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Amoni M, Ingelaere S, Moeyersons J, Wets D, Tanushi A, Van Huffel S, Varon C, Sipido K, Claus P, Willems R. Regional beat-to-beat variability of repolarization increases during ischemia and predicts imminent arrhythmias in a pig model of myocardial infarction. Am J Physiol Heart Circ Physiol 2023; 325:H54-H65. [PMID: 37145956 PMCID: PMC10511165 DOI: 10.1152/ajpheart.00732.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 04/07/2023] [Accepted: 04/21/2023] [Indexed: 05/07/2023]
Abstract
Ventricular arrhythmia (VT/VF) can complicate acute myocardial ischemia (AMI). Regional instability of repolarization during AMI contributes to the substrate for VT/VF. Beat-to-beat variability of repolarization (BVR), a measure of repolarization lability increases during AMI. We hypothesized that its surge precedes VT/VF. We studied the spatial and temporal changes in BVR in relation to VT/VF during AMI. In 24 pigs, BVR was quantified on 12-lead electrocardiogram recorded at a sampling rate of 1 kHz. AMI was induced in 16 pigs by percutaneous coronary artery occlusion (MI), whereas 8 underwent sham operation (sham). Changes in BVR were assessed at 5 min after occlusion, 5 and 1 min pre-VF in animals that developed VF, and matched time points in pigs without VF. Serum troponin and ST deviation were measured. After 1 mo, magnetic resonance imaging and VT induction by programmed electrical stimulation were performed. During AMI, BVR increased significantly in inferior-lateral leads correlating with ST deviation and troponin increase. BVR was maximal 1 min pre-VF (3.78 ± 1.36 vs. 5 min pre-VF, 1.67 ± 1.56, P < 0.0001). After 1 mo, BVR was higher in MI than in sham and correlated with the infarct size (1.43 ± 0.50 vs. 0.57 ± 0.30, P = 0.009). VT was inducible in all MI animals and the ease of induction correlated with BVR. BVR increased during AMI and temporal BVR changes predicted imminent VT/VF, supporting a possible role in monitoring and early warning systems. BVR correlated to arrhythmia vulnerability suggesting utility in risk stratification post-AMI.NEW & NOTEWORTHY The key finding of this study is that BVR increases during AMI and surges before ventricular arrhythmia onset. This suggests that monitoring BVR may be useful for monitoring the risk of VF during and after AMI in the coronary care unit settings. Beyond this, monitoring BVR may have value in cardiac implantable devices or wearables.
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Affiliation(s)
- Matthew Amoni
- Experimental Cardiology, Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium
- Department of Cardiology, University Hospitals, Leuven, Belgium
| | - Sebastian Ingelaere
- Experimental Cardiology, Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium
- Department of Cardiology, University Hospitals, Leuven, Belgium
| | - Jonathan Moeyersons
- Department of Electrical Engineering, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium
| | - Dries Wets
- Experimental Cardiology, Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium
| | - Aldo Tanushi
- Experimental Cardiology, Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium
| | - Sabine Van Huffel
- Department of Electrical Engineering, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium
| | - Carolina Varon
- Department of Electrical Engineering, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium
- Microgravity Research Center, Université Libre de Bruxelles, Brussels, Belgium
| | - Karin Sipido
- Experimental Cardiology, Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium
| | - Piet Claus
- Cardiovascular Imaging and Dynamics, Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium
| | - Rik Willems
- Experimental Cardiology, Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium
- Department of Cardiology, University Hospitals, Leuven, Belgium
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2
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Amoni M, Dries E, Ingelaere S, Vermoortele D, Roderick HL, Claus P, Willems R, Sipido KR. Ventricular Arrhythmias in Ischemic Cardiomyopathy-New Avenues for Mechanism-Guided Treatment. Cells 2021; 10:2629. [PMID: 34685609 PMCID: PMC8534043 DOI: 10.3390/cells10102629] [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: 08/16/2021] [Revised: 09/20/2021] [Accepted: 09/23/2021] [Indexed: 12/13/2022] Open
Abstract
Ischemic heart disease is the most common cause of lethal ventricular arrhythmias and sudden cardiac death (SCD). In patients who are at high risk after myocardial infarction, implantable cardioverter defibrillators are the most effective treatment to reduce incidence of SCD and ablation therapy can be effective for ventricular arrhythmias with identifiable culprit lesions. Yet, these approaches are not always successful and come with a considerable cost, while pharmacological management is often poor and ineffective, and occasionally proarrhythmic. Advances in mechanistic insights of arrhythmias and technological innovation have led to improved interventional approaches that are being evaluated clinically, yet pharmacological advancement has remained behind. We review the mechanistic basis for current management and provide a perspective for gaining new insights that centre on the complex tissue architecture of the arrhythmogenic infarct and border zone with surviving cardiac myocytes as the source of triggers and central players in re-entry circuits. Identification of the arrhythmia critical sites and characterisation of the molecular signature unique to these sites can open avenues for targeted therapy and reduce off-target effects that have hampered systemic pharmacotherapy. Such advances are in line with precision medicine and a patient-tailored therapy.
