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Viola F, Bustamante M, Bolger A, Engvall J, Ebbers T. Diastolic function assessment with four-dimensional flow cardiovascular magnetic resonance using automatic deep learning E/A ratio analysis. J Cardiovasc Magn Reson 2024; 26:101042. [PMID: 38556134 PMCID: PMC11058894 DOI: 10.1016/j.jocmr.2024.101042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 03/19/2024] [Accepted: 03/26/2024] [Indexed: 04/02/2024] Open
Abstract
BACKGROUND Diastolic left ventricular (LV) dysfunction is a powerful contributor to the symptoms and prognosis of patients with heart failure. In patients with depressed LV systolic function, the E/A ratio, the ratio between the peak early (E) and the peak late (A) transmitral flow velocity, is the first step to defining the grade of diastolic dysfunction. Doppler echocardiography (echo) is the preferred imaging technique for diastolic function assessment, while cardiovascular magnetic resonance (CMR) is less established as a method. Previous four-dimensional (4D) Flow-based studies have looked at the E/A ratio proximal to the mitral valve, requiring manual interaction. In this study, we compare an automated, deep learning-based and two semi-automated approaches for 4D Flow CMR-based E/A ratio assessment to conventional, gold-standard echo-based methods. METHODS Ninety-seven subjects with chronic ischemic heart disease underwent a cardiac echo followed by CMR investigation. 4D Flow-based E/A ratio values were computed using three different approaches; two semi-automated, assessing the E/A ratio by measuring the inflow velocity (MVvel) and the inflow volume (MVflow) at the mitral valve plane, and one fully automated, creating a full LV segmentation using a deep learning-based method with which the E/A ratio could be assessed without constraint to the mitral plane (LVvel). RESULTS MVvel, MVflow, and LVvel E/A ratios were strongly associated with echocardiographically derived E/A ratio (R2 = 0.60, 0.58, 0.72). LVvel peak E and A showed moderate association to Echo peak E and A, while MVvel values were weakly associated. MVvel and MVflow EA ratios were very strongly associated with LVvel (R2 = 0.84, 0.86). MVvel peak E was moderately associated with LVvel, while peak A showed a strong association (R2 = 0.26, 0.57). CONCLUSION Peak E, peak A, and E/A ratio are integral to the assessment of diastolic dysfunction and may expand the utility of CMR studies in patients with cardiovascular disease. While underestimation of absolute peak E and A velocities was noted, the E/A ratio measured with all three 4D Flow methods was strongly associated with the gold standard Doppler echocardiography. The automatic, deep learning-based method performed best, with the most favorable runtime of ∼40 seconds. As both semi-automatic methods associated very strongly to LVvel, they could be employed as an alternative for estimation of E/A ratio.
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Affiliation(s)
- Federica Viola
- Division of Diagnostics and Specialist Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden; Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
| | - Mariana Bustamante
- Division of Diagnostics and Specialist Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden; Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden; deCODE Genetics/Amgen Inc., Reykjavik, Iceland
| | - Ann Bolger
- Division of Diagnostics and Specialist Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden; Department of Medicine, University of California San Francisco, San Francisco, CA, United States
| | - Jan Engvall
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden; Department of Clinical Physiology in Linköping, and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Tino Ebbers
- Division of Diagnostics and Specialist Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden; Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
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2
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Cardiac troponin T and NT-proBNP for detecting myocardial ischemia in suspected chronic coronary syndrome. Int J Cardiol 2022; 361:14-17. [DOI: 10.1016/j.ijcard.2022.05.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 04/06/2022] [Accepted: 05/11/2022] [Indexed: 11/23/2022]
