologies
    Identifiers
    urn:nbn:se:liu:diva-47833 (URN)10.1002/mrm.21295 (DOI)000250560000009 ()
    Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2017-12-13Bibliographically approved
    Download full text (pdf)
    FULLTEXT01
  • 41. Order onlineBuy this publication >>
    Sigfridsson, Andreas
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, The Institute of Technology.
    Multidimensional MRI  of Myocardial Dynamics: Acquisition, Reconstruction and Visualization2009Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Methods for measuring deformation and motion of the human heart in-vivo are crucial in the assessment of cardiac function. Applications ranging from basic physiological research, through early detection of disease to follow-up studies, all rely on the quality of the measurements of heart dynamics. This thesis presents new improved magnetic resonance imaging methods for acquisition, image reconstruction and visualization of cardiac motion and deformation.As the heart moves and changes shape during the acquisition, synchronization to the heart dynamics is necessary. Here, a method to resolve not only the cardiac cycle but also the respiratory cycle is presented. Combined with volumetric imaging, this produces a five-dimensional data set with two cyclic temporal dimensions. This type of data reveals unique physiological information, such as interventricular coupling in the heart in different phases of the respiratory cycle.The acquisition can also be sensitized to motion, measuring not only the magnitude of the magnetization but also a signal proportional to local velocity or displacement. This allows for quantification of the motion which is especially suitable for functional study of the cardiac deformation. In this work, an evaluation of the influence of several factors on the signal-to-noise ratio is presented for in-vivo displacement encoded imaging. Additionally, an extension of the method to acquire multiple displacement encoded slices in a single breath hold is also presented.Magnetic resonance imaging is usually associated with long scan times, and many methods exist to shorten the acquisition time while maintaining acceptable image quality. One class of such methods involves acquiring only a sparse subset of k-space. A special reconstruction is then necessary in order to obtain an artifact-free image. One family of these reconstruction techniques tailored for dynamic imaging is the k-t BLAST approach, which incorporates data-driven prior knowledge to suppress aliasing artifacts that otherwise occur with the sparse sampling. In this work, an extension of the original k-t BLAST method to two temporal dimensions is presented and applied to data acquired with full coverage of the cardio-respiratory cycles. Using this technique, termed k-t2 BLAST, simultaneous reduction of scan time and improved spatial resolution is demonstrated. Further, the loss of temporal fidelity when using the k-t BLAST approach is investigated, and an improved reconstruction is proposed for the application of cardiac function analysis.Visualization is a crucial part of the imaging chain. Scalar data, such as regular anatomical images, are straightforward to display. Myocardial strain and strain-rate, however, are tensor quantities which do not lend themselves to direct visualization. The problem of visualizing the tensor field is approached in this work by combining a local visualization that displays all degrees of freedom for a single tensor with an overview visualization using a scalar field representation of the complete tensor field. The scalar field is obtained by iterated adaptive filtering of a noise field, creating a continuous geometrical representation of the myocardial strain-rate tensor field.The results of the work presented in this thesis provide opportunities for improved imaging of myocardial function, in all areas of the imaging chain; acquisition, reconstruction and visualization.

     

    List of papers
    1. Tensor Field Visualisation using Adaptive Filtering of Noise Fields combined with Glyph Rendering
    Open this publication in new window or tab >>Tensor Field Visualisation using Adaptive Filtering of Noise Fields combined with Glyph Rendering
    2002 (English)In: IEEE Visualization 2002 Conference, IEEE , 2002, p. 371-378Conference paper, Published paper (Refereed)
    Abstract [en]

    While many methods exist for visualising scalar and vector data, visualisation of tensor data is still troublesome. We present a method for visualising second order tensors in three dimensions using a hybrid between direct volume rendering and glyph rendering.

    An overview scalar field is created by using three-dimensional adaptive filtering of a scalar field containing noise. The filtering process is controlled by the tensor field to be visualised, creating patterns that characterise the tensor field. By combining direct volume rendering of the scalar field with standard glyph rendering methods for detailed tensor visualisation, a hybrid solution is created.