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Affiliation(s)
- Matthew Amoni
- Experimental Cardiology, Department of Cardiovascular Sciences, KU Leuven, 3000 Leuven, Belgium; (M.A.); (E.D.); (S.I.); (H.L.R.); (R.W.)
- Division of Cardiology, University Hospitals Leuven, 3000 Leuven, Belgium
- Department of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town 7935, South Africa
| | - Eef Dries
- Experimental Cardiology, Department of Cardiovascular Sciences, KU Leuven, 3000 Leuven, Belgium; (M.A.); (E.D.); (S.I.); (H.L.R.); (R.W.)
| | - Sebastian Ingelaere
- Experimental Cardiology, Department of Cardiovascular Sciences, KU Leuven, 3000 Leuven, Belgium; (M.A.); (E.D.); (S.I.); (H.L.R.); (R.W.)
- Division of Cardiology, University Hospitals Leuven, 3000 Leuven, Belgium
| | - Dylan Vermoortele
- Imaging and Cardiovascular Dynamics, Department of Cardiovascular Sciences, KU Leuven, 3000 Leuven, Belgium; (D.V.); (P.C.)
| | - H. Llewelyn Roderick
- Experimental Cardiology, Department of Cardiovascular Sciences, KU Leuven, 3000 Leuven, Belgium; (M.A.); (E.D.); (S.I.); (H.L.R.); (R.W.)
| | - Piet Claus
- Imaging and Cardiovascular Dynamics, Department of Cardiovascular Sciences, KU Leuven, 3000 Leuven, Belgium; (D.V.); (P.C.)
| | - Rik Willems
- Experimental Cardiology, Department of Cardiovascular Sciences, KU Leuven, 3000 Leuven, Belgium; (M.A.); (E.D.); (S.I.); (H.L.R.); (R.W.)
- Division of Cardiology, University Hospitals Leuven, 3000 Leuven, Belgium
| | - Karin R. Sipido
- Experimental Cardiology, Department of Cardiovascular Sciences, KU Leuven, 3000 Leuven, Belgium; (M.A.); (E.D.); (S.I.); (H.L.R.); (R.W.)
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3
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Merino-Caviedes S, Gutierrez LK, Alfonso-Almazán JM, Sanz-Estébanez S, Cordero-Grande L, Quintanilla JG, Sánchez-González J, Marina-Breysse M, Galán-Arriola C, Enríquez-Vázquez D, Torres C, Pizarro G, Ibáñez B, Peinado R, Merino JL, Pérez-Villacastín J, Jalife J, López-Yunta M, Vázquez M, Aguado-Sierra J, González-Ferrer JJ, Pérez-Castellano N, Martín-Fernández M, Alberola-López C, Filgueiras-Rama D. Time-efficient three-dimensional transmural scar assessment provides relevant substrate characterization for ventricular tachycardia features and long-term recurrences in ischemic cardiomyopathy. Sci Rep 2021; 11:18722. [PMID: 34580343 PMCID: PMC8476552 DOI: 10.1038/s41598-021-97399-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 08/17/2021] [Indexed: 11/21/2022] Open
Abstract
Delayed gadolinium-enhanced cardiac magnetic resonance (LGE-CMR) imaging requires novel and time-efficient approaches to characterize the myocardial substrate associated with ventricular arrhythmia in patients with ischemic cardiomyopathy. Using a translational approach in pigs and patients with established myocardial infarction, we tested and validated a novel 3D methodology to assess ventricular scar using custom transmural criteria and a semiautomatic approach to obtain transmural scar maps in ventricular models reconstructed from both 3D-acquired and 3D-upsampled-2D-acquired LGE-CMR images. The results showed that 3D-upsampled models from 2D LGE-CMR images provided a time-efficient alternative to 3D-acquired sequences to assess the myocardial substrate associated with ischemic cardiomyopathy. Scar assessment from 2D-LGE-CMR sequences using 3D-upsampled models was superior to conventional 2D assessment to identify scar sizes associated with the cycle length of spontaneous ventricular tachycardia episodes and long-term ventricular tachycardia recurrences after catheter ablation. This novel methodology may represent an efficient approach in clinical practice after manual or automatic segmentation of myocardial borders in a small number of conventional 2D LGE-CMR slices and automatic scar detection.