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Kihlberg J, Gupta V, Haraldsson H, Sigfridsson A, Sarvari SI, Ebbers T, Engvall JE. Clinical validation of three cardiovascular magnetic resonance techniques to measure strain and torsion in patients with suspected coronary artery disease. J Cardiovasc Magn Reson 2020; 22:83. [PMID: 33280612 PMCID: PMC7720468 DOI: 10.1186/s12968-020-00684-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Accepted: 10/29/2020] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Several cardiovascular magnetic resonance (CMR) techniques can measure myocardial strain and torsion with high accuracy. The purpose of this study was to compare displacement encoding with stimulated echoes (DENSE), tagging and feature tracking (FT) for measuring circumferential and radial myocardial strain and myocardial torsion in order to assess myocardial function and infarct scar burden both at a global and at a segmental level. METHOD 116 patients with a high likelihood of coronary artery disease (European SCORE > 15%) underwent CMR examination including cine images, tagging, DENSE and late gadolinium enhancement (LGE) in the short axis direction. In total, 97 patients had signs of myocardial disease and 19 had no abnormalities in terms of left ventricular (LV) wall mass index, LV ejection fraction, wall motion, LGE or a history of myocardial infarction. Thirty-four patients had myocardial infarct scar with a transmural LGE extent (transmurality) that exceeded 50% of the wall thickness in at least one segment. Global circumferential strain (GCS) and global radial strain (GRS) was analyzed using FT of cine loops, deformation of tag lines or DENSE displacement. RESULTS DENSE and tagging both showed high sensitivity (82% and 71%) at a specificity of 80% for the detection of segments with > 50% LGE transmurality, and receiver operating characteristics (ROC) analysis showed significantly higher area under the curve-values (AUC) for DENSE (0.87) than for tagging (0.83, p < 0.001) and FT (0.66, p = 0.003). GCS correlated with global LGE when determined with DENSE (r = 0.41), tagging (r = 0.37) and FT (r = 0.15). GRS had a low but significant negative correlation with LGE; DENSE r = - 0.10, FT r = - 0.07 and tagging r = - 0.16. Torsion from DENSE and tagging had a weak correlation (- 0.20 and - 0.22 respectively) with global LGE. CONCLUSION Circumferential strain from DENSE detected segments with > 50% scar with a higher AUC than strain determined from tagging and FT at a segmental level. GCS and torsion computed from DENSE and tagging showed similar correlation with global scar size, while when computed from FT, the correlation was lower.
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Affiliation(s)
- Johan Kihlberg
- Department of Radiology in Linköping, and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
| | - Vikas Gupta
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Henrik Haraldsson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Andreas Sigfridsson
- Department of Clinical Physiology & Molecular Medicine and Surgery, Karolinska Institutet, Karolinska University Hospital, 17176, Stockholm, Sweden
| | - Sebastian I Sarvari
- Department of Cardiology, Oslo University Hospital, Rikshospitalet, 0316, Oslo, Norway
| | - Tino Ebbers
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Jan E Engvall
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
- Department of Clinical Physiology in Linköping, and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
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Pedrosa J, Duchenne J, Queirós S, Degtiarova G, Gheysens O, Claus P, Voigt JU, D'hooge J. Non-invasive myocardial performance mapping using 3D echocardiographic stress-strain loops. Phys Med Biol 2019; 64:115026. [PMID: 31096199 DOI: 10.1088/1361-6560/ab21f8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Regional contribution to left ventricular (LV) ejection is of much clinical importance but its assessment is notably challenging. While deformation imaging is often used, this does not take into account loading conditions. Recently, a method for intraventricular pressure estimation was proposed, thus allowing for loading conditions to be taken into account in a non-invasive way. In this work, a method for 3D automatic myocardial performance mapping in echocardiography is proposed by performing 3D myocardial segmentation and tracking, thus giving access to local geometry and strain. This is then used to assess local LV stress-strain relationships which can be seen as a measure of local myocardial work. The proposed method was validated against 18F-fluorodeoxyglucose positron emission tomography, the reference method to clinically assess local metabolism. Averaged over all patients, the mean correlation between FDG-PET and the proposed method was [Formula: see text]. In conclusion, stress-strain loops were, for the first time, estimated from 3D echocardiography and correlated to the clinical gold standard for local metabolism, showing the future potential of real-time 3D echocardiography (RT3DE) for the assessment of local metabolic activity of the heart.