    A combined volume and glyph renderer was implemented and tested with both synthetic tensors and strain-rate tensors from the human heart muscle, calculated from phase contrast magnetic resonance image data. A comprehensible result could be obtained, giving both an overview of the tensor field as well as detailed information on individual tensors.

    Place, publisher, year, edition, pages
    IEEE, 2002
    Keywords
    Tensor, Visualisation, Volume rendering, Glyph rendering, Hybrid rendering, Strain-rate
    National Category
    Medical and Health Sciences Medical Laboratory and Measurements Technologies
    Identifiers
    urn:nbn:se:liu:diva-14011 (URN)
    Available from: 2006-10-04 Created: 2006-10-04 Last updated: 2013-09-03Bibliographically approved
    2. Five-dimensional MRI Incorporating Simultaneous Resolution of Cardiac and Respiratory Phases for Volumetric Imaging
    Open this publication in new window or tab >>Five-dimensional MRI Incorporating Simultaneous Resolution of Cardiac and Respiratory Phases for Volumetric Imaging
    2006 (English)In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 25, no 1, p. 113-121Article in journal (Refereed) Published
    Abstract [en]

    Purpose

    To develop a new volumetric imaging method resolved over both the cardiac and respiratory cycles, to enable future physiological and pathophysiological studies of respiratory-related cardiac motion.

    Materials and Methods

    An acquisition scheme is proposed whereby the k-space acquisition order is controlled in real-time by the current cardiac and respiratory phases. To reduce eddy-current effects induced by sudden jumps in k-space, the acquisition order is further optimized by the use of a Hilbert curve trajectory in the ky-kz plane. A complete three-dimensional (3D) k-space is acquired for all combinations of cardiac and respiratory phases, yielding a five-dimensional (5D) data set after retrospective reconstruction.

    Results

    Left (LV) and right ventricular (RV) wall excursion was measured in a healthy volunteer. Diastolic LV diameter was shown to increase during expiration and decrease during inspiration, as expected from previous echocardiography studies. The LV volume was estimated for all cardiac and respiratory phases with the use of a fully 3D segmentation tool. The results confirmed that the diastolic LV volume increased during expiration and decreased during inspiration.

    Conclusion

    With its ability to measure motion anywhere in the heart, the described technique provides a promising approach for in-depth description of interventricular coupling, including 3D ventricular volumes, during both the cardiac and respiratory cycles.

    Keywords
    respiration, septal motion, interventricular coupling, volumetric MRI, cine imaging
    National Category
    Medical and Health Sciences Medical Laboratory and Measurements Technologies
    Identifiers
    urn:nbn:se:liu:diva-14012 (URN)10.1002/jmri.20820 (DOI)000243250800014 ()
    Available from: 2006-10-04 Created: 2006-10-04 Last updated: 2017-12-13Bibliographically approved
    3. k-t2 BLAST: Exploiting spatiotemporal structure in simultaneously cardiac and respiratory time-resolved volumetric imaging
    Open this publication in new window or tab >>k-t2 BLAST: Exploiting spatiotemporal structure in simultaneously cardiac and respiratory time-resolved volumetric imaging
    2007 (English)In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 58, no 5, p. 922-930Article in journal (Refereed) Published
    Abstract [en]

    Multidimensional imaging resolving both the cardiac and respiratory cycles simultaneously has the potential to describe important physiological interdependences between the heart and pulmonary processes. A fully five-dimensional acquisition with three spatial and two temporal dimensions is hampered, however, by the long acquisition time and low spatial resolution. A technique is proposed to reduce the scan time substantially by extending the k-t BLAST framework to two temporal dimensions. By sampling the k-t space sparsely in a lattice grid, the signal in the transform domain, x-f space, can be densely packed, exploiting the fact that large regions in the field of view have low temporal bandwidth. A volumetric online prospective triggering approach with full cardiac and respiratory cycle coverage was implemented. Retrospective temporal interpolation was used to refine the timing estimates for the center of k-space, which is sampled for all cardiac and respiratory time frames. This resulted in reduced reconstruction error compared with conventional k-t BLAST reconstruction. The k-t2 BLAST technique was evaluated by decimating a fully sampled five-dimensional data set, and feasibility was further demonstrated by performing sparsely sampled acquisitions. Compared to the fully sampled data, a fourfold improvement in spatial resolution was accomplished in approximately half the scan time.