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Affiliation(s)
| | - Lilian K Gutierrez
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Myocardial Pathophysiology Area, Madrid, Spain
| | | | | | - Lucilio Cordero-Grande
- Universidad Politécnica de Madrid, Biomedical Image Technologies, ETSI Telecomunicación, Madrid, Spain.,Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
| | - Jorge G Quintanilla
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Myocardial Pathophysiology Area, Madrid, Spain.,Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute, Madrid, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | | | - Manuel Marina-Breysse
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Myocardial Pathophysiology Area, Madrid, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | - Carlos Galán-Arriola
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Myocardial Pathophysiology Area, Madrid, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | - Daniel Enríquez-Vázquez
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Myocardial Pathophysiology Area, Madrid, Spain.,Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute, Madrid, Spain
| | - Carlos Torres
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute, Madrid, Spain
| | - Gonzalo Pizarro
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Myocardial Pathophysiology Area, Madrid, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain.,Hospital Ruber Juan Bravo Quironsalud UEM, Cardiology Department, Madrid, Spain
| | - Borja Ibáñez
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Myocardial Pathophysiology Area, Madrid, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain.,IIS-University Hospital Fundación Jiménez Díaz, Cardiology Department, Madrid, Spain
| | - Rafael Peinado
- Hospital Universitario La Paz, Cardiology Department, Madrid, Spain
| | - Jose Luis Merino
- Hospital Universitario La Paz, Cardiology Department, Madrid, Spain
| | - Julián Pérez-Villacastín
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute, Madrid, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain.,Fundación Interhospitalaria para la Investigación Cardiovascular (FIC), Madrid, Spain
| | - José Jalife
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Myocardial Pathophysiology Area, Madrid, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | | | - Mariano Vázquez
- Barcelona Supercomputing Center (BSC), Barcelona, Spain.,ELEM Biotech SL., Barcelona, Spain
| | | | - Juan José González-Ferrer
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute, Madrid, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | - Nicasio Pérez-Castellano
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute, Madrid, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain.,Fundación Interhospitalaria para la Investigación Cardiovascular (FIC), Madrid, Spain
| | | | | | - David Filgueiras-Rama
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Myocardial Pathophysiology Area, Madrid, Spain. .,Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute, Madrid, Spain. .,Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain.
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4
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Bhaskaran A, Fitzgerald J, Jackson N, Gizurarson S, Nanthakumar K, Porta-Sánchez A. Decrement Evoked Potential Mapping to Guide Ventricular Tachycardia Ablation: Elucidating the Functional Substrate. Arrhythm Electrophysiol Rev 2020; 9:211-218. [PMID: 33437489 PMCID: PMC7788395 DOI: 10.15420/aer.2020.25] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Empirical approaches to targeting the ventricular tachycardia (VT) substrate include mapping of late potentials, local abnormal electrogram, pace-mapping and homogenisation of the abnormal signals. These approaches do not try to differentiate between the passive or active role of local signals as the critical components of the VT circuit. By not considering the functional components, these approaches often view the substrate as a fixed anatomical barrier. Strategies to improve the success of VT ablation need to include the identification of critical functional substrate. Decrement-evoked potential (DeEP) mapping has been developed to elucidate this using an extra-stimulus added to a pacing drive train. With knowledge translation in mind, the authors detail the evolution of the DeEP concept by way of a study of simultaneous panoramic endocardial mapping in VT ablation; an in silico modelling study to demonstrate the factors influencing DeEPs; a multicentre VT ablation validation study; a practical approach to DeEP mapping; the potential utility of DeEPs to identify arrhythmogenic atrial substrate; and, finally, other functional mapping strategies.
