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Govil S, Mauger C, Hegde S, Occleshaw CJ, Yu X, Perry JC, Young AA, Omens JH, McCulloch AD. Biventricular shape modes discriminate pulmonary valve replacement in tetralogy of Fallot better than imaging indices. Sci Rep 2023; 13:2335. [PMID: 36759522 PMCID: PMC9911768 DOI: 10.1038/s41598-023-28358-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 01/17/2023] [Indexed: 02/11/2023] Open
Abstract
Current indications for pulmonary valve replacement (PVR) in repaired tetralogy of Fallot (rTOF) rely on cardiovascular magnetic resonance (CMR) image-based indices but are inconsistently applied, lead to mixed outcomes, and remain debated. This study aimed to test the hypothesis that specific markers of biventricular shape may discriminate differences between rTOF patients who did and did not require subsequent PVR better than standard imaging indices. In this cross-sectional retrospective study, biventricular shape models were customized to CMR images from 84 rTOF patients. A statistical atlas of end-diastolic shape was constructed using principal component analysis. Multivariate regression was used to quantify shape mode and imaging index associations with subsequent intervention status (PVR, n = 48 vs. No-PVR, n = 36), while accounting for confounders. Clustering analysis was used to test the ability of the most significant shape modes and imaging indices to discriminate PVR status as evaluated by a Matthews correlation coefficient (MCC). Geometric strain analysis was also conducted to assess shape mode associations with systolic function. PVR status correlated significantly with shape modes associated with right ventricular (RV) apical dilation and left ventricular (LV) dilation (p < 0.01), RV basal bulging and LV conicity (p < 0.05), and pulmonary valve dilation (p < 0.01). PVR status also correlated significantly with RV ejection fraction (p < 0.05) and correlated marginally with LV end-systolic volume index (p < 0.07). Shape modes discriminated subsequent PVR better than standard imaging indices (MCC = 0.49 and MCC = 0.28, respectively) and were significantly associated with RV and LV radial systolic strain. Biventricular shape modes discriminated differences between patients who did and did not require subsequent PVR better than standard imaging indices in current use. These regional features of cardiac morphology may provide insight into adaptive vs. maladaptive types of structural remodeling and point toward an improved quantitative, patient-specific assessment tool for clinical use.
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Affiliation(s)
- Sachin Govil
- Department of Bioengineering, University of California San Diego, 9500 Gilman Drive, MC 0412, La Jolla, CA, 92093-0412, USA
| | - Charlène Mauger
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand.,Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Sanjeet Hegde
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.,Division of Cardiology, Rady Children's Hospital San Diego, San Diego, CA, USA
| | | | - Xiaoyang Yu
- Division of Cardiology, Rady Children's Hospital San Diego, San Diego, CA, USA
| | - James C Perry
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.,Division of Cardiology, Rady Children's Hospital San Diego, San Diego, CA, USA
| | - Alistair A Young
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand.,Department of Biomedical Engineering, King's College London, London, UK
| | - Jeffrey H Omens
- Department of Bioengineering, University of California San Diego, 9500 Gilman Drive, MC 0412, La Jolla, CA, 92093-0412, USA
| | - Andrew D McCulloch
- Department of Bioengineering, University of California San Diego, 9500 Gilman Drive, MC 0412, La Jolla, CA, 92093-0412, USA.
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Auger DA, Ghadimi S, Cai X, Reagan CE, Sun C, Abdi M, Cao JJ, Cheng JY, Ngai N, Scott AD, Ferreira PF, Oshinski JN, Emamifar N, Ennis DB, Loecher M, Liu ZQ, Croisille P, Viallon M, Bilchick KC, Epstein FH. Reproducibility of global and segmental myocardial strain using cine DENSE at 3 T: a multicenter cardiovascular magnetic resonance study in healthy subjects and patients with heart disease. J Cardiovasc Magn Reson 2022; 24:23. [PMID: 35369885 PMCID: PMC8978361 DOI: 10.1186/s12968-022-00851-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Accepted: 03/07/2022] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND While multiple cardiovascular magnetic resonance (CMR) methods provide excellent reproducibility of global circumferential and global longitudinal strain, achieving highly reproducible segmental strain is more challenging. Previous single-center studies have demonstrated excellent reproducibility of displacement encoding with stimulated echoes (DENSE) segmental circumferential strain. The present study evaluated the reproducibility of DENSE for measurement of whole-slice or global circumferential (Ecc), longitudinal (Ell) and radial (Err) strain, torsion, and segmental Ecc at multiple centers. METHODS Six centers participated and a total of 81 subjects were studied, including 60 healthy subjects and 21 patients with various types of heart disease. CMR utilized 3 T scanners, and cine DENSE images were acquired in three short-axis planes and in the four-chamber long-axis view. During one imaging session, each subject underwent two separate DENSE scans to assess inter-scan reproducibility. Each subject was taken out of the scanner and repositioned between the scans. Intra-user, inter-user-same-site, inter-user-different-site, and inter-user-Human-Deep-Learning (DL) comparisons assessed the reproducibility of different users analyzing the same data. Inter-scan comparisons assessed the reproducibility of DENSE from scan to scan. The reproducibility of whole-slice or global Ecc, Ell and Err, torsion, and segmental Ecc were quantified using Bland-Altman analysis, the coefficient of variation (CV), and the intraclass correlation coefficient (ICC). CV was considered excellent for CV ≤ 10%, good for 10% < CV ≤ 20%, fair for 20% < CV ≤ 40%, and poor for CV > 40. ICC values were considered excellent for ICC > 0.74, good for ICC 0.6 < ICC ≤ 0.74, fair for ICC 0.4 < ICC ≤ 0.59, poor for ICC < 0.4. RESULTS Based on CV and ICC, segmental Ecc provided excellent intra-user, inter-user-same-site, inter-user-different-site, inter-user-Human-DL reproducibility and good-excellent inter-scan reproducibility. Whole-slice Ecc and global Ell provided excellent intra-user, inter-user-same-site, inter-user-different-site, inter-user-Human-DL and inter-scan reproducibility. The reproducibility of torsion was good-excellent for all comparisons. For whole-slice Err, CV was in the fair-good range, and ICC was in the good-excellent range. CONCLUSIONS Multicenter data show that 3 T CMR DENSE provides highly reproducible whole-slice and segmental Ecc, global Ell, and torsion measurements in healthy subjects and heart disease patients.