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Affiliation(s)
- João Pedrosa
- Laboratory on Cardiovascular Imaging and Dynamics, Department of Cardiovascular Sciences, KU Leuven, Belgium
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Bustamante M, Gupta V, Forsberg D, Carlhäll CJ, Engvall J, Ebbers T. Automated multi-atlas segmentation of cardiac 4D flow MRI. Med Image Anal 2018; 49:128-140. [DOI: 10.1016/j.media.2018.08.003] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2017] [Revised: 08/07/2018] [Accepted: 08/10/2018] [Indexed: 11/16/2022]
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Myhre PL, Omland T, Sarvari SI, Ukkonen H, Rademakers F, Engvall JE, Hagve TA, Nagel E, Sicari R, Zamorano JL, Monaghan M, D'hooge J, Edvardsen T, Røsjø H. Cardiac Troponin T Concentrations, Reversible Myocardial Ischemia, and Indices of Left Ventricular Remodeling in Patients with Suspected Stable Angina Pectoris: a DOPPLER-CIP Substudy. Clin Chem 2018; 64:1370-1379. [DOI: 10.1373/clinchem.2018.288894] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2018] [Accepted: 06/01/2018] [Indexed: 11/06/2022]
Abstract
Abstract
BACKGROUND
Cardiac troponin T concentrations measured with high-sensitivity assays (hs-cTnT) provide important prognostic information for patients with stable coronary artery disease (CAD). However, whether hs-cTnT concentrations mainly reflect left ventricular (LV) remodeling or recurrent myocardial ischemia in this population is not known.
METHODS
We measured hs-cTnT concentrations in 619 subjects with suspected stable CAD in a prospectively designed multicenter study. We identified associations with indices of LV remodeling, as assessed by cardiac MRI and echocardiography, and evidence of myocardial ischemia diagnosed by single positron emission computed tomography.
RESULTS
Median hs-cTnT concentration was 7.8 ng/L (interquartile range, 4.8–11.6 ng/L), and 111 patients (18%) had hs-cTnT concentrations above the upper reference limit (>14 ng/L). Patients with hs-cTnT >14 ng/L had increased LV mass (144 ± 40 g vs 116 ± 34 g; P < 0.001) and volume (179 ± 80 mL vs 158 ± 44 mL; P = 0.006), lower LV ejection fraction (LVEF) (59 ± 14 vs 62 ± 11; P = 0.006) and global longitudinal strain (14.1 ± 3.4% vs 16.9 ± 3.2%; P < 0.001), and more reversible perfusion defects (P = 0.001) and reversible wall motion abnormalities (P = 0.008). Age (P = 0.009), estimated glomerular filtration rate (P = 0.01), LV mass (P = 0.003), LVEF (P = 0.03), and evidence of reversible myocardial ischemia (P = 0.004 for perfusion defects and P = 0.02 for LV wall motion) were all associated with increasing hs-cTnT concentrations in multivariate analysis. We found analogous results when using the revised US upper reference limit of 19 ng/L.
CONCLUSIONS
hs-cTnT concentrations reflect both LV mass and reversible myocardial ischemia in patients with suspected stable CAD.
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Affiliation(s)
- Peder L Myhre
- Division of Medicine, Akershus University Hospital, Lørenskog, Norway and Center for Heart Failure Research, University of Oslo, Oslo, Norway
- Division of Cardiovascular Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Torbjørn Omland
- Division of Medicine, Akershus University Hospital, Lørenskog, Norway and Center for Heart Failure Research, University of Oslo, Oslo, Norway
| | - Sebastian I Sarvari
- Department of Cardiology, Oslo University Hospital, Rikshospitalet and Center for Heart Failure Research, University of Oslo, Oslo, Norway
| | - Heikki Ukkonen
- Department of Medicine, Turku University Hospital, Turku, Finland
| | - Frank Rademakers
- Department of Cardiovascular Sciences, University Hospitals Leuven and KU Leuven, Leuven, Belgium
| | - Jan E Engvall
- Department of Clinical Physiology Linköping University, Linköping, Sweden and Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
| | - Tor-Arne Hagve
- Division of Diagnostics and Technology, Akershus University Hospital, Lørenskog and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Eike Nagel
- Kings College Hospital, Department of Non-invasive Cardiology, Denmark Hill, London, UK
| | - Rosa Sicari
- CNR, Istituto di Fisiologia Clinica, Pisa, Italy
| | - Jose L Zamorano
