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Agarwal PP, Nasr LA, Ghoshhajra BB, Brown RKJ, Collier P, De Cecco CN, Fuss C, Goldstein JN, Kallianos K, Malik SB, Maroules CD, Meyersohn NM, Nazarian S, Scherer MD, Singh S, Tailor TD, Tong MS, Koweek LM. ACR Appropriateness Criteria® Preprocedural Planning for Left Atrial Procedures in Atrial Fibrillation. J Am Coll Radiol 2024; 21:S237-S248. [PMID: 38823947 DOI: 10.1016/j.jacr.2024.02.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 02/28/2024] [Indexed: 06/03/2024]
Abstract
This document summarizes the relevant literature for the selection of preprocedural imaging in three clinical scenarios in patients needing endovascular treatment or cardioversion of atrial fibrillation. These clinical scenarios include preprocedural imaging prior to radiofrequency ablation; prior to left atrial appendage occlusion; and prior to cardioversion. The appropriateness of imaging modalities as they apply to each clinical scenario is rated as usually appropriate, may be appropriate, and usually not appropriate to assist the selection of the most appropriate imaging modality in the corresponding clinical scenarios. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.
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Affiliation(s)
| | - Layla A Nasr
- Research Author, Allegheny Health Network Imaging Institute, Pittsburgh, Pennsylvania
| | | | - Richard K J Brown
- University of Utah, Department of Radiology and Imaging Sciences, Salt Lake City, Utah; Commission on Nuclear Medicine and Molecular Imaging
| | | | | | - Cristina Fuss
- Oregon Health & Science University, Portland, Oregon
| | - Jennifer N Goldstein
- ChristianaCare Health System, Newark, Delaware; Society of General Internal Medicine
| | | | - Sachin B Malik
- VA Palo Alto Health Care System, Palo Alto, California; Stanford University, Stanford, California
| | | | | | - Saman Nazarian
- Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania; Heart Rhythm Society
| | - Markus D Scherer
- Sanger Heart and Vascular Institute, Charlotte, North Carolina; Society of Cardiovascular Computed Tomography
| | - Simranjit Singh
- Indiana University School of Medicine, Indianapolis, Indiana; American College of Physicians
| | - Tina D Tailor
- Duke University Medical Center, Durham, North Carolina
| | - Matthew S Tong
- Ohio State University, Columbus, Ohio; Society for Cardiovascular Magnetic Resonance
| | - Lynne M Koweek
- Specialty Chair, Duke University Medical Center, Durham, North Carolina
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2
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Uslu F. GSM-Net: A global sequence modelling network for the segmentation of short axis CINE MRI images. Comput Med Imaging Graph 2023; 108:102266. [PMID: 37385047 DOI: 10.1016/j.compmedimag.2023.102266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 05/04/2023] [Accepted: 06/11/2023] [Indexed: 07/01/2023]
Abstract
Atrial Fibrillation (AF) is a disease where the atria fail to properly contract but quiver instead, due to the abnormal electrical activity of the atrial tissue. In AF patients, anatomical and functional parameters of the left atrium (LA) largely differ from that of healthy people due to LA remodelling, which can continue in many cases after the catheter ablation treatment. Therefore, it is important to follow up with AF patients to detect any recurrence. LA segmentation masks obtained from short-axis CINE MRI images are used as the gold standard for the quantification of LA parameters. Thick slices of CINE MRI images hinder the use of 3D networks for segmentation while 2D architectures often fail to model inter-slice dependencies. This study presents GSM-Net which approximates 3D networks with effective modelling of inter-slice similarities with two new modules: global slice sequence encoder (GSSE) and sequence dependent channel attention module (SdCAt). In contrast to previous work modelling only local inter-slice similarities, GSSE also models global spatial dependencies across slices. SdCAt generates a distribution of attention weights over MRI slices per channel, to better trace characteristic changes in the size of the LA or other structures across slices. We found that GSM-Net outperforms previous methods on LA segmentation and helps to identify AF recurrence patients. We believe that GSM-Net can be used as an automatic tool to estimate LA parameters such as ejection fraction to identify AF, and to follow up with patients after treatment to detect any recurrence.
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Affiliation(s)
- Fatmatülzehra Uslu
- Bursa Technical University, Electrical and Electronics Engineering Department, Bursa, 16310, Türkiye.
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3
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O’Neill L, Sim I, O’Hare D, Whitaker J, Mukherjee RK, Razeghi O, Niederer S, Wright M, Chiribiri A, Frigiola A, O’Neill MD, Williams SE. CArdiac MagnEtic resonance assessment of bi-Atrial fibrosis in secundum atrial septal defects patients: CAMERA-ASD study. Eur Heart J Cardiovasc Imaging 2022; 23:1231-1239. [PMID: 34568942 PMCID: PMC9365304 DOI: 10.1093/ehjci/jeab188] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Indexed: 12/25/2022] Open
Abstract
AIMS Atrial septal defects (ASD) are associated with atrial arrhythmias, but the arrhythmia substrate in these patients is poorly defined. We hypothesized that bi-atrial fibrosis is present and that right atrial fibrosis is associated with atrial arrhythmias in ASD patients. We aimed to evaluate the extent of bi-atrial fibrosis in ASD patients and to investigate the relationships between bi-atrial fibrosis, atrial arrhythmias, shunt fraction, and age. METHODS AND RESULTS Patients with uncorrected secundum ASDs (n = 36; 50.4 ± 13.6 years) underwent cardiac magnetic resonance imaging with atrial late gadolinium enhancement. Comparison was made to non-congenital heart disease patients (n = 36; 60.3 ± 10.5 years) with paroxysmal atrial fibrillation (AF). Cardiac magnetic resonance parameters associated with atrial arrhythmias were identified and the relationship between bi-atrial structure, age, and shunt fraction studied. Bi-atrial fibrosis burden was greater in ASD patients than paroxysmal AF patients (20.7 ± 14% vs. 10.1 ± 8.6% and 14.8 ± 8.5% vs. 8.6 ± 6.1% for right and left atria respectively, P = 0.001 for both). In ASD patients, right atrial fibrosis burden was greater in those with than without atrial arrhythmias (33.4 ± 18.7% vs. 16.8 ± 10.3%, P = 0.034). On receiver operating characteristic analysis, a right atrial fibrosis burden of 32% had a 92% specificity and 71% sensitivity for predicting the presence of atrial arrhythmias. Neither age nor shunt fraction was associated with bi-atrial fibrosis burden. CONCLUSION Bi-atrial fibrosis burden is greater in ASD patients than non-congenital heart disease patients with paroxysmal AF. Right atrial fibrosis is associated with the presence of atrial arrhythmias in ASD patients. These findings highlight the importance of right atrial fibrosis to atrial arrhythmogenesis in ASD patients.