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Affiliation(s)
- Daniel A. Auger
- Department of Biomedical Engineering, University of Virginia, Box 800759, Charlottesville, VA 22908 USA
| | - Sona. Ghadimi
- Department of Biomedical Engineering, University of Virginia, Box 800759, Charlottesville, VA 22908 USA
| | | | - Claire E. Reagan
- Department of Biomedical Engineering, University of Virginia, Box 800759, Charlottesville, VA 22908 USA
| | - Changyu Sun
- Department of Biomedical Engineering, University of Virginia, Box 800759, Charlottesville, VA 22908 USA
| | - Mohamad Abdi
- Department of Biomedical Engineering, University of Virginia, Box 800759, Charlottesville, VA 22908 USA
| | - Jie Jane Cao
- St. Francis Hospital, The Heart Center, Long Island, NY USA
| | | | - Nora Ngai
- St. Francis Hospital, The Heart Center, Long Island, NY USA
| | - Andrew D. Scott
- Cardiovascular Magnetic Resonance Unit, The Royal Brompton Hospital and National Heart and Lung Institute, Imperial College London, London, UK
| | - Pedro F. Ferreira
- Cardiovascular Magnetic Resonance Unit, The Royal Brompton Hospital and National Heart and Lung Institute, Imperial College London, London, UK
| | - John N. Oshinski
- Department of Radiology & Imaging Sciences and Biomedical Engineering, Emory University, Atlanta, Georgia
| | - Nick Emamifar
- Department of Radiology & Imaging Sciences and Biomedical Engineering, Emory University, Atlanta, Georgia
| | - Daniel B. Ennis
- Department of Radiology, Stanford University, Stanford, CA USA
| | - Michael Loecher
- Department of Radiology, Stanford University, Stanford, CA USA
| | - Zhan-Qiu Liu
- Department of Radiology, Stanford University, Stanford, CA USA
| | - Pierre Croisille
- University of Lyon, UJM-Saint-Etienne, INSA, CNRS UMR 5520, INSERM U1206, CREATIS, Saint-Etienne, France
- Department of Radiology, University Hospital Saint-Etienne, Saint-Etienne, France
| | - Magalie Viallon
- University of Lyon, UJM-Saint-Etienne, INSA, CNRS UMR 5520, INSERM U1206, CREATIS, Saint-Etienne, France
| | - Kenneth C. Bilchick
- Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, VA USA
| | - Frederick H. Epstein
- Department of Biomedical Engineering, University of Virginia, Box 800759, Charlottesville, VA 22908 USA
- Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, VA USA
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Mauger CA, Govil S, Chabiniok R, Gilbert K, Hegde S, Hussain T, McCulloch AD, Occleshaw CJ, Omens J, Perry JC, Pushparajah K, Suinesiaputra A, Zhong L, Young AA. Right-left ventricular shape variations in tetralogy of Fallot: associations with pulmonary regurgitation. J Cardiovasc Magn Reson 2021; 23:105. [PMID: 34615541 PMCID: PMC8496085 DOI: 10.1186/s12968-021-00780-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 05/26/2021] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Relationships between right ventricular (RV) and left ventricular (LV) shape and function may be useful in determining optimal timing for pulmonary valve replacement in patients with repaired tetralogy of Fallot (rTOF). However, these are multivariate and difficult to quantify. We aimed to quantify variations in biventricular shape associated with pulmonary regurgitant volume (PRV) in rTOF using a biventricular atlas. METHODS In this cross-sectional retrospective study, a biventricular shape model was customized to cardiovascular magnetic resonance (CMR) images from 88 rTOF patients (median age 16, inter-quartile range 11.8-24.3 years). Morphometric scores quantifying biventricular shape at end-diastole and end-systole were computed using principal component analysis. Multivariate linear regression was used to quantify biventricular shape associations with PRV, corrected for age, sex, height, and weight. Regional associations were confirmed by univariate correlations with distances and angles computed from the models, as well as global systolic strains computed from changes in arc length from end-diastole to end-systole. RESULTS PRV was significantly associated with 5 biventricular morphometric scores, independent of covariates, and accounted for 12.3% of total shape variation (p < 0.05). Increasing PRV was associated with RV dilation and basal bulging, in conjunction with decreased LV septal-lateral dimension (LV flattening) and systolic septal motion towards the RV (all p < 0.05). Increased global RV radial, longitudinal, circumferential and LV radial systolic strains were significantly associated with increased PRV (all p < 0.05). CONCLUSION A biventricular atlas of rTOF patients quantified multivariate relationships between left-right ventricular morphometry and wall motion with pulmonary regurgitation. Regional RV dilation, LV reduction, LV septal-lateral flattening and increased RV strain were all associated with increased pulmonary regurgitant volume. Morphometric scores provide simple metrics linking mechanisms for structural and functional alteration with important clinical indices.