- Hospital Universitario Ramón y Cajal, Cardiovascular Imaging Unit, Madrid, Spain
| | - Mark Monaghan
- Kings College Hospital, Department of Non-invasive Cardiology, Denmark Hill, London, UK
| | - Jan D'hooge
- Department of Cardiovascular Sciences, University Hospitals Leuven and KU Leuven, Leuven, Belgium
| | - Thor Edvardsen
- Department of Cardiology, Oslo University Hospital, Rikshospitalet and Center for Heart Failure Research, University of Oslo, Oslo, Norway
| | - Helge Røsjø
- Division of Medicine, Akershus University Hospital, Lørenskog, Norway and Center for Heart Failure Research, University of Oslo, Oslo, Norway
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Pedrosa J, Queiros S, Bernard O, Engvall J, Edvardsen T, Nagel E, D'hooge J. Fast and Fully Automatic Left Ventricular Segmentation and Tracking in Echocardiography Using Shape-Based B-Spline Explicit Active Surfaces. IEEE TRANSACTIONS ON MEDICAL IMAGING 2017; 36:2287-2296. [PMID: 28783626 DOI: 10.1109/tmi.2017.2734959] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Cardiac volume/function assessment remains a critical step in daily cardiology, and 3-D ultrasound plays an increasingly important role. Fully automatic left ventricular segmentation is, however, a challenging task due to the artifacts and low contrast-to-noise ratio of ultrasound imaging. In this paper, a fast and fully automatic framework for the full-cycle endocardial left ventricle segmentation is proposed. This approach couples the advantages of the B-spline explicit active surfaces framework, a purely image information approach, to those of statistical shape models to give prior information about the expected shape for an accurate segmentation. The segmentation is propagated throughout the heart cycle using a localized anatomical affine optical flow. It is shown that this approach not only outperforms other state-of-the-art methods in terms of distance metrics with a mean average distances of 1.81±0.59 and 1.98±0.66 mm at end-diastole and end-systole, respectively, but is computationally efficient (in average 11 s per 4-D image) and fully automatic.
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Morais P, Queirós S, Heyde B, Engvall J, 'hooge JD, Vilaça JL. Fully automatic left ventricular myocardial strain estimation in 2D short-axis tagged magnetic resonance imaging. Phys Med Biol 2017; 62:6899-6919. [PMID: 28783715 DOI: 10.1088/1361-6560/aa7dc2] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Cardiovascular diseases are among the leading causes of death and frequently result in local myocardial dysfunction. Among the numerous imaging modalities available to detect these dysfunctional regions, cardiac deformation imaging through tagged magnetic resonance imaging (t-MRI) has been an attractive approach. Nevertheless, fully automatic analysis of these data sets is still challenging. In this work, we present a fully automatic framework to estimate left ventricular myocardial deformation from t-MRI. This strategy performs automatic myocardial segmentation based on B-spline explicit active surfaces, which are initialized using an annular model. A non-rigid image-registration technique is then used to assess myocardial deformation. Three experiments were set up to validate the proposed framework using a clinical database of 75 patients. First, automatic segmentation accuracy was evaluated by comparing against manual delineations at one specific cardiac phase. The proposed solution showed an average perpendicular distance error of 2.35 ± 1.21 mm and 2.27 ± 1.02 mm for the endo- and epicardium, respectively. Second, starting from either manual or automatic segmentation, myocardial tracking was performed and the resulting strain curves were compared. It is shown that the automatic segmentation adds negligible differences during the strain-estimation stage, corroborating its accuracy. Finally, segmental strain was compared with scar tissue extent determined by delay-enhanced MRI. The results proved that both strain components were able to distinguish between normal and infarct regions. Overall, the proposed framework was shown to be accurate, robust, and attractive for clinical practice, as it overcomes several limitations of a manual analysis.