    Keywords
    Cine imaging, k-t BLAST, Respiration, Volumetric MRI
    National Category
    Engineering and Technology Medical Laboratory and Measurements Technologies
    Identifiers
    urn:nbn:se:liu:diva-47833 (URN)10.1002/mrm.21295 (DOI)000250560000009 ()
    Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2017-12-13Bibliographically approved
    4. Improving Temporal Fidelity in k-t BLAST MRI Reconstruction
    Open this publication in new window or tab >>Improving Temporal Fidelity in k-t BLAST MRI Reconstruction
    Show others...
    2007 (English)In: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007: 10th International Conference, Brisbane, Australia, October 29 - November 2, 2007, Proceedings, Part II / [ed] Ayache, N; Ourdelin, S; Maeder, A, Springer Berlin/Heidelberg, 2007, p. 385-392Conference paper, Published paper (Refereed)
    Abstract [en]

    Studies of myocardial motion using magnetic resonance imaging usually require multiple breath holds and several methods have been proposed in order to reduce the scan time. Rapid imaging using k-t BLAST has gained much attention with its high reduction factors and image quality. Temporal smoothing, however, may reduce the accuracy when assessing cardiac function. In the present work, a modified reconstruction filter is proposed, that preserves more of the high temporal frequencies. Artificial decimation of a fully sampled data set was used to evaluate the reconstruction filter. Compared to the conventional k-t BLAST reconstruction, the modified filter produced images with sharper temporal delineation of the myocardial walls.  Quantitative analysis by means of regional velocity estimation showed that the modified reconstruction filter produced more accurate velocity estimations.

    Place, publisher, year, edition, pages
    Springer Berlin/Heidelberg, 2007
    Series
    Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 4792
    National Category
    Medical Image Processing
    Identifiers
    urn:nbn:se:liu:diva-21764 (URN)10.1007/978-3-540-75759-7_47 (DOI)000250917700047 ()978-3-540-75758-0 (ISBN)978-3-540-75759-7 (ISBN)
    Conference
    MICCAI 2007, 10th International Conference, Brisbane, Australia, October 29 - November 2, 2007
    Available from: 2009-10-05 Created: 2009-10-05 Last updated: 2018-02-09Bibliographically approved
    5. Single Breath Hold Multiple Slice DENSE MRI
    Open this publication in new window or tab >>Single Breath Hold Multiple Slice DENSE MRI
    Show others...
    2010 (English)In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 63, no 5, p. 1411-1414Article in journal (Refereed) Published
    Abstract [en]

    A method to acquire multiple displacement encoded slices within asingle breath hold is presented. Efficiency is improved overconventional Displacement ENcoding with Stimulated Echoes (DENSE) without compromising image quality by read-out of multiple slices inthe same cardiac cycle, thus utilizing the position encoded stimulatedecho available in the whole heart. The method was evaluated bycomparing strain values obtained using the proposed method to strainvalues obtained by conventional separate breath hold single-sliceDENSE acquisitions. Good agreement (Lagrangian E2 strainbias=0.000, 95% limits of agreement ±0.04,root-mean-square-difference 0.02 (9.4% of the mean end-systolic E2)) was found between the methods, indicating that the proposedmethod can replace a multiple breath hold acquisition. Eliminating theneed for multiple breath holds reduces the risk of changes in breathhold positions or heart rate, results in higher patient comfort andfacilitates inclusion of DENSE in a clinical routine protocol.