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Affiliation(s)
- Charlène A. Mauger
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Sachin Govil
- University of California San Diego, La Jolla, CA USA
| | - Radomir Chabiniok
- University of Texas Southwestern Medical Centre, Dallas, TX USA
- Inria, Palaiseau, France
- LMS, École Polytechnique, CNRS, Institut Polytechnique de Paris, Palaiseau, France
- Department of Mathematics, Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Kathleen Gilbert
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Sanjeet Hegde
- University of California San Diego, La Jolla, CA USA
- Division of Cardiology, Rady Children’s Hospital, San Diego, CA USA
| | - Tarique Hussain
- University of Texas Southwestern Medical Centre, Dallas, TX USA
| | | | | | - Jeffrey Omens
- University of California San Diego, La Jolla, CA USA
| | - James C. Perry
- University of California San Diego, La Jolla, CA USA
- Division of Cardiology, Rady Children’s Hospital, San Diego, CA USA
| | | | | | - Liang Zhong
- National Heart Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Alistair A. Young
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
- Department of Biomedical Engineering, King’s College London, London, UK
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Ferdian E, Suinesiaputra A, Fung K, Aung N, Lukaschuk E, Barutcu A, Maclean E, Paiva J, Piechnik SK, Neubauer S, Petersen SE, Young AA. Fully Automated Myocardial Strain Estimation from Cardiovascular MRI-tagged Images Using a Deep Learning Framework in the UK Biobank. Radiol Cardiothorac Imaging 2020; 2:e190032. [PMID: 32715298 PMCID: PMC7051160 DOI: 10.1148/ryct.2020190032] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 07/19/2019] [Accepted: 08/21/2019] [Indexed: 11/25/2022]
Abstract
PURPOSE To demonstrate the feasibility and performance of a fully automated deep learning framework to estimate myocardial strain from short-axis cardiac MRI-tagged images. MATERIALS AND METHODS In this retrospective cross-sectional study, 4508 cases from the U.K. Biobank were split randomly into 3244 training cases, 812 validation cases, and 452 test cases. Ground truth myocardial landmarks were defined and tracked by manual initialization and correction of deformable image registration using previously validated software with five readers. The fully automatic framework consisted of (a) a convolutional neural network (CNN) for localization and (b) a combination of a recurrent neural network (RNN) and a CNN to detect and track the myocardial landmarks through the image sequence for each slice. Radial and circumferential strain were then calculated from the motion of the landmarks and averaged on a slice basis. RESULTS Within the test set, myocardial end-systolic circumferential Green strain errors were -0.001 ± 0.025, -0.001 ± 0.021, and 0.004 ± 0.035 in the basal, mid-, and apical slices, respectively (mean ± standard deviation of differences between predicted and manual strain). The framework reproduced significant reductions in circumferential strain in participants with diabetes, hypertensive participants, and participants with a previous heart attack. Typical processing time was approximately 260 frames (approximately 13 slices) per second on a GPU with 12 GB RAM compared with 6-8 minutes per slice for the manual analysis. CONCLUSION The fully automated combined RNN and CNN framework for analysis of myocardial strain enabled unbiased strain evaluation in a high-throughput workflow, with similar ability to distinguish impairment due to diabetes, hypertension, and previous heart attack.Published under a CC BY 4.0 license. Supplemental material is available for this article.