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Affiliation(s)
- Pedro Morais
- Lab on Cardiovascular Imaging & Dynamics, Department of Cardiovascular Sciences, KULeuven-University of Leuven, Leuven, Belgium. ICVS/3B's-PT Government Associate Laboratory, Braga/Guimarães, Portugal. Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial, Faculdade de Engenharia, Universidade do Porto, Porto, Portugal
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Machine learning of the spatio-temporal characteristics of echocardiographic deformation curves for infarct classification. Int J Cardiovasc Imaging 2017; 33:1159-1167. [PMID: 28321681 DOI: 10.1007/s10554-017-1108-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2017] [Accepted: 03/03/2017] [Indexed: 10/19/2022]
Abstract
The aim of this study was to analyze the whole temporal profiles of the segmental deformation curves of the left ventricle (LV) and describe their interrelations to obtain more detailed information concerning global LV function in order to be able to identify abnormal changes in LV mechanics. The temporal characteristics of the segmental LV deformation curves were compactly described using an efficient decomposition into major patterns of variation through a statistical method, called Principal Component Analysis (PCA). In order to describe the spatial relations between the segmental traces, the PCA-derived temporal features of all LV segments were concatenated. The obtained set of features was then used to build an automatic classification system. The proposed methodology was applied to a group of 60 MRI-delayed enhancement confirmed infarct patients and 60 controls in order to detect myocardial infarction. An average classification accuracy of 87% with corresponding sensitivity and specificity rates of 89% and 85%, respectively was obtained by the proposed methodology applied on the strain rate curves. This classification performance was better than that obtained with the same methodology applied on the strain curves, reading of two expert cardiologists as well as comparative classification systems using only the spatial distribution of the end-systolic strain and peak-systolic strain rate values. This study shows the potential of machine learning in the field of cardiac deformation imaging where an efficient representation of the spatio-temporal characteristics of the segmental deformation curves allowed automatic classification of infarcted from control hearts with high accuracy.
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10
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Pedrosa J, Barbosa D, Heyde B, Schnell F, Rosner A, Claus P, D'hooge J. Left Ventricular Myocardial Segmentation in 3-D Ultrasound Recordings: Effect of Different Endocardial and Epicardial Coupling Strategies. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2017; 64:525-536. [PMID: 27992332 DOI: 10.1109/tuffc.2016.2638080] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Cardiac volume/function assessment remains a critical step in daily cardiology, and 3-D ultrasound plays an increasingly important role. Though development of automatic endocardial segmentation methods has received much attention, the same cannot be said about epicardial segmentation, in spite of the importance of full myocardial segmentation. In this paper, different ways of coupling the endocardial and epicardial segmentations are contrasted and compared with uncoupled segmentation. For this purpose, the B-spline explicit active surfaces framework was used; 27 3-D echocardiographic images were used to validate the different coupling strategies, which were compared with manual contouring of the endocardial and epicardial borders performed by an expert. It is shown that an independent segmentation of the endocardium followed by an epicardial segmentation coupled to the endocardium is the most advantageous. In this way, a framework for fully automatic 3-D myocardial segmentation is proposed using a novel coupling strategy.
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11
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Almeida N, Papachristidis A, Pearson P, Sarvari SI, Engvall J, Edvardsen T, Monaghan M, Gérard O, Samset E, D'hooge J. Left atrial volumetric assessment using a novel automated framework for 3D echocardiography: a multi-centre analysis. Eur Heart J Cardiovasc Imaging 2016; 18:1008-1015. [DOI: 10.1093/ehjci/jew166] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2016] [Accepted: 06/30/2016] [Indexed: 11/15/2022] Open
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Svalbring E, Fredriksson A, Eriksson J, Dyverfeldt P, Ebbers T, Bolger AF, Engvall J, Carlhäll CJ. Altered Diastolic Flow Patterns and Kinetic Energy in Subtle Left Ventricular Remodeling and Dysfunction Detected by 4D Flow MRI. PLoS One 2016; 11:e0161391. [PMID: 27532640 PMCID: PMC4988651 DOI: 10.1371/journal.pone.0161391] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2016] [Accepted: 08/04/2016] [Indexed: 01/24/2023] Open
