liu.seSearch for publications in DiVA
Change search
Refine search result
1 - 11 of 11
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the 'Create feeds' function.
  • 1.
    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.

  • 2.
    Bustamante, Mariana
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. 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. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Carlhäll, Carljohan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    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).
    Improving visualization of 4D flow cardiovascular magnetic resonance with four-dimensional angiographic data: generation of a 4D phase-contrast magnetic resonance CardioAngiography (4D PC-MRCA)2017In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 19, article id 47Article in journal (Refereed)
    Abstract [en]

    Magnetic Resonance Angiography (MRA) and Phase-Contrast MRA (PC-MRA) approaches used for assessment of cardiovascular morphology typically result in data containing information from the entire cardiac cycle combined into one 2D or 3D image. Information specific to each timeframe of the cardiac cycle is, however, lost in this process. This study proposes a novel technique, called Phase-Contrast Magnetic Resonance CardioAngiography (4D PC-MRCA), that utilizes the full potential of 4D Flow CMR when generating temporally resolved PC-MRA data to improve visualization of the heart and major vessels throughout the cardiac cycle. Using non-rigid registration between the timeframes of the 4D Flow CMR acquisition, the technique concentrates information from the entire cardiac cycle into an angiographic dataset at one specific timeframe, taking movement over the cardiac cycle into account. Registration between the timeframes is used once more to generate a time-resolved angiography. The method was evaluated in ten healthy volunteers. Visual comparison of the 4D PC-MRCAs versus PC-MRAs generated from 4D Flow CMR using the traditional approach was performed by two observers using Maximum Intensity Projections (MIPs). The 4D PC-MRCAs resulted in better visibility of the main anatomical regions of the cardiovascular system, especially where cardiac or vessel motion was present. The proposed method represents an improvement over previous PC-MRA generation techniques that rely on 4D Flow CMR, as it effectively utilizes all the information available in the acquisition. The 4D PC-MRCA can be used to visualize the motion of the heart and major vessels throughout the entire cardiac cycle.

  • 3.
    Bustamante, Mariana
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Petersson, Sven
    Linköping University, Department of Medical and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Medicine and Health Sciences.
    Eriksson, Jonatan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Alehagen, Urban
    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.
    Dyverfeldt, Petter
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Carlhäll, Carljohan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    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).
    Atlas-based analysis of 4D flow CMR: Automated vessel segmentation and flow quantification2015In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 17, no 87Article in journal (Refereed)
    Abstract [en]

    Background: Flow volume quantification in the great thoracic vessels is used in the assessment of several cardiovascular diseases. Clinically, it is often based on semi-automatic segmentation of a vessel throughout the cardiac cycle in 2D cine phase-contrast Cardiovascular Magnetic Resonance (CMR) images. Three-dimensional (3D), time-resolved phase-contrast CMR with three-directional velocity encoding (4D flow CMR) permits assessment of net flow volumes and flow patterns retrospectively at any location in a time-resolved 3D volume. However, analysis of these datasets can be demanding. The aim of this study is to develop and evaluate a fully automatic method for segmentation and analysis of 4D flow CMR data of the great thoracic vessels. Methods: The proposed method utilizes atlas-based segmentation to segment the great thoracic vessels in systole, and registration between different time frames of the cardiac cycle in order to segment these vessels over time. Additionally, net flow volumes are calculated automatically at locations of interest. The method was applied on 4D flow CMR datasets obtained from 11 healthy volunteers and 10 patients with heart failure. Evaluation of the method was performed visually, and by comparison of net flow volumes in the ascending aorta obtained automatically (using the proposed method), and semi-automatically. Further evaluation was done by comparison of net flow volumes obtained automatically at different locations in the aorta, pulmonary artery, and caval veins. Results: Visual evaluation of the generated segmentations resulted in good outcomes for all the major vessels in all but one dataset. The comparison between automatically and semi-automatically obtained net flow volumes in the ascending aorta resulted in very high correlation (r(2) = 0.926). Moreover, comparison of the net flow volumes obtained automatically in other vessel locations also produced high correlations where expected: pulmonary trunk vs. proximal ascending aorta (r(2) = 0.955), pulmonary trunk vs. pulmonary branches (r(2) = 0.808), and pulmonary trunk vs. caval veins (r(2) = 0.906). Conclusions: The proposed method allows for automatic analysis of 4D flow CMR data, including vessel segmentation, assessment of flow volumes at locations of interest, and 4D flow visualization. This constitutes an important step towards facilitating the clinical utility of 4D flow CMR.