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Affiliation(s)
- Edward Ferdian
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Avan Suinesiaputra
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Kenneth Fung
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Nay Aung
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Elena Lukaschuk
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Ahmet Barutcu
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Edd Maclean
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Jose Paiva
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Stefan K. Piechnik
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Stefan Neubauer
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Steffen E. Petersen
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Alistair A. Young
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
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Bilchick KC, Auger DA, Abdishektaei M, Mathew R, Sohn MW, Cai X, Sun C, Narayan A, Malhotra R, Darby A, Mangrum JM, Mehta N, Ferguson J, Mazimba S, Mason PK, Kramer CM, Levy WC, Epstein FH. CMR DENSE and the Seattle Heart Failure Model Inform Survival and Arrhythmia Risk After CRT. JACC Cardiovasc Imaging 2019; 13:924-936. [PMID: 31864974 DOI: 10.1016/j.jcmg.2019.10.017] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Revised: 09/23/2019] [Accepted: 10/10/2019] [Indexed: 11/30/2022]
Abstract
OBJECTIVES This study sought to determine if combining the Seattle Heart Failure Model (SHFM-D) and cardiac magnetic resonance (CMR) provides complementary prognostic data for patients with cardiac resynchronization therapy (CRT) defibrillators. BACKGROUND The SHFM-D is among the most widely used risk stratification models for overall survival in patients with heart failure and implantable cardioverter-defibrillators (ICDs), and CMR provides highly detailed information regarding cardiac structure and function. METHODS CMR Displacement Encoding with Stimulated Echoes (DENSE) strain imaging was used to generate the circumferential uniformity ratio estimate with singular value decomposition (CURE-SVD) circumferential strain dyssynchrony parameter, and the SHFM-D was determined from clinical parameters. Multivariable Cox proportional hazards regression was used to determine adjusted hazard ratios and time-dependent areas under the curve for the primary endpoint of death, heart transplantation, left ventricular assist device, or appropriate ICD therapies. RESULTS The cohort consisted of 100 patients (65.5 [interquartile range 57.7 to 72.7] years; 29% female), of whom 47% had the primary clinical endpoint and 18% had appropriate ICD therapies during a median follow-up of 5.3 years. CURE-SVD and the SHFM-D were independently associated with the primary endpoint (SHFM-D: hazard ratio: 1.47/SD; 95% confidence interval: 1.06 to 2.03; p = 0.02) (CURE-SVD: hazard ratio: 1.54/SD; 95% confidence interval: 1.12 to 2.11; p = 0.009). Furthermore, a favorable prognostic group (Group A, with CURE-SVD <0.60 and SHFM-D <0.70) comprising approximately one-third of the patients had a very low rate of appropriate ICD therapies (1.5% per year) and a greater (90%) 4-year survival compared with Group B (CURE-SVD ≥0.60 or SHFM-D ≥0.70) patients (p = 0.02). CURE-SVD with DENSE had a stronger correlation with CRT response (r = -0.57; p < 0.0001) than CURE-SVD with feature tracking (r = -0.28; p = 0.004). CONCLUSIONS A combined approach to risk stratification using CMR DENSE strain imaging and a widely used clinical risk model, the SHFM-D, proved to be effective in this cohort of patients referred for CRT defibrillators. The combined use of CMR and clinical risk models represents a promising and novel paradigm to inform prognosis and device selection in the future.
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Affiliation(s)
- Kenneth C Bilchick
- Department of Medicine, University of Virginia Health System, Charlottesville, Virginia.
| | - Daniel A Auger
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia
| | - Mohammad Abdishektaei
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia
| | - Roshin Mathew
- Department of Medicine, University of Virginia Health System, Charlottesville, Virginia
| | - Min-Woong Sohn
- Department of Public Health Sciences, University of Virginia Health System, Charlottesville, Virginia
| | - Xiaoying Cai
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia
| | - Changyu Sun
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia
| | - Aditya Narayan
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia
| | - Rohit Malhotra
- Department of Medicine, University of Virginia Health System, Charlottesville, Virginia
| | - Andrew Darby
- Department of Medicine, University of Virginia Health System, Charlottesville, Virginia
| | - J Michael Mangrum
- Department of Medicine, University of Virginia Health System, Charlottesville, Virginia
| | - Nishaki Mehta
- Department of Medicine, University of Virginia Health System, Charlottesville, Virginia
| | - John Ferguson
- Department of Medicine, University of Virginia Health System, Charlottesville, Virginia
| | - Sula Mazimba
- Department of Medicine, University of Virginia Health System, Charlottesville, Virginia
| | - Pamela K Mason
- Department of Medicine, University of Virginia Health System, Charlottesville, Virginia
| | - Christopher M Kramer
- Department of Medicine, University of Virginia Health System, Charlottesville, Virginia; Department of Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia
| | - Wayne C Levy
- Department of Medicine, University of Washington, Seattle, Washington
| | - Frederick H Epstein
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia; Department of Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia
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6
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Tayal U, Wage R, Ferreira PF, Nielles-Vallespin S, Epstein FH, Auger D, Zhong X, Pennell DJ, Firmin DN, Scott AD, Prasad SK. The feasibility of a novel limited field of view spiral cine DENSE sequence to assess myocardial strain in dilated cardiomyopathy. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2019; 32:317-329. [PMID: 30694416 PMCID: PMC6525145 DOI: 10.1007/s10334-019-00735-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/04/2018] [Revised: 12/21/2018] [Accepted: 01/03/2019] [Indexed: 12/25/2022]
Abstract
Objective Develop an accelerated cine displacement encoding with stimulated echoes (DENSE) cardiovascular magnetic resonance (CMR) sequence to enable clinically feasible myocardial strain evaluation in patients with dilated cardiomyopathy (DCM). Materials and methods A spiral cine DENSE sequence was modified by limiting the field of view in two dimensions using in-plane slice-selective pulses in the stimulated echo. This reduced breath hold duration from 20RR to 14RR intervals. Following phantom and pilot studies, the feasibility of the sequence to assess peak radial, circumferential, and longitudinal strain was tested in control subjects (n = 18) and then applied in DCM patients (n = 29). Results DENSE acquisition was possible in all participants. Elements of the data were not analysable in 1 control (6%) and 4 DCM r(14%) subjects due to off-resonance or susceptibility artefacts and low signal-to-noise ratio. Peak radial, circumferential, short-axis contour strain and longitudinal strain was reduced in DCM patients (p < 0.001 vs. controls) and strain measurements correlated with left ventricular ejection fraction (with circumferential strain r = − 0.79, p < 0.0001; with vertical long-axis strain r = − 0.76, p < 0.0001). All strain measurements had good inter-observer agreement (ICC > 0.80), except peak radial strain. Discussion We demonstrate the feasibility of CMR strain assessment in healthy controls and DCM patients using an accelerated cine DENSE technique. This may facilitate integration of strain assessment into routine CMR studies. Electronic supplementary material The online version of this article (10.1007/s10334-019-00735-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Upasana Tayal