Abstract
AIMS 4D flow magnetic resonance imaging (MRI) allows quantitative assessment of left ventricular (LV) function according to characteristics of the dynamic flow in the chamber. Marked abnormalities in flow components' volume and kinetic energy (KE) have previously been demonstrated in moderately dilated and depressed LV's compared to healthy subjects. We hypothesized that these 4D flow-based measures would detect even subtle LV dysfunction and remodeling. METHODS AND RESULTS We acquired 4D flow and morphological MRI data from 26 patients with chronic ischemic heart disease with New York Heart Association (NYHA) class I and II and with no to mild LV systolic dysfunction and remodeling, and from 10 healthy controls. A previously validated method was used to separate the LV end-diastolic volume (LVEDV) into functional components: direct flow, which passes directly to ejection, and non-ejecting flow, which remains in the LV for at least 1 cycle. The direct flow and non-ejecting flow proportions of end-diastolic volume and KE were assessed. The proportions of direct flow volume and KE fell with increasing LVEDV-index (LVEDVI) and LVESV-index (LVESVI) (direct flow volume r = -0.64 and r = -0.74, both P<0.001; direct flow KE r = -0.48, P = 0.013, and r = -0.56, P = 0.003). The proportions of non-ejecting flow volume and KE rose with increasing LVEDVI and LVESVI (non-ejecting flow volume: r = 0.67 and r = 0.76, both P<0.001; non-ejecting flow KE: r = 0.53, P = 0.005 and r = 0.52, P = 0.006). The proportion of direct flow volume correlated moderately to LVEF (r = 0.68, P < 0.001) and was higher in a sub-group of patients with LVEDVI >74 ml/m2 compared to patients with LVEDVI <74 ml/m2 and controls (both P<0.05). CONCLUSION Direct flow volume and KE proportions diminish with increased LV volumes, while non-ejecting flow proportions increase. A decrease in direct flow volume and KE at end-diastole proposes that alterations in these novel 4D flow-specific markers may detect LV dysfunction even in subtle or subclinical LV remodeling.
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Affiliation(s)
- Emil Svalbring
- Department of Medical and Health Sciences, Division of Cardiovascular Medicine, Linköping University, Linköping, Sweden
| | - Alexandru Fredriksson
- Department of Medical and Health Sciences, Division of Cardiovascular Medicine, Linköping University, Linköping, Sweden
| | - Jonatan Eriksson
- Department of Medical and Health Sciences, Division of Cardiovascular Medicine, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
| | - Petter Dyverfeldt
- Department of Medical and Health Sciences, Division of Cardiovascular Medicine, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
| | - Tino Ebbers
- Department of Medical and Health Sciences, Division of Cardiovascular Medicine, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
| | - Ann F Bolger
- Department of Medical and Health Sciences, Division of Cardiovascular Medicine, Linköping University, Linköping, Sweden
- Department of Medicine, University of California San Francisco, San Francisco, California, United States of America
| | - Jan Engvall
- Department of Medical and Health Sciences, Division of Cardiovascular Medicine, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
- Department of Clinical Physiology, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden
| | - Carl-Johan Carlhäll
- Department of Medical and Health Sciences, Division of Cardiovascular Medicine, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
- Department of Clinical Physiology, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden
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Andersson C, Kihlberg J, Ebbers T, Lindström L, Carlhäll CJ, Engvall JE. Phase-contrast MRI volume flow--a comparison of breath held and navigator based acquisitions. BMC Med Imaging 2016; 16:26. [PMID: 27021353 PMCID: PMC4809032 DOI: 10.1186/s12880-016-0128-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2015] [Accepted: 03/21/2016] [Indexed: 01/23/2023] Open
Abstract