  • 4.
    Dyverfeldt, Petter
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Bissell, Malenka
    University of Oxford, England.
    Barker, Alex J.
    Northwestern University, IL 60611 USA.
    Bolger, Ann F
    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. University of Calif San Francisco, CA USA.
    Carlhäll, Carljohan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    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).
    Francios, Christopher J.
    University of Wisconsin, WI 53706 USA.
    Frydrychowicz, Alex
    University Hospital Schleswig Holstein, Germany.
    Geiger, Julia
    University of Childrens Hospital Zurich, Switzerland.
    Giese, Daniel
    University Hospital Cologne, Germany.
    Hope, Michael D.
    University of Calif San Francisco, CA USA.
    Kilner, Philip J.
    University of London Imperial Coll Science Technology and Med, England.
    Kozerke, Sebastian
    University of Zurich, Switzerland; ETH, Switzerland.
    Myerson, Saul
    University of Oxford, England.
    Neubauer, Stefan
    University of Oxford, England.
    Wieben, Oliver
    University of Wisconsin, WI 53706 USA.
    Markl, Michael
    Northwestern University, IL 60611 USA; Northwestern University, IL 60611 USA.
    4D flow cardiovascular magnetic resonance consensus statement2015In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 17, no 72Article, review/survey (Refereed)
    Abstract [en]

    Pulsatile blood flow through the cavities of the heart and great vessels is time-varying and multidirectional. Access to all regions, phases and directions of cardiovascular flows has formerly been limited. Four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) has enabled more comprehensive access to such flows, with typical spatial resolution of 1.5x1.5x1.5 - 3x3x3 mm(3), typical temporal resolution of 30-40 ms, and acquisition times in the order of 5 to 25 min. This consensus paper is the work of physicists, physicians and biomedical engineers, active in the development and implementation of 4D Flow CMR, who have repeatedly met to share experience and ideas. The paper aims to assist understanding of acquisition and analysis methods, and their potential clinical applications with a focus on the heart and greater vessels. We describe that 4D Flow CMR can be clinically advantageous because placement of a single acquisition volume is straightforward and enables flow through any plane across it to be calculated retrospectively and with good accuracy. We also specify research and development goals that have yet to be satisfactorily achieved. Derived flow parameters, generally needing further development or validation for clinical use, include measurements of wall shear stress, pressure difference, turbulent kinetic energy, and intracardiac flow components. The dependence of measurement accuracy on acquisition parameters is considered, as are the uses of different visualization strategies for appropriate representation of time-varying multidirectional flow fields. Finally, we offer suggestions for more consistent, user-friendly implementation of 4D Flow CMR acquisition and data handling with a view to multicenter studies and more widespread adoption of the approach in routine clinical investigations.

  • 5.
    Escobar Kvitting, John-Peder
    et al.
    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.
    Ebbers, Tino
    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.
    Engvall, Jan
    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.
    Sutherland, George R.
    Department of Cardiology, University Hospital Gasthuisberg, Leuven, Belgium.
    Wranne, Bengt
    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.
    Wigström, Lars
    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.
    Three-directional myocardial motion assessed using 3D phase contrast MRI2004In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 6, no 3, p. 627-636Article in journal (Refereed)
    Abstract [en]

    Regional myocardial function is a complex entity consisting of motion in three dimensions (3D). Besides magnetic resonance imaging (MRI), no other noninvasive technique can give a true 3D description of cardiac motion. Using a time‐resolved 3D phase contrast technique, three‐dimensional image volumes containing myocardial velocity data in six normal volunteers were acquired. Coordinates and velocity information were extracted from nine points placed in different myocardial segments in the left ventricle (LV), and decomposed into longitudinal (VL), radial (VR), and circumferential (VC) velocity components. Our findings confirm a longitudinal apex‐to‐base gradient for the LV, with only a small motion of the apex. The mean velocity for VL for all the basal segments was higher compared to the midsegments during systole [3.5 ± 1.2 vs. 2.5 ± 1.7 cm/s (p < 0.01)], early filling [− 6.9 ± 1.8 vs. − 4.9 ± 1.8 cm/s (p < 0.001)], and during atrial contraction [− 2.2 ± 1.4 vs. − 1.6 ± 1.3 cm/s (p < 0.05)]. A similar pattern was observed when comparing velocities from the midsegments to the apex. Radial velocity was higher during early filling in the midportion of the lateral [− 4.9 ± 2.7 vs. − 3.2 ± 1.6 cm/s (p < 0.05)] wall compared to the basal segments, no difference was observed for the septal [− 2.0 ± 1.5 vs. − 0.3 ± 2.5 cm/s (p = 0.15)], anterior [− 5.8 ± 3.3 vs. − 4.0 ± 1.7 cm/s (p = 0.17)], and posterior [− 2.3 ± 2.1 vs. − 2.5 ± 1.0 cm/s (p = 0.78)] walls. When observing the myocardial velocity in a single point and visualizing the movement of the main direction of the velocities in this point as vectors in velocity vector plots like planes, it is clear that myocardial movement is by no means one dimensional. In conclusion, our time‐resolved 3D, phase contrast MRI technique makes it feasible to extract myocardial velocities from anywhere in the myocardium, including all three velocity components without the need for positioning any slices at the time of acquisition.