- National Heart Lung Institute, Imperial College London, London, UK
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, London, SW3 6NP UK
| | - Ricardo Wage
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, London, SW3 6NP UK
| | - Pedro Filipe Ferreira
- National Heart Lung Institute, Imperial College London, London, UK
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, London, SW3 6NP UK
| | - Sonia Nielles-Vallespin
- National Heart Lung Institute, Imperial College London, London, UK
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, London, SW3 6NP UK
- National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD USA
| | | | - Daniel Auger
- Biomedical Engineering, University of Virginia, Charlottesville, VA USA
| | | | - Dudley John Pennell
- National Heart Lung Institute, Imperial College London, London, UK
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, London, SW3 6NP UK
| | - David Nigel Firmin
- National Heart Lung Institute, Imperial College London, London, UK
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, London, SW3 6NP UK
| | - Andrew David Scott
- National Heart Lung Institute, Imperial College London, London, UK
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, London, SW3 6NP UK
| | - Sanjay Kumar Prasad
- National Heart Lung Institute, Imperial College London, London, UK
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, London, SW3 6NP UK
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7
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Mangion K, Carrick D, Clerfond G, Rush C, McComb C, Oldroyd KG, Petrie MC, Eteiba H, Lindsay M, McEntegart M, Hood S, Watkins S, Davie A, Auger DA, Zhong X, Epstein FH, Haig CE, Berry C. Predictors of segmental myocardial functional recovery in patients after an acute ST-Elevation myocardial infarction. Eur J Radiol 2019; 112:121-129. [PMID: 30777200 PMCID: PMC6390173 DOI: 10.1016/j.ejrad.2019.01.010] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2018] [Revised: 01/08/2019] [Accepted: 01/12/2019] [Indexed: 01/28/2023]
Abstract
Objective We hypothesized that Displacement Encoding with Stimulated Echoes (DENSE) and feature-tracking derived circumferential strain would provide incremental prognostic value over the extent of infarction for recovery of segmental myocardial function. Methods Two hundred and sixty-one patients (mean age 59 years, 73% male) underwent MRI 2 days post-ST elevation myocardial infarction (STEMI) and 241 (92%) underwent repeat imaging 6 months later. The MRI protocol included cine, 2D-cine DENSE, T2 mapping and late enhancement. Wall motion scoring was assessed by 2-blinded observers and adjudicated by a third. (WMS: 1=normal, 2=hypokinetic, 3=akinetic, 4=dyskinetic). WMS improvement was defined as a decrease in WMS ≥ 1, and normalization where WMS = 1 on follow-up. Segmental circumferential strain was derived utilizing DENSE and feature-tracking. A generalized linear mixed model with random effect of subject was constructed and used to account for repeated sampling when investigating predictors of segmental myocardial improvement or normalization Results At baseline and follow-up, 1416 segments had evaluable data for all parameters. Circumferential strain by DENSE (p < 0.001) and feature-tracking (p < 0.001), extent of oedema (p < 0.001), infarct size (p < 0.001), and microvascular obstruction (p < 0.001) were associates of both improvement and normalization of WMS. Circumferential strain provided incremental predictive value even after accounting for infarct size, extent of oedema and microvascular obstruction, for segmental improvement (DENSE: odds ratio, 95% confidence intervals: 1.08 per −1% peak strain, 1.05–1.12, p < 0.001, feature-tracking: odds ratio, 95% confidence intervals: 1.05 per −1% peak strain, 1.03–1.07, p < 0.001) and segmental normalization (DENSE: 1.08 per −1% peak strain, 1.04–1.12, p < 0.001, feature-tracking: 1.06 per −1% peak strain, 1.04–1.08, p < 0.001). Conclusions Circumferential strain provides incremental prognostic value over segmental infarct size in patients post STEMI for predicting segmental improvement or normalization by wall-motion scoring.
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Affiliation(s)
- Kenneth Mangion
- British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, UK; West of Scotland Heart and Lung Centre, Golden Jubilee National Hospital, Clydebank, UK
| | - David Carrick
- British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, UK; West of Scotland Heart and Lung Centre, Golden Jubilee National Hospital, Clydebank, UK
| | - Guillaume Clerfond
- British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, UK
| | - Christopher Rush
- British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, UK; West of Scotland Heart and Lung Centre, Golden Jubilee National Hospital, Clydebank, UK
| | - Christie McComb
- British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, UK; Clinical Physics, NHS Greater Glasgow and Clyde, Glasgow, UK
| | - Keith G Oldroyd
- West of Scotland Heart and Lung Centre, Golden Jubilee National Hospital, Clydebank, UK
| | - Mark C Petrie
- British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, UK; West of Scotland Heart and Lung Centre, Golden Jubilee National Hospital, Clydebank, UK
| | - Hany Eteiba
- West of Scotland Heart and Lung Centre, Golden Jubilee National Hospital, Clydebank, UK
| | - Mitchell Lindsay
- West of Scotland Heart and Lung Centre, Golden Jubilee National Hospital, Clydebank, UK
| | - Margaret McEntegart
- West of Scotland Heart and Lung Centre, Golden Jubilee National Hospital, Clydebank, UK
| | - Stuart Hood
- West of Scotland Heart and Lung Centre, Golden Jubilee National Hospital, Clydebank, UK
| | - Stuart Watkins
- West of Scotland Heart and Lung Centre, Golden Jubilee National Hospital, Clydebank, UK
| | - Andrew Davie
- West of Scotland Heart and Lung Centre, Golden Jubilee National Hospital, Clydebank, UK
| | - Daniel A Auger
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
| | - Xiaodong Zhong
- MR R&D Collaborations, Siemens Healthcare, Los Angeles, CA, USA
| | - Frederick H Epstein
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
| | - Caroline E Haig
- Robertson Centre for Biostatistics, University of Glasgow, UK
| | - Colin Berry
- British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, UK; West of Scotland Heart and Lung Centre, Golden Jubilee National Hospital, Clydebank, UK.