    Place, publisher, year, edition, pages
    John Wiley and Sons, Ltd, 2010
    Keywords
    DENSE, strain, multi-slice, breath hold, cardiac function
    National Category
    Medical Laboratory and Measurements Technologies
    Identifiers
    urn:nbn:se:liu:diva-51974 (URN)10.1002/mrm.22305 (DOI)000277098100030 ()
    Available from: 2009-11-25 Created: 2009-11-25 Last updated: 2017-12-12Bibliographically approved
    6. In-vivo SNR in DENSE MRI: temporal and regional effects of field strength, receiver coil sensitivity, and flip angle strategies
    Open this publication in new window or tab >>In-vivo SNR in DENSE MRI: temporal and regional effects of field strength, receiver coil sensitivity, and flip angle strategies
    Show others...
    2011 (English)In: Magnetic Resonance Imaging, ISSN 0730-725X, E-ISSN 1873-5894, Vol. 29, no 2, p. 202-208Article in journal (Refereed) Published
    Abstract [en]

    Aim: The influences on the SNR of DENSE MRI of field strength, receiver coil sensitivity and choice of flip angle strategy have been previously investigated individually. In this study, all of these parameters have been investigated in the same setting, and a mutual comparison of their impact on SNR is presented.

    Materials and methods: Ten healthy volunteers were imaged in a 1.5T and a 3T MRI system, using standard 5 or 6 channel cardiac coils as well as 32 channel coils, with four different excitation patterns. Variation of spatial coil sensitivity was assessed by regional SNR analysis.

    Results: SNR ranging from 2.8 to 30.5 was found depending on the combination of excitation patterns, coil sensitivity and field strength. The SNR at 3T was 53 ± 26% higher than at 1.5T (p<0.001), whereas spatial differences of 59 ± 26% were found in the ventricle (p<0.001). 32 channel coils provided 52 ± 29% higher SNR compared to standard 5 or 6 channel coils (p<0.001). A fixed flip angle strategy provided an excess of 50% higher SNR in half of the imaged cardiac cycle compared to a sweeping flip angle strategy, and a single phase acquisition provided a six-fold increase of SNR compared to a cine acquisition.

    Conclusion: The effect of field strength and receiver coil sensitivity influences the SNR with the same order of magnitude, whereas flip angle strategy can have a larger effect on SNR. Thus, careful choice of imaging hardware in combination with adaptation of the acquisition protocol is crucial in order to realize sufficient SNR in DENSE MRI.

    Place, publisher, year, edition, pages
    Elsevier, 2011
    Keywords
    DENSE, strain, SNR, flip angle, coil sensitivity
    National Category
    Medical Laboratory and Measurements Technologies
    Identifiers
    urn:nbn:se:liu:diva-51975 (URN)10.1016/j.mri.2010.08.016 (DOI)000287390500008 ()
    Note

    Original Publication: Andreas Sigfridsson, Henrik Haraldsson, Tino Ebbers, Hans Knutsson and Hajime Sakuma, In-vivo SNR in DENSE MRI: temporal and regional effects of field strength, receiver coil sensitivity, and flip angle strategies, 2011, Magnetic Resonance Imaging, (29), 2, 202-208. http://dx.doi.org/10.1016/j.mri.2010.08.016 Copyright: Elsevier Science B.V., Amsterdam. http://www.elsevier.com/

    Available from: 2009-11-25 Created: 2009-11-25 Last updated: 2017-12-12
    Download full text (pdf)
    Multidimensional MRI of Myocardial Dynamics: Acquisition, Reconstruction and Visualization
    Download (pdf)
    Cover
  • 42.
    Sigfridsson, Andreas
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Andersson, Mats
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Wigström, Lars
    Linköping University, Department of Biomedical Engineering, Center for Medical Image Science and Visualization. Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Kvitting, John-Peder Escobar
    Linköping University, Department of Biomedical Engineering, Center for Medical Image Science and Visualization. Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Knutsson, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Improving Temporal Fidelity in k-t BLAST MRI Reconstruction2007In: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007: 10th International Conference, Brisbane, Australia, October 29 - November 2, 2007, Proceedings, Part II / [ed] Ayache, N; Ourdelin, S; Maeder, A, Springer Berlin/Heidelberg, 2007, p. 385-392Conference paper (Refereed)
    Abstract [en]

    Studies of myocardial motion using magnetic resonance imaging usually require multiple breath holds and several methods have been proposed in order to reduce the scan time. Rapid imaging using k-t BLAST has gained much attention with its high reduction factors and image quality. Temporal smoothing, however, may reduce the accuracy when assessing cardiac function. In the present work, a modified reconstruction filter is proposed, that preserves more of the high temporal frequencies. Artificial decimation of a fully sampled data set was used to evaluate the reconstruction filter. Compared to the conventional k-t BLAST reconstruction, the modified filter produced images with sharper temporal delineation of the myocardial walls.  Quantitative analysis by means of regional velocity estimation showed that the modified reconstruction filter produced more accurate velocity estimations.