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Affiliation(s)
| | | | | | | | | | - Andreu Porta-Sánchez
- Hospital Universitario Quirónsalud Madrid, Molecular Cardiology Laboratory, Centro Nacional de Investigaciones Cardiovasculares, Spain
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5
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Li W, Gao H, Mangion K, Berry C, Luo X. Apparent growth tensor of left ventricular post myocardial infarction - In human first natural history study. Comput Biol Med 2020; 129:104168. [PMID: 33341555 DOI: 10.1016/j.compbiomed.2020.104168] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 12/03/2020] [Accepted: 12/03/2020] [Indexed: 11/25/2022]
Abstract
An outstanding challenge in modelling biomechanics after myocardial infarction (MI) is to estimate the so-called growth tensor. Since it is impossible to track pure growth induced geometry change from in vivo magnetic resonance images alone, in this work, we propose a way of estimating a surrogate or apparent growth tensor of the human left ventricle using cine magnetic resonance (CMR) and late gadolinium enhanced (LGE) images of 16 patients following acute MI. The apparent growth tensor is evaluated at four time-points following myocardial reperfusion: 4-12 h (baseline), 3 days, 10 days and 7 months. We have identified three different growth patterns classified as the Dilation, No-Change and Shrinkage groups defined by the left ventricle end-diastole cavity volume change from baseline. We study the- trends in both the infarct and remote regions. Importantly, although the No-Change group has little change in the ventricular cavity volume, significant remodelling changes are seen within the myocardial wall, both in the infarct and remote regions. Through statistical analysis, we show that the growth tensor invariants can be used as effective biomarkers for adverse and favourable remodelling of the heart from 10 days onwards post-MI with statistically significant changes over time, in contrast to most of the routine clinical indices. We believe this is the first time that the apparent growth tensor has been estimated from in vivo CMR images post-MI. Our study not only provides much-needed information for understanding growth and remodelling in the human heart following acute MI, but also identifies novel biomarker for assessing heart disease progression.
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Affiliation(s)
- Wenguang Li
- School of Engineering, University of Glasgow, UK.
| | - Hao Gao
- School of Mathematics and Statistics, University of Glasgow, UK.
| | - Kenneth Mangion
- College of Medical, Veterinary and Life Sciences, University of Glasgow, UK.
| | - Colin Berry
- College of Medical, Veterinary and Life Sciences, University of Glasgow, UK.
| | - Xiaoyu Luo
- School of Mathematics and Statistics, University of Glasgow, UK.
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6
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Tornifoglio B, Stone AJ, Johnston RD, Shahid SS, Kerskens C, Lally C. Diffusion tensor imaging and arterial tissue: establishing the influence of arterial tissue microstructure on fractional anisotropy, mean diffusivity and tractography. Sci Rep 2020; 10:20718. [PMID: 33244026 PMCID: PMC7693170 DOI: 10.1038/s41598-020-77675-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Accepted: 10/26/2020] [Indexed: 12/11/2022] Open
Abstract
This study investigates diffusion tensor imaging (DTI) for providing microstructural insight into changes in arterial tissue by exploring how cell, collagen and elastin content effect fractional anisotropy (FA), mean diffusivity (MD) and tractography. Five ex vivo porcine carotid artery models (n = 6 each) were compared-native, fixed native, collagen degraded, elastin degraded and decellularised. Vessels were imaged at 7 T using a DTI protocol with b = 0 and 800 s/mm2 and 10 isotopically distributed directions. FA and MD were evaluated in the vessel media and compared across models. FA values measured in native (p < 0.0001), fixed native (p < 0.0001) and collagen degraded (p = 0.0018, p = 0.0016, respectively) were significantly higher than those in elastin degraded and decellularised arteries. Native and fixed native had significantly lower MD values than elastin degraded (p < 0.0001) and decellularised tissue (p = 0.0032, p = 0.0003, respectively). Significantly lower MD was measured in collagen degraded compared with the elastin degraded model (p = 0.0001). Tractography yielded helically arranged tracts for native and collagen degraded vessels only. FA, MD and tractography were found to be highly sensitive to changes in the microstructural composition of arterial tissue, specifically pointing to cell, not collagen, content as the dominant source of the measured anisotropy in the vessel wall.