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8
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Gho JMIH, van Es R, van Slochteren FJ, Jansen Of Lorkeers SJ, Hauer AJ, van Oorschot JWM, Doevendans PA, Leiner T, Vink A, Asselbergs FW, Chamuleau SAJ. A systematic comparison of cardiovascular magnetic resonance and high resolution histological fibrosis quantification in a chronic porcine infarct model. Int J Cardiovasc Imaging 2017; 33:1797-1807. [PMID: 28616762 PMCID: PMC5682871 DOI: 10.1007/s10554-017-1187-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2017] [Accepted: 06/05/2017] [Indexed: 10/26/2022]
Abstract
The noninvasive reference standard for myocardial fibrosis detection on cardiovascular magnetic resonance imaging (CMR) is late gadolinium enhancement (LGE). Currently there is no consensus on the preferred method for LGE quantification. Moreover myocardial wall thickening (WT) and strain are measures of regional deformation and function. The aim of this research was to systematically compare in vivo CMR parameters, such as LGE, WT and strain, with histological fibrosis quantification. Eight weeks after 90 min ischemia/reperfusion of the LAD artery, 16 pigs underwent in vivo Cine and LGE CMR. Histological sections from transverse heart slices were digitally analysed for fibrosis quantification. Mean fibrosis percentage of analysed sections was related to the different CMR techniques (using segmentation or feature tracking software) for each slice using a linear mixed model analysis. The full width at half maximum (FWHM) technique for quantification of LGE yielded the highest R2 of 60%. Cine derived myocardial WT explained 16-36% of the histological myocardial fibrosis. The peak circumferential and radial strain measured by feature tracking could explain 15 and 10% of the variance of myocardial fibrosis, respectively. The used method to systematically compare CMR image data with digital histological images is novel and feasible. Myocardial WT and strain were only modestly related with the amount of fibrosis. The fully automatic FWHM analysis technique is the preferred method to detect myocardial fibrosis.
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Affiliation(s)
- Johannes M I H Gho
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Room E03.511, P.O. Box 85500, 3508 GA, Utrecht, The Netherlands
| | - René van Es
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Room E03.511, P.O. Box 85500, 3508 GA, Utrecht, The Netherlands.
| | | | - Sanne J Jansen Of Lorkeers
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Room E03.511, P.O. Box 85500, 3508 GA, Utrecht, The Netherlands
| | - Allard J Hauer
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Room E03.511, P.O. Box 85500, 3508 GA, Utrecht, The Netherlands
| | - Joep W M van Oorschot
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Pieter A Doevendans
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Room E03.511, P.O. Box 85500, 3508 GA, Utrecht, The Netherlands
| | - Tim Leiner
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Aryan Vink
- Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Folkert W Asselbergs
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Room E03.511, P.O. Box 85500, 3508 GA, Utrecht, The Netherlands
- Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, Utrecht, The Netherlands
- Faculty of Population Health Sciences, Institute of Cardiovascular Science, University College London, London, UK
| | - Steven A J Chamuleau
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Room E03.511, P.O. Box 85500, 3508 GA, Utrecht, The Netherlands
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9
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Mangion K, McComb C, Auger DA, Epstein FH, Berry C. Magnetic Resonance Imaging of Myocardial Strain After Acute ST-Segment-Elevation Myocardial Infarction: A Systematic Review. Circ Cardiovasc Imaging 2017; 10:CIRCIMAGING.117.006498. [PMID: 28733364 DOI: 10.1161/circimaging.117.006498] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The purpose of this systematic review is to provide a clinically relevant, disease-based perspective on myocardial strain imaging in patients with acute myocardial infarction or stable ischemic heart disease. Cardiac magnetic resonance imaging uniquely integrates myocardial function with pathology. Therefore, this review focuses on strain imaging with cardiac magnetic resonance. We have specifically considered the relationships between left ventricular (LV) strain, infarct pathologies, and their associations with prognosis. A comprehensive literature review was conducted in accordance with the PRISMA guidelines. Publications were identified that (1) described the relationship between strain and infarct pathologies, (2) assessed the relationship between strain and subsequent LV outcomes, and (3) assessed the relationship between strain and health outcomes. In patients with acute myocardial infarction, circumferential strain predicts the recovery of LV systolic function in the longer term. The prognostic value of longitudinal strain is less certain. Strain differentiates between infarcted versus noninfarcted myocardium, even in patients with stable ischemic heart disease with preserved LV ejection fraction. Strain recovery is impaired in infarcted segments with intramyocardial hemorrhage or microvascular obstruction. There are practical limitations to measuring strain with cardiac magnetic resonance in the acute setting, and knowledge gaps, including the lack of data showing incremental value in clinical practice. Critically, studies of cardiac magnetic resonance strain imaging in patients with ischemic heart disease have been limited by sample size and design. Strain imaging has potential as a tool to assess for early or subclinical changes in LV function, and strain is now being included as a surrogate measure of outcome in therapeutic trials.