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Affiliation(s)
- Louisa O’Neill
- Division of Imaging Sciences and Biomedical Engineering, King’s College London, 4th Floor North, Wing, St. Thomas’, Hospital, London SE1 7EH, UK
| | - Iain Sim
- Division of Imaging Sciences and Biomedical Engineering, King’s College London, 4th Floor North, Wing, St. Thomas’, Hospital, London SE1 7EH, UK
| | - Daniel O’Hare
- Division of Imaging Sciences and Biomedical Engineering, King’s College London, 4th Floor North, Wing, St. Thomas’, Hospital, London SE1 7EH, UK
| | - John Whitaker
- Division of Imaging Sciences and Biomedical Engineering, King’s College London, 4th Floor North, Wing, St. Thomas’, Hospital, London SE1 7EH, UK
| | - Rahul K Mukherjee
- Division of Imaging Sciences and Biomedical Engineering, King’s College London, 4th Floor North, Wing, St. Thomas’, Hospital, London SE1 7EH, UK
| | - Orod Razeghi
- Division of Imaging Sciences and Biomedical Engineering, King’s College London, 4th Floor North, Wing, St. Thomas’, Hospital, London SE1 7EH, UK
| | - Steven Niederer
- Division of Imaging Sciences and Biomedical Engineering, King’s College London, 4th Floor North, Wing, St. Thomas’, Hospital, London SE1 7EH, UK
| | - Matthew Wright
- Division of Imaging Sciences and Biomedical Engineering, King’s College London, 4th Floor North, Wing, St. Thomas’, Hospital, London SE1 7EH, UK
| | - Amedeo Chiribiri
- Division of Imaging Sciences and Biomedical Engineering, King’s College London, 4th Floor North, Wing, St. Thomas’, Hospital, London SE1 7EH, UK
| | | | - Mark D O’Neill
- Division of Imaging Sciences and Biomedical Engineering, King’s College London, 4th Floor North, Wing, St. Thomas’, Hospital, London SE1 7EH, UK
| | - Steven E Williams
- Division of Imaging Sciences and Biomedical Engineering, King’s College London, 4th Floor North, Wing, St. Thomas’, Hospital, London SE1 7EH, UK
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Yakimenka A, Labib D, Dykstra S, Mikami Y, Satriano A, Flewitt J, Feuchter P, Rivest S, Howarth AG, Lydell CP, Quinn FR, Wilton SB, White JA. Influence of Sex-Based Differences in Cardiac Phenotype on Atrial Fibrillation Recurrence in Patients Undergoing Pulmonary Vein Isolation. Front Cardiovasc Med 2022; 9:894592. [PMID: 35966521 PMCID: PMC9366168 DOI: 10.3389/fcvm.2022.894592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 06/13/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundPulmonary vein isolation (PVI) is a commonly engaged therapy for symptomatic atrial fibrillation (AF). Prior studies have documented elevated AF recurrence rates among females vs. males. Sex-specific mechanisms underlying this phenomenon are poorly understood. This prospective cohort study aimed to evaluate the sex-based differences in cardiac phenotype and their influence on (AF) recurrence following first-time PVI.MethodsA total of 204 consecutive patients referred for first-time PVI and 101 healthy subjects were prospectively studied by cardiovascular magnetic resonance (CMR) imaging. Multi-chamber volumetric and functional measures were assessed by sex-corrected Z-score analyses vs. healthy subjects. Patients were followed for a median of 2.6 years for the primary outcome of clinical AF recurrence. Multivariable analyses adjusting for age and comorbidities were performed to identify independent predictors of AF recurrence.ResultsAF recurrence following first PVI occurred in 41% of males and 59% of females (p = 0.03). Females were older with higher prevalence of hypertension and thyroid disorders. Z-score-based analyses revealed significantly reduced ventricular volumes, greater left atrial (LA) volumes, and reduced LA contractility in females vs. males. Multivariable analysis revealed each of LA minimum and pre-systolic volumes and booster EF Z-scores to be independently associated with AF recurrence, providing respective hazard ratios of 1.10, 1.19, and 0.89 (p = 0.001, 0.03, and 0.01).ConclusionAmong patients referred for first time PVI, females were older and demonstrated significantly poorer LA contractile health vs. males, the latter independently associated with AF recurrence. Assessment of LA contractile health may therefore be of value to identify female patients at elevated risk of AF recurrence. Factors influencing female patient referral for PVI at more advanced stages of atrial disease warrant focused investigation.
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Affiliation(s)
- Alena Yakimenka
- Stephenson Cardiac Imaging Centre, Libin Cardiovascular Institute of Alberta, University of Calgary, Calgary, AB, Canada
- Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Dina Labib
- Stephenson Cardiac Imaging Centre, Libin Cardiovascular Institute of Alberta, University of Calgary, Calgary, AB, Canada
- Department of Cardiovascular Medicine, Cairo University, Cairo, Egypt
| | - Steven Dykstra
- Stephenson Cardiac Imaging Centre, Libin Cardiovascular Institute of Alberta, University of Calgary, Calgary, AB, Canada
| | - Yoko Mikami
- Stephenson Cardiac Imaging Centre, Libin Cardiovascular Institute of Alberta, University of Calgary, Calgary, AB, Canada
| | - Alessandro Satriano
- Stephenson Cardiac Imaging Centre, Libin Cardiovascular Institute of Alberta, University of Calgary, Calgary, AB, Canada
| | - Jacqueline Flewitt
- Stephenson Cardiac Imaging Centre, Libin Cardiovascular Institute of Alberta, University of Calgary, Calgary, AB, Canada
| | - Patricia Feuchter
- Stephenson Cardiac Imaging Centre, Libin Cardiovascular Institute of Alberta, University of Calgary, Calgary, AB, Canada
| | - Sandra Rivest
- Stephenson Cardiac Imaging Centre, Libin Cardiovascular Institute of Alberta, University of Calgary, Calgary, AB, Canada
| | - Andrew G. Howarth
- Stephenson Cardiac Imaging Centre, Libin Cardiovascular Institute of Alberta, University of Calgary, Calgary, AB, Canada
- Department of Cardiac Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Carmen P. Lydell
- Stephenson Cardiac Imaging Centre, Libin Cardiovascular Institute of Alberta, University of Calgary, Calgary, AB, Canada
- Department of Diagnostic Imaging, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - F. Russell Quinn
- Department of Cardiac Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Stephen B. Wilton
- Department of Cardiac Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - James A. White
- Stephenson Cardiac Imaging Centre, Libin Cardiovascular Institute of Alberta, University of Calgary, Calgary, AB, Canada
- Department of Cardiac Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- *Correspondence: James A. White,
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Ismail TF, Strugnell W, Coletti C, Božić-Iven M, Weingärtner S, Hammernik K, Correia T, Küstner T. Cardiac MR: From Theory to Practice. Front Cardiovasc Med 2022; 9:826283. [PMID: 35310962 PMCID: PMC8927633 DOI: 10.3389/fcvm.2022.826283] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 01/17/2022] [Indexed: 01/10/2023] Open
Abstract
Cardiovascular disease (CVD) is the leading single cause of morbidity and mortality, causing over 17. 9 million deaths worldwide per year with associated costs of over $800 billion. Improving prevention, diagnosis, and treatment of CVD is therefore a global priority. Cardiovascular magnetic resonance (CMR) has emerged as a clinically important technique for the assessment of cardiovascular anatomy, function, perfusion, and viability. However, diversity and complexity of imaging, reconstruction and analysis methods pose some limitations to the widespread use of CMR. Especially in view of recent developments in the field of machine learning that provide novel solutions to address existing problems, it is necessary to bridge the gap between the clinical and scientific communities. This review covers five essential aspects of CMR to provide a comprehensive overview ranging from CVDs to CMR pulse sequence design, acquisition protocols, motion handling, image reconstruction and quantitative analysis of the obtained data. (1) The basic MR physics of CMR is introduced. Basic pulse sequence building blocks that are commonly used in CMR imaging are presented. Sequences containing these building blocks are formed for parametric mapping and functional imaging techniques. Commonly perceived artifacts and potential countermeasures are discussed for these methods. (2) CMR methods for identifying CVDs are illustrated. Basic anatomy and functional processes are described to understand the cardiac pathologies and how they can be captured by CMR imaging. (3) The planning and conduct of a complete CMR exam which is targeted for the respective pathology is shown. Building blocks are illustrated to create an efficient and patient-centered workflow. Further strategies to cope with challenging patients are discussed. (4) Imaging acceleration and reconstruction techniques are presented that enable acquisition of spatial, temporal, and parametric dynamics of the cardiac cycle. The handling of respiratory and cardiac motion strategies as well as their integration into the reconstruction processes is showcased. (5) Recent advances on deep learning-based reconstructions for this purpose are summarized. Furthermore, an overview of novel deep learning image segmentation and analysis methods is provided with a focus on automatic, fast and reliable extraction of biomarkers and parameters of clinical relevance.
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Affiliation(s)
- Tevfik F. Ismail
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Cardiology Department, Guy's and St Thomas' Hospital, London, United Kingdom
| | - Wendy Strugnell
- Queensland X-Ray, Mater Hospital Brisbane, Brisbane, QLD, Australia
| | - Chiara Coletti
- Magnetic Resonance Systems Lab, Delft University of Technology, Delft, Netherlands
| | - Maša Božić-Iven
- Magnetic Resonance Systems Lab, Delft University of Technology, Delft, Netherlands
- Computer Assisted Clinical Medicine, Heidelberg University, Mannheim, Germany
| | | | - Kerstin Hammernik
- Lab for AI in Medicine, Technical University of Munich, Munich, Germany
- Department of Computing, Imperial College London, London, United Kingdom
| | - Teresa Correia
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Centre of Marine Sciences, Faro, Portugal
| | - Thomas Küstner
- Medical Image and Data Analysis (MIDAS.lab), Department of Diagnostic and Interventional Radiology, University Hospital of Tübingen, Tübingen, Germany
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6
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Hopman LHGA, Bhagirath P, Mulder MJ, Eggink IN, van Rossum AC, Allaart CP, Götte MJW. Extent of Left Atrial Fibrosis Correlates with Descending Aorta Proximity at 3D Late Gadolinium Enhancement Cardiac MRI in Patients with Atrial Fibrillation. Radiol Cardiothorac Imaging 2022; 4:e210192. [PMID: 35795718 PMCID: PMC8893208 DOI: 10.1148/ryct.210192] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 11/15/2021] [Accepted: 11/29/2021] [Indexed: 05/04/2023]
Abstract
PURPOSE To determine whether the distance between the descending aorta and left atrial (LA) wall correlates with the amount of fibrosis quantified in the posterior left inferior pulmonary vein (LIPV) area of the LA in patients with atrial fibrillation (AF). MATERIALS AND METHODS In this retrospective study, patients with AF underwent cardiac MRI in sinus rhythm prior to a pulmonary vein isolation procedure (July 2018 to February 2020). The mean distance (distancemean) and shortest distance (distanceshort) between the descending aorta and the LA wall were measured on three-dimensional (3D) contrast-enhanced MR angiograms; distancemean was defined as the average of five measurements at different levels between the descending aorta and the LA wall. The extent of LA fibrosis, both global fibrosis and regional fibrosis within the LIPV area, was derived from postprocessed, 3D, late gadolinium-enhanced images. Associations between the extent of fibrosis and the proximity of the descending aorta were analyzed by using correlative and multivariable analyses. RESULTS A total of 47 (mean age, 60 years ± 8 [standard deviation]; 31 men) patients were included for analysis. The extent of fibrosis in the posterior LIPV area was correlated with the distancemean (r s = -0.48; P < .01) and distanceshort (r s = -0.49; P < .01). Patients with a short distance between the descending aorta and LA wall (defined as a distanceshort < 2 mm) had a higher percentage of fibrosis in the posterior LIPV area than patients with a distanceshort greater than 2 mm (38.7% ± 22.7 vs 21.2% ± 17.8; P < .01). CONCLUSION The distance between the descending aorta and LA was correlated with the extent of quantified fibrosis within the posterior LIPV area.Keywords: MRI, Cardiac, Left Atrium Supplemental material is available for this article. © RSNA, 2022.
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7
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Ghafouri K, Franke KB, Foo FS, Stiles MK. Clinical utility of cardiac magnetic resonance imaging to assess the left atrium before catheter ablation for atrial fibrillation - A systematic review and meta-analysis. Int J Cardiol 2021; 339:192-202. [PMID: 34303756 DOI: 10.1016/j.ijcard.2021.07.030] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 06/04/2021] [Accepted: 07/14/2021] [Indexed: 11/28/2022]
Abstract
AIMS This systematic review and meta-analysis aims to clarify the role of pre-procedural cardiac magnetic resonance imaging (MRI) in identifying the association between left atrial (LA) characteristics and post-ablation atrial fibrillation (AF) recurrence. These characteristics include LA fibrosis, emptying function, sphericity, volume, volume index, peak strain and post-contrast T1 relaxation time. METHODS PubMed, EMBASE, and Cochrane were searched up to July 2020 for English language articles reporting the use of cardiac MRI in catheter ablation for AF. Studies reporting the prognostic value of pre-ablation cardiac MRI were included. All references and citations were filtered for relevant manuscripts. RESULTS Twenty-four publications were identified. Every 10% increase in LA fibrosis was associated with a 1.54-fold increase in post-ablation AF recurrence (95%CI: 1.39-1.70, I2 = 50.1%). Every 10 ml increase in LA volume resulted in a hazard ratio of 1.07 (95%CI:1.03-1.12; I2 = 41.4%) for post-ablation AF recurrence. For LA sphericity, there was no significant association with post-ablation AF recurrence (HR: 1.032 [95%CI: 0.962-1.103, I2 = 49.6%). Egger's test was non-significant for publication bias in all meta-analyses. LA volume index, emptying function, peak strain and post-contrast LA T1 relaxation time had insufficient compatible publications to conduct a meta-analysis. CONCLUSION LA fibrosis quantified by cardiac MRI is associated with risk of AF recurrence after AF ablation, while increased LA volume is associated with AF recurrence to a lesser extent. There remains insufficient evidence to support the routine measurement of LA sphericity, LA volume index, LA emptying function, peak strain and LA T1 relaxation time to predict AF recurrence after AF ablation.
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Affiliation(s)
- Khashayar Ghafouri
- The university of Auckland, Faculty of Medical and Health Sciences, 85 Park Road, Grafton, 1023 Auckland, New Zealand..
| | - Kyle B Franke
- The University of Adelaide, Adelaide Medical School, North Terrace, Adelaide, South Australia 5005, Australia
| | - Fang Shawn Foo
- Peter Rothwell Academic Centre, Waikato Hospital, Pembroke Street, 3240 Hamilton, New Zealand; North Shore Hospital, 124 Shakespeare Road, Takapuna, 0620 Auckland, New Zealand
| | - Martin K Stiles
- The university of Auckland, Faculty of Medical and Health Sciences, 85 Park Road, Grafton, 1023 Auckland, New Zealand.; Peter Rothwell Academic Centre, Waikato Hospital, Pembroke Street, 3240 Hamilton, New Zealand
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Evaluation of accelerated motion-compensated 3d water/fat late gadolinium enhanced MR for atrial wall imaging. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2021; 34:877-887. [PMID: 34165670 PMCID: PMC8578113 DOI: 10.1007/s10334-021-00935-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 05/28/2021] [Accepted: 06/03/2021] [Indexed: 12/26/2022]
Abstract
OBJECTIVE 3D late gadolinium enhancement (LGE) imaging is a promising non-invasive technique for the assessment of atrial fibrosis. However, current techniques result in prolonged and unpredictable scan times and high rates of non-diagnostic images. The purpose of this study was to compare the performance of a recently proposed accelerated respiratory motion-compensated 3D water/fat LGE technique with conventional 3D LGE for atrial wall imaging. MATERIALS AND METHODS 18 patients (age: 55.7±17.1 years) with atrial fibrillation underwent conventional diaphragmatic navigator gated inversion recovery (IR)-prepared 3D LGE (dNAV) and proposed image-navigator motion-corrected water/fat IR-prepared 3D LGE (iNAV) imaging. Images were assessed for image quality and presence of fibrosis by three expert observers. The scan time for both techniques was recorded. RESULTS Image quality scores were improved with the proposed compared to the conventional method (iNAV: 3.1 ± 1.0 vs. dNAV: 2.6 ± 1.0, p = 0.0012, with 1: Non-diagnostic to 4: Full diagnostic). Furthermore, scan time for the proposed method was significantly shorter with a 59% reduction is scan time (4.5 ± 1.2 min vs. 10.9 ± 3.9 min, p < 0.0001). The images acquired with the proposed method were deemed as inconclusive less frequently than the conventional images (expert 1/expert 2: 4/7 dNAV and 2/4 iNAV images inconclusive). DISCUSSION The motion-compensated water/fat LGE method enables atrial wall imaging with diagnostic quality comparable to the current conventional approach with a significantly shorter scan of about 5 min.
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Wu Z, Jiang C, Li J, Du J, Bai Y, Guo X, Wang W, Li S, Jiang C, Liu N, Tang R, Bai R, Sang C, Long D, Du X, Ma C, Dong J. Effect of family history of atrial fibrillation on recurrence after atrial fibrillation ablation: A report from the Chinese Atrial Fibrillation Registry Study. J Cardiovasc Electrophysiol 2021; 32:678-685. [PMID: 33512061 DOI: 10.1111/jce.14919] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2020] [Revised: 01/11/2021] [Accepted: 01/21/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND To evaluate the impact of family history of atrial fibrillation (FAF) on postablation atrial tachyarrhythmia (AT) recurrence. METHODS All the 8198 patients undergoing initial AF ablation registered in the Chinese Atrial Fibrillation Registry study were analyzed. FAF was defined as having first-degree relatives diagnosed as AF at age 65 years or younger, and before the time the case in this study was diagnosed. Cox proportional hazards models were used to evaluate the impact of FAF on postablation AT recurrence. Age, sex, body mass index, AF type, history of congestive heart failure, hypertension, diabetes mellitus, prior stroke/transient ischemic attack/systemic embolism, vascular diseases, use of contact force-sensing catheter, and completion of high school were adjusted. The definition of AT recurrence was any documented AF, atrial flutter, or AT lasting more than or equal to 30 s after 3 months blanking period. RESULTS After a mean follow-up of 26.2 ± 19.6 months, 318 out of the 645 patients (49.3%) with FAF and 3339 out of the 7553 patients (44.2%) without FAF experienced AT recurrence, corresponding to annual recurrence rates of 22.8% and 20.2%, respectively. Patients with FAF had a significant higher risk of AT recurrence (adjusted hazard ratio 1.129, 95% confidence interval 1.005-1.267) in multivariable analysis. Moreover, FAF had a significant higher impact on AT recurrence in the subgroup of patients diagnosed with AF at age 50 years or younger (p for interaction = .036). CONCLUSION FAF is a risk factor for postablation AT recurrence. This is especially true in those with AF diagnosed at 50 years or younger.
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Affiliation(s)
- Zhuanzhuan Wu
- Department of Cardiology, Beijing AnZhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing, China
| | - Chao Jiang
- Department of Cardiology, Beijing AnZhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing, China
| | - Jingye Li
- Department of Cardiology, Beijing AnZhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing, China
| | - Jing Du
- Beijing Centre for Disease Prevention and Control, China
| | - Yu Bai
- Faculty of Science, The University of Sydney, Sydney, Australia
| | - Xueyuan Guo
- Department of Cardiology, Beijing AnZhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing, China
| | - Wei Wang
- Department of Cardiology, Beijing AnZhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing, China
| | - Songnan Li
- Department of Cardiology, Beijing AnZhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing, China
| | - Chenxi Jiang
- Department of Cardiology, Beijing AnZhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing, China
| | - Nian Liu
- Department of Cardiology, Beijing AnZhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing, China
| | - Ribo Tang
- Department of Cardiology, Beijing AnZhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing, China
| | - Rong Bai
- Department of Cardiology, Beijing AnZhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing, China
| | - Caihua Sang
- Department of Cardiology, Beijing AnZhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing, China
| | - Deyong Long
- Department of Cardiology, Beijing AnZhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing, China
| | - Xin Du
- Department of Cardiology, Beijing AnZhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing, China.,Heart Health Research Center, Beijing, China.,University of New South Wales, Sydney, Australia
| | - Changsheng Ma
- Department of Cardiology, Beijing AnZhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing, China
| | - Jianzeng Dong
- Department of Cardiology, Beijing AnZhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing, China.,Centre for Cardiovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Henan, China
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10
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Razeghi O, Sim I, Roney CH, Karim R, Chubb H, Whitaker J, O’Neill L, Mukherjee R, Wright M, O’Neill M, Williams SE, Niederer S. Fully Automatic Atrial Fibrosis Assessment Using a Multilabel Convolutional Neural Network. Circ Cardiovasc Imaging 2020; 13:e011512. [PMID: 33317334 PMCID: PMC7771635 DOI: 10.1161/circimaging.120.011512] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Supplemental Digital Content is available in the text. Background: Pathological atrial fibrosis is a major contributor to sustained atrial fibrillation. Currently, late gadolinium enhancement (LGE) scans provide the only noninvasive estimate of atrial fibrosis. However, widespread adoption of atrial LGE has been hindered partly by nonstandardized image processing techniques, which can be operator and algorithm dependent. Minimal validation and limited access to transparent software platforms have also exacerbated the problem. This study aims to estimate atrial fibrosis from cardiac magnetic resonance scans using a reproducible operator-independent fully automatic open-source end-to-end pipeline. Methods: A multilabel convolutional neural network was designed to accurately delineate atrial structures including the blood pool, pulmonary veins, and mitral valve. The output from the network removed the operator dependent steps in a reproducible pipeline and allowed for automated estimation of atrial fibrosis from LGE-cardiac magnetic resonance scans. The pipeline results were compared against manual fibrosis burdens, calculated using published thresholds: image intensity ratio 0.97, image intensity ratio 1.61, and mean blood pool signal +3.3 SD. Results: We validated our methods on a large 3-dimensional LGE-cardiac magnetic resonance data set from 207 labeled scans. Automatic atrial segmentation achieved a 91% Dice score, compared with the mutual agreement of 85% in Dice seen in the interobserver analysis of operators. Intraclass correlation coefficients of the automatic pipeline with manually generated results were excellent and better than or equal to interobserver correlations for all 3 thresholds: 0.94 versus 0.88, 0.99 versus 0.99, 0.99 versus 0.96 for image intensity ratio 0.97, image intensity ratio 1.61, and +3.3 SD thresholds, respectively. Automatic analysis required 3 minutes per case on a standard workstation. The network and the analysis software are publicly available. Conclusions: Our pipeline provides a fully automatic estimation of fibrosis burden from LGE-cardiac magnetic resonance scans that is comparable to manual analysis. This removes one key source of variability in the measurement of atrial fibrosis.
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Affiliation(s)
- Orod Razeghi
- Biomedical Engineering and Imaging Sciences, King’s College London, United Kingdom (O.R., I.S., C.H.R., R.K., H.C., J.W., L.O., R.M., M.O., S.E.W., S.N.)
| | - Iain Sim
- Biomedical Engineering and Imaging Sciences, King’s College London, United Kingdom (O.R., I.S., C.H.R., R.K., H.C., J.W., L.O., R.M., M.O., S.E.W., S.N.)
| | - Caroline H. Roney
- Biomedical Engineering and Imaging Sciences, King’s College London, United Kingdom (O.R., I.S., C.H.R., R.K., H.C., J.W., L.O., R.M., M.O., S.E.W., S.N.)
| | - Rashed Karim
- Biomedical Engineering and Imaging Sciences, King’s College London, United Kingdom (O.R., I.S., C.H.R., R.K., H.C., J.W., L.O., R.M., M.O., S.E.W., S.N.)
| | - Henry Chubb
- Biomedical Engineering and Imaging Sciences, King’s College London, United Kingdom (O.R., I.S., C.H.R., R.K., H.C., J.W., L.O., R.M., M.O., S.E.W., S.N.)
| | - John Whitaker
- Biomedical Engineering and Imaging Sciences, King’s College London, United Kingdom (O.R., I.S., C.H.R., R.K., H.C., J.W., L.O., R.M., M.O., S.E.W., S.N.)
| | - Louisa O’Neill
- Biomedical Engineering and Imaging Sciences, King’s College London, United Kingdom (O.R., I.S., C.H.R., R.K., H.C., J.W., L.O., R.M., M.O., S.E.W., S.N.)
| | - Rahul Mukherjee
- Biomedical Engineering and Imaging Sciences, King’s College London, United Kingdom (O.R., I.S., C.H.R., R.K., H.C., J.W., L.O., R.M., M.O., S.E.W., S.N.)
| | - Matthew Wright
- Cardiology Department, St. Thomas’ Hospital, London, United Kingdom (M.W., M.O.)
| | - Mark O’Neill
- Biomedical Engineering and Imaging Sciences, King’s College London, United Kingdom (O.R., I.S., C.H.R., R.K., H.C., J.W., L.O., R.M., M.O., S.E.W., S.N.)
- Cardiology Department, St. Thomas’ Hospital, London, United Kingdom (M.W., M.O.)
| | - Steven E. Williams
- Biomedical Engineering and Imaging Sciences, King’s College London, United Kingdom (O.R., I.S., C.H.R., R.K., H.C., J.W., L.O., R.M., M.O., S.E.W., S.N.)
| | - Steven Niederer
- Biomedical Engineering and Imaging Sciences, King’s College London, United Kingdom (O.R., I.S., C.H.R., R.K., H.C., J.W., L.O., R.M., M.O., S.E.W., S.N.)
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11
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Roney CH, Beach ML, Mehta AM, Sim I, Corrado C, Bendikas R, Solis-Lemus JA, Razeghi O, Whitaker J, O’Neill L, Plank G, Vigmond E, Williams SE, O’Neill MD, Niederer SA. In silico Comparison of Left Atrial Ablation Techniques That Target the Anatomical, Structural, and Electrical Substrates of Atrial Fibrillation. Front Physiol 2020; 11:1145. [PMID: 33041850 PMCID: PMC7526475 DOI: 10.3389/fphys.2020.572874] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Accepted: 08/18/2020] [Indexed: 12/17/2022] Open
Abstract
Catheter ablation therapy for persistent atrial fibrillation (AF) typically includes pulmonary vein isolation (PVI) and may include additional ablation lesions that target patient-specific anatomical, electrical, or structural features. Clinical centers employ different ablation strategies, which use imaging data together with electroanatomic mapping data, depending on data availability. The aim of this study was to compare ablation techniques across a virtual cohort of AF patients. We constructed 20 paroxysmal and 30 persistent AF patient-specific left atrial (LA) bilayer models incorporating fibrotic remodeling from late-gadolinium enhancement (LGE) MRI scans. AF was simulated and post-processed using phase mapping to determine electrical driver locations over 15 s. Six different ablation approaches were tested: (i) PVI alone, modeled as wide-area encirclement of the pulmonary veins; PVI together with: (ii) roof and inferior lines to model posterior wall box isolation; (iii) isolating the largest fibrotic area (identified by LGE-MRI); (iv) isolating all fibrotic areas; (v) isolating the largest driver hotspot region [identified as high simulated phase singularity (PS) density]; and (vi) isolating all driver hotspot regions. Ablation efficacy was assessed to predict optimal ablation therapies for individual patients. We subsequently trained a random forest classifier to predict ablation response using (a) imaging metrics alone, (b) imaging and electrical metrics, or (c) imaging, electrical, and ablation lesion metrics. The optimal ablation approach resulting in termination, or if not possible atrial tachycardia (AT), varied among the virtual patient cohort: (i) 20% PVI alone, (ii) 6% box ablation, (iii) 2% largest fibrosis area, (iv) 4% all fibrosis areas, (v) 2% largest driver hotspot, and (vi) 46% all driver hotspots. Around 20% of cases remained in AF for all ablation strategies. The addition of patient-specific and ablation pattern specific lesion metrics to the trained random forest classifier improved predictive capability from an accuracy of 0.73 to 0.83. The trained classifier results demonstrate that the surface areas of pre-ablation driver regions and of fibrotic tissue not isolated by the proposed ablation strategy are both important for predicting ablation outcome. Overall, our study demonstrates the need to select the optimal ablation strategy for each patient. It suggests that both patient-specific fibrosis properties and driver locations are important for planning ablation approaches, and the distribution of lesions is important for predicting an acute response.
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Affiliation(s)
- Caroline H. Roney
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Marianne L. Beach
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Arihant M. Mehta
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Iain Sim
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Cesare Corrado
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Rokas Bendikas
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Jose A. Solis-Lemus
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Orod Razeghi
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - John Whitaker
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Louisa O’Neill
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Gernot Plank
- Department of Biophysics, Medical University of Graz, Graz, Austria
| | - Edward Vigmond
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Bordeaux, France
| | - Steven E. Williams
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Mark D. O’Neill
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Steven A. Niederer
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
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12
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Roy A, Varela M, Chubb H, MacLeod R, Hancox JC, Schaeffter T, Aslanidi O. Identifying locations of re-entrant drivers from patient-specific distribution of fibrosis in the left atrium. PLoS Comput Biol 2020; 16:e1008086. [PMID: 32966275 PMCID: PMC7535127 DOI: 10.1371/journal.pcbi.1008086] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Revised: 10/05/2020] [Accepted: 06/22/2020] [Indexed: 11/18/2022] Open
Abstract
Clinical evidence suggests a link between fibrosis in the left atrium (LA) and atrial fibrillation (AF), the most common sustained arrhythmia. Image-derived fibrosis is increasingly used for patient stratification and therapy guidance. However, locations of re-entrant drivers (RDs) sustaining AF are unknown and therapy success rates remain suboptimal. This study used image-derived LA models to explore the dynamics of RD stabilization in fibrotic regions and generate maps of RD locations. LA models with patient-specific geometry and fibrosis distribution were derived from late gadolinium enhanced magnetic resonance imaging of 6 AF patients. In each model, RDs were initiated at multiple locations, and their trajectories were tracked and overlaid on the LA fibrosis distributions to identify the most likely regions where the RDs stabilized. The simulations showed that the RD dynamics were strongly influenced by the amount and spatial distribution of fibrosis. In patients with fibrosis burden greater than 25%, RDs anchored to specific locations near large fibrotic patches. In patients with fibrosis burden below 25%, RDs either moved near small fibrotic patches or anchored to anatomical features. The patient-specific maps of RD locations showed that areas that harboured the RDs were much smaller than the entire fibrotic areas, indicating potential targets for ablation therapy. Ablating the predicted locations and connecting them to the existing pulmonary vein ablation lesions was the most effective in-silico ablation strategy.
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Affiliation(s)
- Aditi Roy
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
| | - Marta Varela
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Henry Chubb
- Cardiothoracic Surgery, Stanford University, United States of America
| | - Robert MacLeod
- Bioengineering Department, University of Utah, Salt Lake City, Utah, United States of America
| | - Jules C. Hancox
- School of Physiology and Pharmacology, Cardiovascular Research Laboratories, University of Bristol, Bristol, United Kingdom
| | | | - Oleg Aslanidi
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
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13
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Habibi M, Chrispin J, Spragg DD, Zimmerman SL, Tandri H, Nazarian S, Halperin H, Trayanova N, Calkins H. Utility of Cardiac MRI in Atrial Fibrillation Management. Card Electrophysiol Clin 2020; 12:131-139. [PMID: 32451098 DOI: 10.1016/j.ccep.2020.02.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Advances in cardiac magnetic resonance (CMR) techniques and image acquisition have made it an excellent tool in the assessment of atrial myopathy. Remolding of the left atrium is the mainstay of atrial fibrillation (AF) development and its progression. CMR can detect phasic atrial volumes, atrial function, and atrial fibrosis using cine, and contrast-enhanced or non-contrast-enhanced images. These abilities make CMR a versatile and extraordinary tool in management of patients with AF including for risk stratification, ablation prognostication and planning, and assessment of stroke risk. We review the latest advancements in utility of CMR in management of patients with AF.
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Affiliation(s)
- Mohammadali Habibi
- Division of Cardiology, Section for Cardiac Electrophysiology, Johns Hopkins University, Baltimore, MD, USA
| | - Jonathan Chrispin
- Division of Cardiology, Section for Cardiac Electrophysiology, Johns Hopkins University, Baltimore, MD, USA
| | - David D Spragg
- Division of Cardiology, Section for Cardiac Electrophysiology, Johns Hopkins University, Baltimore, MD, USA
| | | | - Harikrishna Tandri
- Division of Cardiology, Section for Cardiac Electrophysiology, Johns Hopkins University, Baltimore, MD, USA
| | - Saman Nazarian
- Division of Cardiology, Section for Cardiac Electrophysiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Henry Halperin
- Division of Cardiology, Section for Cardiac Electrophysiology, Johns Hopkins University, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Natalia Trayanova
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Hugh Calkins
- Division of Cardiology, Section for Cardiac Electrophysiology, Johns Hopkins University, Baltimore, MD, USA.
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14
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Mulder MJ, Kemme MJB, Visser CL, Hopman LHGA, van Diemen PA, van de Ven PM, Götte MJW, Danad I, Knaapen P, van Rossum AC, Allaart CP. Left atrial sphericity as a marker of atrial remodeling: Comparison of atrial fibrillation patients and controls. Int J Cardiol 2020; 304:69-74. [PMID: 32005449 DOI: 10.1016/j.ijcard.2020.01.042] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Revised: 01/07/2020] [Accepted: 01/20/2020] [Indexed: 12/19/2022]
Abstract
BACKGROUND Left atrial (LA) sphericity has been proposed as a more sensitive marker of atrial fibrillation (AF)-associated atrial remodeling compared to traditional markers such as LA size. However, mechanisms that underlie changes in LA sphericity are not fully understood and studies investigating the predictive value of LA sphericity for AF ablation outcome have yielded conflicting results. The present study aimed to assess correlates of LA sphericity and to compare LA sphericity in subjects with and without AF. METHODS Measures of LA size (LA diameter, LA volume, LA volume index), LA sphericity and thoracic anteroposterior diameter (APd) at the level of the LA were determined using computed tomography (CT) imaging data in 293 AF patients (62% paroxysmal AF) and 110 controls. RESULTS LA diameter (40.1 ± 6.8 mm vs. 35.2 ± 5.1 mm; p < 0.001), LA volume (116.0 ± 33.0 ml vs. 80.3 ± 22.6 ml; p < 0.001) and LA volume index (56.1 ± 15.3 ml/m2 vs. 41.6 ± 11.1 ml/m2; p < 0.001) were significantly larger in AF patients compared to controls, also after adjustment for covariates. LA sphericity did not differ between AF patients and controls (83.7 ± 2.9 vs. 83.9 ± 2.4; p = 0.642). Multivariable linear regression analysis demonstrated that LA diameter, LA volume, female sex, body length and thoracic APd were independently associated with LA sphericity. CONCLUSIONS The present study suggests that thoracic constraints rather than the presence of AF determine LA sphericity, implying LA sphericity to be unsuitable as a marker of AF-related atrial remodeling.
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Affiliation(s)
- Mark J Mulder
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Michiel J B Kemme
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Charlotte L Visser
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Luuk H G A Hopman
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Pepijn A van Diemen
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Peter M van de Ven
- Department of Epidemiology and Biostatistics, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Marco J W Götte
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Ibrahim Danad
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Paul Knaapen
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Albert C van Rossum
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Cornelis P Allaart
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands.
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15
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Left Atrial Structural Remodelling in Non-Valvular Atrial Fibrillation: What Have We Learnt from CMR? Diagnostics (Basel) 2020; 10:diagnostics10030137. [PMID: 32131455 PMCID: PMC7151417 DOI: 10.3390/diagnostics10030137] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2020] [Revised: 02/20/2020] [Accepted: 02/27/2020] [Indexed: 12/28/2022] Open
Abstract
Left atrial structural, functional and electrical remodelling are linked to atrial fibrillation (AF) pathophysiology and mirror the phrase “AF begets AF”. A structurally remodelled left atrium (LA) is fibrotic, dysfunctional and enlarged. Fibrosis is the hallmark of LA structural remodelling and is associated with increased risk of stroke, heart failure development and/or progression and poorer catheter ablation outcomes with increased recurrence rates. Moreover, increased atrial fibrosis has been associated with higher rates of stroke even in sinus-rhythm individuals. As such, properly assessing the fibrotic atrial cardiomyopathy in AF patients becomes necessary. In this respect, late-gadolinium enhancement cardiac magnetic resonance (LGE-CMR) imaging is the gold standard in imaging myocardial fibrosis. LA structural remodelling extension offers both diagnostic and prognostic information and influences therapeutic choices. LGE-CMR scans can be used before the procedure to better select candidates and to aid in choosing the ablation technique, during the procedure (full CMR-guided ablations) and after the ablation (to assess the ablation scar). This review focuses on imaging several LA structural remodelling CMR parameters, including size, shape and fibrosis (both extension and architecture) and their impact on procedure outcomes, recurrence risk, as well as their utility in relation to the index procedure timing.
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16
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Packer M. Potential Role of Atrial Myopathy in the Pathogenesis of Stroke in Rheumatoid Arthritis and Psoriasis: A Conceptual Framework and Implications for Prophylaxis. J Am Heart Assoc 2020; 9:e014764. [PMID: 31973602 PMCID: PMC7033881 DOI: 10.1161/jaha.119.014764] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Milton Packer
- Baylor Heart and Vascular Institute Baylor University Medical Center Dallas TX.,Imperial College London United Kingdom
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