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Affiliation(s)
- B Tornifoglio
- Trinity Centre for Biomedical Engineering, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
- Department of Mechanical, Manufacturing and Biomedical Engineering, School of Engineering, Trinity College Dublin, Dublin, Ireland
| | - A J Stone
- Trinity Centre for Biomedical Engineering, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
- Department of Mechanical, Manufacturing and Biomedical Engineering, School of Engineering, Trinity College Dublin, Dublin, Ireland
| | - R D Johnston
- Trinity Centre for Biomedical Engineering, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
- Department of Mechanical, Manufacturing and Biomedical Engineering, School of Engineering, Trinity College Dublin, Dublin, Ireland
| | - S S Shahid
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - C Kerskens
- Trinity Centre for Biomedical Engineering, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - C Lally
- Trinity Centre for Biomedical Engineering, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.
- Department of Mechanical, Manufacturing and Biomedical Engineering, School of Engineering, Trinity College Dublin, Dublin, Ireland.
- Advanced Materials and Bioengineering Research Centre (AMBER), Royal College of Surgeons in Ireland and Trinity College Dublin, Dublin, Ireland.
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7
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Nelson T, Garg P, Clayton RH, Lee J. The Role of Cardiac MRI in the Management of Ventricular Arrhythmias in Ischaemic and Non-ischaemic Dilated Cardiomyopathy. Arrhythm Electrophysiol Rev 2019; 8:191-201. [PMID: 31463057 PMCID: PMC6702467 DOI: 10.15420/aer.2019.5.1] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2019] [Accepted: 04/25/2019] [Indexed: 02/07/2023] Open
Abstract
Ventricular tachycardia (VT) and VF account for the majority of sudden cardiac deaths worldwide. Treatments for VT/VF include anti-arrhythmic drugs, ICDs and catheter ablation, but these treatments vary in effectiveness and carry substantial risks and/or expense. Current methods of selecting patients for ICD implantation are imprecise and fail to identify some at-risk patients, while leading to others being overtreated. In this article, the authors discuss the current role and future direction of cardiac MRI (CMRI) in refining diagnosis and personalising ventricular arrhythmia management. The capability of CMRI with gadolinium contrast delayed-enhancement patterns and, more recently, T1 mapping to determine the aetiology of patients presenting with heart failure is well established. Although CMRI imaging in patients with ICDs can be challenging, recent technical developments have started to overcome this. CMRI can contribute to risk stratification, with precise and reproducible assessment of ejection fraction, quantification of scar and 'border zone' volumes, and other indices. Detailed tissue characterisation has begun to enable creation of personalised computer models to predict an individual patient's arrhythmia risk. When patients require VT ablation, a substrate-based approach is frequently employed as haemodynamic instability may limit electrophysiological activation mapping. Beyond accurate localisation of substrate, CMRI could be used to predict the location of re-entrant circuits within the scar to guide ablation.
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Affiliation(s)
- Tom Nelson
- Sheffield Teaching Hospitals NHS Foundation TrustSheffield, UK
- Department of Immunity, Infection and Cardiovascular Disease, University of SheffieldSheffield, UK
| | - Pankaj Garg
- Sheffield Teaching Hospitals NHS Foundation TrustSheffield, UK
- Department of Immunity, Infection and Cardiovascular Disease, University of SheffieldSheffield, UK
| | - Richard H Clayton
- INSIGNEO Institute for In-Silico Medicine, University of SheffieldSheffield, UK
- Department of Computer Science, University of SheffieldSheffield, UK
| | - Justin Lee
- Sheffield Teaching Hospitals NHS Foundation TrustSheffield, UK
- Department of Immunity, Infection and Cardiovascular Disease, University of SheffieldSheffield, UK
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