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Affiliation(s)
- Kenneth Mangion
- From the British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, United Kingdom (K.M., C.M., C.B.); Department of Clinical Physics, NHS Greater Glasgow and Clyde, United Kingdom (C.M.); and Department of Biomedical Engineering, University of Virginia, Charlottesville (D.A.A., F.H.E.)
| | - Christie McComb
- From the British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, United Kingdom (K.M., C.M., C.B.); Department of Clinical Physics, NHS Greater Glasgow and Clyde, United Kingdom (C.M.); and Department of Biomedical Engineering, University of Virginia, Charlottesville (D.A.A., F.H.E.)
| | - Daniel A Auger
- From the British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, United Kingdom (K.M., C.M., C.B.); Department of Clinical Physics, NHS Greater Glasgow and Clyde, United Kingdom (C.M.); and Department of Biomedical Engineering, University of Virginia, Charlottesville (D.A.A., F.H.E.)
| | - Frederick H Epstein
- From the British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, United Kingdom (K.M., C.M., C.B.); Department of Clinical Physics, NHS Greater Glasgow and Clyde, United Kingdom (C.M.); and Department of Biomedical Engineering, University of Virginia, Charlottesville (D.A.A., F.H.E.)
| | - Colin Berry
- From the British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, United Kingdom (K.M., C.M., C.B.); Department of Clinical Physics, NHS Greater Glasgow and Clyde, United Kingdom (C.M.); and Department of Biomedical Engineering, University of Virginia, Charlottesville (D.A.A., F.H.E.).
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10
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Schrauben EM, Cowan BR, Greiser A, Young AA. Left ventricular function and regional strain with subtly-tagged steady-state free precession feature tracking. J Magn Reson Imaging 2017; 47:787-797. [PMID: 28722247 DOI: 10.1002/jmri.25819] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2017] [Accepted: 07/06/2017] [Indexed: 11/11/2022] Open
Abstract
PURPOSE To provide regional strain and ventricular volume from a single acquisition, using subtly tagged steady-state free precession (SubTag SSFP) feature tracking. MATERIALS AND METHODS The effects on regional strain of tag strength in gradient recalled echo (GRE) tagging, flip angle in untagged balanced SSFP, and both in SubTag SSFP were examined in the mid left ventricle of 15 healthy volunteers at 3T. Optimal parameters were determined from varying both tag strength and SSFP flip angle using full tag saturation GRE as the reference standard. SubTag SSFP was acquired in 15 additional healthy volunteers for whole-heart volume and strain assessment using the optimized parameters. Values measured by two image analysts were compared to clinical reference standards from untagged SSFP (volumes) and GRE tagging (strains). RESULTS Regional strain accuracy was maintained with decreasing total tagging flip angle (β); less than 3% differences for β ≥ 26°. For untagged SSFP flip angle (α), whole-wall strain differences became statistically significant when α < 40°. A SubTag SSFP acquisition with α = 40° and β = 46° showed the best combination of tagging strength, blood-myocardial contrast, and tag persistence at end-systole for regional strain estimation. SubTag SSFP also showed excellent agreement with untagged SSFP for volumetrics (percent difference: end-diastolic volume = 0.6%, end-systolic volume = 0.4%, stroke volume = 1.2%, ejection fraction = 0.6%, mass = 1.1%). CONCLUSION Feature tracking for regional myocardial strain assessment is dependent on image features, mainly the tag strength, persistence, and image contrast. SubTag SSFP balances these criteria to provide accurate regional strain and volumetric assessment in a single acquisition. LEVEL OF EVIDENCE 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2018;47:787-797.