  • 6. Hänni, M
    et al.
    Edvardson, H
    Wågberg, M
    Pettersson, K
    Smedby, Örjan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Medical Radiology. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology UHL. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Quantification of Atherosclerosis with MRI and Image Processing in Spontaneously Hyperlipidemic Rabbits2004In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 6, p. 675-684Article in journal (Refereed)
  • 7.
    Kihlberg, Johan
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Health Sciences.
    Haraldsson, Henrik
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV). Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA .
    Sigfridsson, Andreas
    Department of Clinical Physiology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden .
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Engvall, Jan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Clinical experience of strain imaging using DENSE for detecting infarcted cardiac segments2015In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 17, article id 50Article in journal (Refereed)
    Abstract [en]

    Background

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

    Methods

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

    Results

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

    Conclusions

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

  • 8.
    Kvernby, Sofia
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine.
    Warntjes, Marcel Jan Bertus
    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). Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Haraldsson, Henrik
    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). Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Carlhäll, Carl-Johan
    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). Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Engvall, Jan
    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). 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, Faculty of Health Sciences. 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, Department of Science and Technology, Media and Information Technology.
    Simultaneous three-dimensional myocardial T1 and T2 mapping in one breath hold with 3D-QALAS2014In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 16, no 102Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Quantification of the longitudinal- and transverse relaxation time in the myocardium has shown to provide important information in cardiac diagnostics. Methods for cardiac relaxation time mapping generally demand a long breath hold to measure either T1 or T2 in a single 2D slice. In this paper we present and evaluate a novel method for 3D interleaved T1 and T2 mapping of the whole left ventricular myocardium within a single breath hold of 15 heartbeats.

    METHODS: The 3D-QALAS (3D-quantification using an interleaved Look-Locker acquisition sequence with T2 preparation pulse) is based on a 3D spoiled Turbo Field Echo sequence using inversion recovery with interleaved T2 preparation. Quantification of both T1 and T2 in a volume of 13 slices with a resolution of 2.0x2.0x6.0 mm is obtained from five measurements by using simulations of the longitudinal magnetizations Mz. This acquisition scheme is repeated three times to sample k-space. The method was evaluated both in-vitro (validated against Inversion Recovery and Multi Echo) and in-vivo (validated against MOLLI and Dual Echo).

    RESULTS: In-vitro, a strong relation was found between 3D-QALAS and Inversion Recovery (R = 0.998; N = 10; p < 0.01) and between 3D-QALAS and Multi Echo (R = 0.996; N = 10; p < 0.01). The 3D-QALAS method showed no dependence on e.g. heart rate in the interval of 40-120 bpm. In healthy myocardium, the mean T1 value was 1083 ± 43 ms (mean ± SD) for 3D-QALAS and 1089 ± 54 ms for MOLLI, while the mean T2 value was 50.4 ± 3.6 ms 3D-QALAS and 50.3 ± 3.5 ms for Dual Echo. No significant difference in in-vivo relaxation times was found between 3D-QALAS and MOLLI (N = 10; p = 0.65) respectively 3D-QALAS and Dual Echo (N = 10; p = 0.925) for the ten healthy volunteers.

    CONCLUSIONS: The 3D-QALAS method has demonstrated good accuracy and intra-scan variability both in-vitro and in-vivo. It allows rapid acquisition and provides quantitative information of both T1 and T2 relaxation times in the same scan with full coverage of the left ventricle, enabling clinical application in a broader spectrum of cardiac disorders.

  • 9.
    Nguyen, Patricia K.
    et al.
    Stanford Univ, Dept Med, Div Cardiovasc Med, Stanford, CA 94305 USA.
    Meyer, Craig
    Univ Virginia, Dept Biomed Engn, Charlottesville, VA 22903 USA.
    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.
    Yang, Phillip
    Stanford Univ, Dept Med, Div Cardiovasc Med, Stanford, CA 94305 USA.
    McConnell, Michael V.
    Stanford Univ, Dept Med, Div Cardiovasc Med, Stanford, CA 94305 USA.
    Noninvasive assessment of coronary vasodilation using cardiovascular magnetic resonance in patients at high risk for coronary artery disease2008In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 10Article in journal (Refereed)
    Abstract [en]