  • 43.
    Sigfridsson, Andreas
    et al.
    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.
    Ebbers, Tino
    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.
    Heiberg, Einar
    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.
    Wigström, Lars
    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.
    Tensor Field Visualisation using Adaptive Filtering of Noise Fields combined with Glyph Rendering2002In: IEEE Visualization 2002 Conference, IEEE , 2002, p. 371-378Conference paper (Refereed)
    Abstract [en]

    While many methods exist for visualising scalar and vector data, visualisation of tensor data is still troublesome. We present a method for visualising second order tensors in three dimensions using a hybrid between direct volume rendering and glyph rendering.

    An overview scalar field is created by using three-dimensional adaptive filtering of a scalar field containing noise. The filtering process is controlled by the tensor field to be visualised, creating patterns that characterise the tensor field. By combining direct volume rendering of the scalar field with standard glyph rendering methods for detailed tensor visualisation, a hybrid solution is created.

    A combined volume and glyph renderer was implemented and tested with both synthetic tensors and strain-rate tensors from the human heart muscle, calculated from phase contrast magnetic resonance image data. A comprehensible result could be obtained, giving both an overview of the tensor field as well as detailed information on individual tensors.

  • 44.
    Sigfridsson, Andreas
    et al.
    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.
    Escobar Kvitting, John-Peder
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Knutsson, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Wigström, Lars
    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.
    5D MRI - Cardiac and respiratory time-resolved volume imaging2004In: Proceedings of the annaual conference of the European Society for Magnetic Resonance in Medicine and Biology, 2004Conference paper (Refereed)
    Abstract [en]

    Respiratory motion is often a source of artifacts in cardiovascular imaging, but may also convey important physiological information. To improve our understanding

    Download full text (pdf)
    5D MRI - Cardiac and respiratory time-resolved volume imaging
  • 45.
    Sigfridsson, Andreas
    et al.
    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.
    Escobar Kvitting, John-Peder
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Wigström, Lars
    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.
    Andersson, Mats
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Knutsson, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Retrospective Respiratory Motion Compensation for Cardiac MRI2003Conference paper (Refereed)
    Abstract [en]

    Cardiac MRI is known to be degraded by respiratory motion. Short scans can be performed using breath-hold techniques, while coronary artery imaging commonly use navigator gated sequences, acquiring data in a known static respiration position.

    Download full text (pdf)
    Retrospective Respiratory Motion Compensation for Cardiac MRI
  • 46.
    Sigfridsson, Andreas
    et al.
    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.
    Escobar Kvitting, John-Peder
    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 Thoracic and Vascular Surgery.
    Wigström, Lars
    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.
    Knutsson, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    k-t2 BLAST: Exploiting spatiotemporal structure in simultaneous cardiac and respiratory resolved volume imaging2005Conference paper (Refereed)
    Abstract [en]

    Multidimensional imaging resolving both the cardiac and respiratory cycles simultaneously has the potential to describe important physiological interdependences between the heart and pulmonary processes. A fully five-dimensional acquisition with three spatial and two temporal dimensions is hampered, however, by the long acquisition time and low spatial resolution. A technique is proposed to reduce the scan time substantially by extending the k-t BLAST framework to two temporal dimensions. By sampling the k-t space sparsely in a lattice grid, the signal in the transform domain, x-f space, can be densely packed, exploiting the fact that large regions in the field of view have low temporal bandwidth. A volumetric online prospective triggering approach with full cardiac and respiratory cycle coverage was implemented. Retrospective temporal interpolation was used to refine the timing estimates for the center of k-space, which is sampled for all cardiac and respiratory time frames. This resulted in reduced reconstruction error compared with conventional k-t BLAST reconstruction. The k-t2 BLAST technique was evaluated by decimating a fully sampled five-dimensional data set, and feasibility was further demonstrated by performing sparsely sampled acquisitions. Compared to the fully sampled data, a fourfold improvement in spatial resolution was accomplished in approximately half the scan time.

    Download full text (pdf)
    k-t2 BLAST: Exploiting spatiotemporal structure in simultaneous cardiac and respiratory resolved volume imaging
  • 47.
    Sigfridsson, Andreas
    et al.
    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.
    Estepar, R.
    E.T.S.I. Telecomunicaci´on, University of Valladolid, Spain.
    Wigström, Lars
    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.
    Alberola, C.
    E.T.S.I. Telecomunicaci´on, University of Valladolid, Spain.
    Westin, C-F.
    Brigham and Women’s Hospital, Harvard Medical School, Boston.
    Diffusion tensor visualization using random field correlation and volume rendering2003Conference paper (Refereed)
    Abstract [en]

    The visualization of diffusion tensor fields remains a challenging topic. A representation based on volume rendering of a scalar field is presented. The method uses the tensor to correlate a noise field in the direction of greater diffusivity while preserving the high frequency components of the noise field in transversal diffusion directions.

    Download full text (pdf)
    Diffusion tensor visualization using random field correlaston and volume rendering
  • 48.
    Sigfridsson, Andreas
    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.
    Haraldsson, Henrik
    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.
    Ebbers, Tino
    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.
    Knutsson, Hans
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Sakuma, Hajima
    Mie University, Japan.
    SNR evaluation of 32 channel cardiac coils in DENSE MRI at 1.5 and 3T2010In: ISMRM 2010, International Society for Magnetic Resonance in Medicine ( ISMRM ) , 2010Conference paper (Other academic)
  • 49.
    Sigfridsson, Andreas
    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 Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Haraldsson, Henrik
    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 Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Ebbers, Tino
    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 Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Knutsson, Hans
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Sakuma, Hajime
    Mie University, Tsu, Mie, Japan.
    In­vivo SNR in DENSE MRI: temporal and regional effects of field  strength, receiver coil sensitivity, and flip angle strategies2009In: Proceedings of the ISMRM Workshop on Cardiovascular Flow,  Function & Tissue Mechanics, 2009Conference paper (Other academic)
  • 50.
    Sigfridsson, Andreas
    et al.
    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.
    Haraldsson, Henrik
    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.
    Ebbers, Tino
    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.
    Knutsson, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Health Sciences.
    Sakuma, Hajime
    Radiology, Mie University, Japan.
    In-vivo SNR in DENSE MRI: temporal and regional effects of field strength, receiver coil sensitivity, and flip angle strategies2011In: Magnetic Resonance Imaging, ISSN 0730-725X, E-ISSN 1873-5894, Vol. 29, no 2, p. 202-208Article in journal (Refereed)
    Abstract [en]

    Aim: The influences on the SNR of DENSE MRI of field strength, receiver coil sensitivity and choice of flip angle strategy have been previously investigated individually. In this study, all of these parameters have been investigated in the same setting, and a mutual comparison of their impact on SNR is presented.

    Materials and methods: Ten healthy volunteers were imaged in a 1.5T and a 3T MRI system, using standard 5 or 6 channel cardiac coils as well as 32 channel coils, with four different excitation patterns. Variation of spatial coil sensitivity was assessed by regional SNR analysis.

    Results: SNR ranging from 2.8 to 30.5 was found depending on the combination of excitation patterns, coil sensitivity and field strength. The SNR at 3T was 53 ± 26% higher than at 1.5T (p<0.001), whereas spatial differences of 59 ± 26% were found in the ventricle (p<0.001). 32 channel coils provided 52 ± 29% higher SNR compared to standard 5 or 6 channel coils (p<0.001). A fixed flip angle strategy provided an excess of 50% higher SNR in half of the imaged cardiac cycle compared to a sweeping flip angle strategy, and a single phase acquisition provided a six-fold increase of SNR compared to a cine acquisition.

    Conclusion: The effect of field strength and receiver coil sensitivity influences the SNR with the same order of magnitude, whereas flip angle strategy can have a larger effect on SNR. Thus, careful choice of imaging hardware in combination with adaptation of the acquisition protocol is crucial in order to realize sufficient SNR in DENSE MRI.

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