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Affiliation(s)
- Eric M Schrauben
- Translational Medicine, the Hospital for Sick Children, Toronto, Canada
| | - Brett R Cowan
- Department of Anatomy with Radiology, University of Auckland, Auckland, New Zealand
| | | | - Alistair A Young
- Department of Anatomy with Radiology, University of Auckland, Auckland, New Zealand
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11
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Auger DA, Bilchick KC, Gonzalez JA, Cui SX, Holmes JW, Kramer CM, Salerno M, Epstein FH. Imaging left-ventricular mechanical activation in heart failure patients using cine DENSE MRI: Validation and implications for cardiac resynchronization therapy. J Magn Reson Imaging 2017; 46:887-896. [PMID: 28067978 DOI: 10.1002/jmri.25613] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2016] [Revised: 12/09/2016] [Accepted: 12/10/2016] [Indexed: 11/06/2022] Open
Abstract
PURPOSE To image late mechanical activation and identify effective left-ventricular (LV) pacing sites for cardiac resynchronization therapy (CRT). There is variability in defining mechanical activation time, with some studies using the time to peak strain (TPS) and some using the time to the onset of circumferential shortening (TOS). We developed improved methods for imaging mechanical activation and evaluated them in heart failure (HF) patients undergoing CRT. MATERIALS AND METHODS We applied active contours to cine displacement encoding with stimulated echoes (DENSE) strain images to detect TOS. Six healthy volunteers underwent magnetic resonance imaging (MRI) at 1.5T, and 50 patients underwent pre-CRT MRI (strain, scar, volumes) and echocardiography, assessment of the electrical activation time (Q-LV) at the LV pacing site, and echocardiography assessment of LV reverse remodeling 6 months after CRT. TPS at the LV pacing site was also measured by DENSE. RESULTS The latest TOS was greater in HF patients vs. healthy subjects (112 ± 28 msec vs. 61 ± 7 msec, P < 0.01). The correlation between TOS and Q-LV was strong (r > 0.75; P < 0.001) and better than between TPS and Q-LV (r < 0.62; P ≥ 0.006). Twenty-three of 50 patients had the latest activating segment in a region other than the mid-ventricular lateral wall, the most common site for the CRT LV lead. Using a multivariable model, TOS/QRS was significantly associated with LV reverse remodeling even after adjustment for overall dyssynchrony and scar (P < 0.05), whereas TPS was not (P = 0.49). CONCLUSION Late activation by cine DENSE TOS analysis is associated with improved LV reverse remodeling with CRT and deserves further study as a tool to achieve optimal LV lead placement in CRT. LEVEL OF EVIDENCE 1 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:887-896.
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Affiliation(s)
- Daniel A Auger
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Kenneth C Bilchick
- Medicine/Cardiology/Electrophysiology, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Jorge A Gonzalez
- Medicine/Cardiology/Electrophysiology, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Sophia X Cui
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Jeffrey W Holmes
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia, USA.,Medicine/Cardiology/Electrophysiology, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Christopher M Kramer
- Medicine/Cardiology/Electrophysiology, University of Virginia Health System, Charlottesville, Virginia, USA.,Radiology/Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Michael Salerno
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia, USA.,Medicine/Cardiology/Electrophysiology, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Frederick H Epstein
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia, USA.,Radiology/Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
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12
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Gao B, Liu W, Wang L, Liu Z, Croisille P, Delachartre P, Clarysse P. Estimation of cardiac motion in cine-MRI sequences by correlation transform optical flow of monogenic features distance. Phys Med Biol 2016; 61:8640-8663. [DOI: 10.1088/1361-6560/61/24/8640] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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13
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Langton JEN, Lam HI, Cowan BR, Occleshaw CJ, Gabriel R, Lowe B, Lydiard S, Greiser A, Schmidt M, Young AA. Estimation of myocardial strain from non-rigid registration and highly accelerated cine CMR. Int J Cardiovasc Imaging 2016; 33:101-107. [PMID: 27624468 DOI: 10.1007/s10554-016-0978-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2016] [Accepted: 09/08/2016] [Indexed: 12/01/2022]
Abstract
Sparsely sampled cardiac cine accelerated acquisitions show promise for faster evaluation of left-ventricular function. Myocardial strain estimation using image feature tracking methods is also becoming widespread. However, it is not known whether highly accelerated acquisitions also provide reliable feature tracking strain estimates. Twenty patients and twenty healthy volunteers were imaged with conventional 14-beat/slice cine acquisition (STD), 4× accelerated 4-beat/slice acquisition with iterative reconstruction (R4), and a 9.2× accelerated 2-beat/slice real-time acquisition with sparse sampling and iterative reconstruction (R9.2). Radial and circumferential strains were calculated using non-rigid registration in the mid-ventricle short-axis slice and inter-observer errors were evaluated. Consistency was assessed using intra-class correlation coefficients (ICC) and bias with Bland-Altman analysis. Peak circumferential strain magnitude was highly consistent between STD and R4 and R9.2 (ICC = 0.876 and 0.884, respectively). Average bias was -1.7 ± 2.0 %, p < 0.001, for R4 and -2.7 ± 1.9 %, p < 0.001 for R9.2. Peak radial strain was also highly consistent (ICC = 0.829 and 0.785, respectively), with average bias -11.2 ± 18.4 %, p < 0.001, for R4 and -15.0 ± 21.2 %, p < 0.001 for R9.2. STD circumferential strain could be predicted by linear regression from R9.2 with an R2 of 0.82 and a root mean squared error of 1.8 %. Similarly, radial strain could be predicted with an R2 of 0.67 and a root mean squared error of 21.3 %. Inter-observer errors were not significantly different between methods, except for peak circumferential strain R9.2 (1.1 ± 1.9 %) versus STD (0.3 ± 1.0 %), p = 0.011. Although small systematic differences were observed in strain, these were highly consistent with standard acquisitions, suggesting that accelerated myocardial strain is feasible and reliable in patients who require short acquisition durations.
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Affiliation(s)
| | - Hoi-Ieng Lam
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
| | - Brett R Cowan
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
| | | | - Ruvin Gabriel
- Auckland District Health Board, Auckland, New Zealand
| | - Boris Lowe
- Auckland District Health Board, Auckland, New Zealand
| | | | | | | | - Alistair A Young
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand.
- Department of Anatomy with Radiology, Faculty of Medical and Health Sciences, University of Auckland, 85 Park Road, Auckland, 1142, New Zealand.
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