BACKGROUND Magnetic Resonance Imaging (MRI) 2D phase-contrast flow measurement has been regarded as the gold standard in blood flow measurements and can be performed with free breathing or breath held techniques. We hypothesized that the accuracy of flow measurements obtained with segmented phase-contrast during breath holding, and in particular higher number of k-space segments, would be non-inferior compared to navigator phase-contrast. Volumes obtained from anatomic segmentation of cine MRI and Doppler echocardiography were used for additional reference. METHODS Forty patients, five women and 35 men, mean age 65 years (range 53-80), were randomly selected and consented to the study. All underwent EKG-gated cardiac MRI including breath hold cine, navigator based free-breathing phase-contrast MRI and breath hold phase-contrast MRI using k-space segmentation factors 3 and 5, as well as transthoracic echocardiography within 2 days. RESULTS In navigator based free-breathing phase-contrast flow, mean stroke volume and cardiac output were 79.7 ± 17.1 ml and 5071 ± 1192 ml/min, respectively. The duration of the acquisition was 50 ± 6 s. With k-space segmentation factor 3, the corresponding values were 77.7 ml ± 17.5 ml and 4979 ± 1211 ml/min (p = 0.15 vs navigator). The duration of the breath hold was 17 ± 2 s. K-space segmentation factor 5 gave mean stroke volume 77.9 ± 16.4 ml, cardiac output 5142 ± 1197 ml/min (p = 0.33 vs navigator), and breath hold time 11 ± 1 s. Anatomical segmentation of cine gave mean stroke volume and cardiac output 91.2 ± 20.8 ml and 5963 ± 1452 ml/min, respectively. Echocardiography was reliable in 20 of the 40 patients. The mean diameter of the left ventricular outflow tract was 20.7 ± 1.5 mm, stroke volume 78.3 ml ± 15.2 ml and cardiac output 5164 ± 1249 ml/min. CONCLUSIONS In forty consecutive patients with coronary heart disease, breath holding and segmented k-space sampling techniques for phase-contrast flow produced stroke volumes and cardiac outputs similar to those obtained with free-breathing navigator based phase-contrast MRI, using less time. The values obtained agreed fairly well with Doppler echocardiography while there was a larger difference when compared with anatomical volume determinations using SSFP (steady state free precession) cine MRI.
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Affiliation(s)
- Charlotta Andersson
- Center for Medical Image Science and Visualization, Linkoping University, SE-581 83, Linkoping, Sweden.,Department of Clinical Physiology, Linkoping University, SE-603 79, Norrkoping, Sweden
| | - Johan Kihlberg
- Center for Medical Image Science and Visualization, Linkoping University, SE-581 83, Linkoping, Sweden.,Department of Diagnostic Radiology, Linkoping University, SE-581 85, Linkoping, Sweden
| | - Tino Ebbers
- Center for Medical Image Science and Visualization, Linkoping University, SE-581 83, Linkoping, Sweden
| | - Lena Lindström
- Department of Clinical Physiology, Linkoping University, SE-603 79, Norrkoping, Sweden
| | - Carl-Johan Carlhäll
- Center for Medical Image Science and Visualization, Linkoping University, SE-581 83, Linkoping, Sweden.,Department of Medical and Health Sciences, Linkoping University, SE-581 83, Linkoping, Sweden.,Department of Clinical Physiology, Linkoping University, SE-581 85, Linkoping, Sweden
| | - Jan E Engvall
- Center for Medical Image Science and Visualization, Linkoping University, SE-581 83, Linkoping, Sweden. .,Department of Medical and Health Sciences, Linkoping University, SE-581 83, Linkoping, Sweden. .,Department of Clinical Physiology, Linkoping University, SE-581 85, Linkoping, Sweden.
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Queirós S, Barbosa D, Engvall J, Ebbers T, Nagel E, Sarvari SI, Claus P, Fonseca JC, Vilaça JL, D'hooge J. Multi-centre validation of an automatic algorithm for fast 4D myocardial segmentation in cine CMR datasets. Eur Heart J Cardiovasc Imaging 2015; 17:1118-27. [DOI: 10.1093/ehjci/jev247] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2015] [Accepted: 09/16/2015] [Indexed: 11/12/2022] Open
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15
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Kihlberg J, Haraldsson H, Sigfridsson A, Ebbers T, Engvall JE. Clinical experience of strain imaging using DENSE for detecting infarcted cardiac segments. J Cardiovasc Magn Reson 2015; 17:50. [PMID: 26104510 PMCID: PMC4478716 DOI: 10.1186/s12968-015-0155-8] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2015] [Accepted: 06/10/2015] [Indexed: 02/06/2023] Open
Abstract
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.
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Affiliation(s)
- Johan Kihlberg
- Department of Radiology and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
- Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
| | - Henrik Haraldsson
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
- Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
| | - Andreas Sigfridsson
- Department of Clinical Physiology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.
| | - Tino Ebbers
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
- Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
| | - Jan E Engvall
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
- Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
- Department of Clinical Physiology and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
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