    Background: Impaired coronary vasodilation to both endothelial-dependent and endothelial-independent stimuli have been associated with atherosclerosis. Direct measurement of coronary vasodilation using x-ray angiography or intravascular ultrasound is invasive and, thus, not appropriate for asymptomatic patients or for serial follow-up. In this study, high-resolution coronary cardiovascular magnetic resonance (CMR) was used to investigate the vasodilatory response to nitroglycerine (NTG) of asymptomatic patients at high risk for CAD. Methods: A total of 46 asymptomatic subjects were studied: 13 high-risk patients [8 with diabetes mellitus (DM), 5 with end stage renal disease (ESRD)] and 33 age-matched controls. Long-axis and cross-sectional coronary artery images were acquired pre-and 5 minutes post-sublingual NTG using a sub-mm-resolution multi-slice spiral coronary CMR sequence. Coronary cross sectional area (CSA) was measured on pre-and post-NTG images and % coronary vasodilation was calculated. Results: Patients with DM and ESRD had impaired coronary vasodilation to NTG compared to age-matched controls (17.8 +/- 7.3% vs. 25.6 +/- 7.1%, p = 0.002). This remained significant for ESRD patients alone (14.8 +/- 7.7% vs. 25.6 +/- 7.1%, p = 0.003) and for DM patients alone (19.8 +/- 6.3% vs. 25.6 +/- 7.1%, p = 0.049), with a non-significant trend toward greater impairment in the ESRD vs. DM patients (14.8 +/- 7.7% vs. 19.8 +/- 6.3%, p = 0.23). Conclusion: Noninvasive coronary CMR demonstrates impairment of coronary vasodilation to NTG in high-risk patients with DM and ESRD. This may provide a functional indicator of subclinical atherosclerosis and warrants clinical follow up to determine prognostic significance.

  • 10.
    Stoll, Victoria M.
    et al.
    Univ Oxford, England.
    Loudon, Margaret
    Univ Oxford, England.
    Eriksson, Jonatan
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Bissell, Malenka M.
    Univ Oxford, England.
    Dyverfeldt, Petter
    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, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Myerson, Saul G.
    Univ Oxford, England.
    Neubauer, Stefan
    Univ Oxford, England.
    Carlhäll, Carljohan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Hess, Aaron T.
    Univ Oxford, England.
    Test-retest variability of left ventricular 4D flow cardiovascular magnetic resonance measurements in healthy subjects2018In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 20, article id 15Article in journal (Refereed)
    Abstract [en]

    Background: Quantification and visualisation of left ventricular (LV) blood flow is afforded by three-dimensional, time resolved phase contrast cardiovascular magnetic resonance (CMR 4D flow). However, few data exist upon the repeatability and variability of these parameters in a healthy population. We aimed to assess the repeatability and variability over time of LV 4D CMR flow measurements. Methods: Forty five controls underwent CMR 4D flow data acquisition. Of these, 10 underwent a second scan within the same visit (scan-rescan), 25 returned for a second visit (interval scan; median interval 52 days, IQR 28-57 days). The LV-end diastolic volume (EDV) was divided into four flow components: 1) Direct flow: inflow that passes directly to ejection; 2) Retained inflow: inflow that enters and resides within the LV; 3) Delayed ejection flow: starts within the LV and is ejected and 4) Residual volume: blood that resides within the LV for amp;gt;2 cardiac cycles. Each flow components volume was related to the EDV (volume-ratio). The kinetic energy at end-diastole (ED) was measured and divided by the components volume. Results: The dominant flow component in all 45 controls was the direct flow (volume ratio 38 +/- 4%) followed by the residual volume (30 +/- 4%), then delayed ejection flow (16 +/- 3%) and retained inflow (16 +/- 4%). The kinetic energy at ED for each component was direct flow (7.8 +/- 3.0 microJ/ml), retained inflow (4.1 +/- 2.0 microJ/ml), delayed ejection flow (6. 3 +/- 2.3 microJ/ml) and the residual volume (1.2 +/- 0.5 microJ/ml). The coefficients of variation for the scan-rescan ranged from 2.5%-9.2% for the flow components volume ratio and between 13.5%-17.7% for the kinetic energy. The interval scan results showed higher coefficients of variation with values from 6.2-16.1% for the flow components volume ratio and 16.9-29.0% for the kinetic energy of the flow components. Conclusion: LV flow components volume and their associated kinetic energy values are repeatable and stable within a population over time. However, the variability of these measurements in individuals over time is greater than can be attributed to sources of error in the data acquisition and analysis, suggesting that additional physiological factors may influence LV flow measurements.

  • 11. Yang, P C
    et al.
    Santos, J M
    Nguyen, P K
    Scott, G C
    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.
    McConnell, M V
    Wright, G A
    Nishimura, D G
    Pauly, J M
    Hu, B S
    Dynamic Real-Time Architecture in Magnetic Resonance Coronary Angiography - A Prosepctive Clinical Trial2004In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 6, p. 885-894Article in journal (Refereed)
1 - 11 of 11
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf