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Zhang Q, Fotaki A, Ghadimi S, Wang Y, Doneva M, Wetzl J, Delfino JG, O'Regan DP, Prieto C, Epstein FH. Improving the efficiency and accuracy of cardiovascular magnetic resonance with artificial intelligence-review of evidence and proposition of a roadmap to clinical translation. J Cardiovasc Magn Reson 2024; 26:101051. [PMID: 38909656 DOI: 10.1016/j.jocmr.2024.101051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2024] [Revised: 06/09/2024] [Accepted: 06/18/2024] [Indexed: 06/25/2024] Open
Abstract
BACKGROUND Cardiovascular magnetic resonance (CMR) is an important imaging modality for the assessment of heart disease; however, limitations of CMR include long exam times and high complexity compared to other cardiac imaging modalities. Recently advancements in artificial intelligence (AI) technology have shown great potential to address many CMR limitations. While the developments are remarkable, translation of AI-based methods into real-world CMR clinical practice remains at a nascent stage and much work lies ahead to realize the full potential of AI for CMR. METHODS Herein we review recent cutting-edge and representative examples demonstrating how AI can advance CMR in areas such as exam planning, accelerated image reconstruction, post-processing, quality control, classification and diagnosis. RESULTS These advances can be applied to speed up and simplify essentially every application including cine, strain, late gadolinium enhancement, parametric mapping, 3D whole heart, flow, perfusion and others. AI is a unique technology based on training models using data. Beyond reviewing the literature, this paper discusses important AI-specific issues in the context of CMR, including (1) properties and characteristics of datasets for training and validation, (2) previously published guidelines for reporting CMR AI research, (3) considerations around clinical deployment, (4) responsibilities of clinicians and the need for multi-disciplinary teams in the development and deployment of AI in CMR, (5) industry considerations, and (6) regulatory perspectives. CONCLUSIONS Understanding and consideration of all these factors will contribute to the effective and ethical deployment of AI to improve clinical CMR.
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Affiliation(s)
- Qiang Zhang
- Oxford Centre for Clinical Magnetic Resonance Research, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK; Big Data Institute, University of Oxford, Oxford, UK.
| | - Anastasia Fotaki
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Royal Brompton Hospital, Guy's and St Thomas' NHS Foundation Trust, London, UK.
| | - Sona Ghadimi
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.
| | - Yu Wang
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.
| | | | - Jens Wetzl
- Siemens Healthineers AG, Erlangen, Germany.
| | - Jana G Delfino
- US Food and Drug Administration, Center for Devices and Radiological Health (CDRH), Office of Science and Engineering Laboratories (OSEL), Silver Spring, MD, USA.
| | - Declan P O'Regan
- MRC Laboratory of Medical Sciences, Imperial College London, London, UK.
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile.
| | - Frederick H Epstein
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.
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Gertz RJ, Wagner A, Sokolowski M, Lennartz S, Gietzen C, Grunz JP, Goertz L, Kaya K, ten Freyhaus H, Persigehl T, Bunck AC, Doerner J, Naehle CP, Maintz D, Weiss K, Katemann C, Pennig L. Compressed SENSE accelerated 3D single-breath-hold late gadolinium enhancement cardiovascular magnetic resonance with isotropic resolution: clinical evaluation. Front Cardiovasc Med 2023; 10:1305649. [PMID: 38099228 PMCID: PMC10720442 DOI: 10.3389/fcvm.2023.1305649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Accepted: 11/17/2023] [Indexed: 12/17/2023] Open
Abstract
Aim The purpose of this study was to investigate the clinical application of Compressed SENSE accelerated single-breath-hold LGE with 3D isotropic resolution compared to conventional LGE imaging acquired in multiple breath-holds. Material & Methods This was a retrospective, single-center study including 105 examinations of 101 patients (48.2 ± 16.8 years, 47 females). All patients underwent conventional breath-hold and 3D single-breath-hold (0.96 × 0.96 × 1.1 mm3 reconstructed voxel size, Compressed SENSE factor 6.5) LGE sequences at 1.5 T in clinical routine for the evaluation of ischemic or non-ischemic cardiomyopathies. Two radiologists independently evaluated the left ventricle (LV) for the presence of hyperenhancing lesions in each sequence, including localization and transmural extent, while assessing their scar edge sharpness (SES). Confidence of LGE assessment, image quality (IQ), and artifacts were also rated. The impact of LV ejection fraction (LVEF), heart rate, body mass index (BMI), and gender as possible confounders on IQ, artifacts, and confidence of LGE assessment was evaluated employing ordinal logistic regression analysis. Results Using 3D single-breath-hold LGE readers detected more hyperenhancing lesions compared to conventional breath-hold LGE (n = 246 vs. n = 216 of 1,785 analyzed segments, 13.8% vs. 12.1%; p < 0.0001), pronounced at subendocardial, midmyocardial, and subepicardial localizations and for 1%-50% of transmural extent. SES was rated superior in 3D single-breath-hold LGE (4.1 ± 0.8 vs. 3.3 ± 0.8; p < 0.001). 3D single-breath-hold LGE yielded more artifacts (3.8 ± 1.0 vs. 4.0 ± 3.8; p = 0.002) whereas IQ (4.1 ± 1.0 vs. 4.2 ± 0.9; p = 0.122) and confidence of LGE assessment (4.3 ± 0.9 vs. 4.3 ± 0.8; p = 0.374) were comparable between both techniques. Female gender negatively influenced artifacts in 3D single-breath-hold LGE (p = 0.0028) while increased heart rate led to decreased IQ in conventional breath-hold LGE (p = 0.0029). Conclusions In clinical routine, Compressed SENSE accelerated 3D single-breath-hold LGE yields image quality and confidence of LGE assessment comparable to conventional breath-hold LGE while providing improved delineation of smaller LGE lesions with superior scar edge sharpness. Given the fast acquisition of 3D single-breath-hold LGE, the technique holds potential to drastically reduce the examination time of CMR.
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Affiliation(s)
- Roman Johannes Gertz
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Anton Wagner
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Institute for Diagnostic and Interventional Radiology, Krankenhaus der Augustinerinnen, Cologne, Germany
| | - Marcel Sokolowski
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Simon Lennartz
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Carsten Gietzen
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Jan-Peter Grunz
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany
| | - Lukas Goertz
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Kenan Kaya
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Henrik ten Freyhaus
- Department III of Internal Medicine, Heart Center, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Thorsten Persigehl
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Alexander Christian Bunck
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Jonas Doerner
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Kontraste Radiologie-Praxis Köln West, Cologne, Germany
| | - Claas Philip Naehle
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Radiologische Allianz Hamburg, Hamburg, Germany
| | - David Maintz
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | | | | | - Lenhard Pennig
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
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Munoz C, Fotaki A, Botnar RM, Prieto C. Latest Advances in Image Acceleration: All Dimensions are Fair Game. J Magn Reson Imaging 2023; 57:387-402. [PMID: 36205716 PMCID: PMC10092100 DOI: 10.1002/jmri.28462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 09/20/2022] [Accepted: 09/22/2022] [Indexed: 01/20/2023] Open
Abstract
Magnetic resonance imaging (MRI) is a versatile modality that can generate high-resolution images with a variety of tissue contrasts. However, MRI is a slow technique and requires long acquisition times, which increase with higher temporal and spatial resolution and/or when multiple contrasts and large volumetric coverage is required. In order to speedup MR data acquisition, several approaches have been introduced in the literature. Most of these techniques acquire less data than required and exploit intrinsic redundancies in the MR images to recover the information that was not sampled. This article presents a review of MR acquisition and reconstruction methods that have exploited redundancies in the temporal, spatial, and contrast/parametric dimensions to accelerate image data acquisition, focusing on cardiac and abdominal MR imaging applications. The review describes how each of these dimensions has been separately exploited for speeding up MR acquisition to then discuss more advanced techniques where multiple dimensions are exploited together for further reducing scan times. Finally, future directions for multidimensional image acceleration and remaining technical challenges are discussed. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: 1.
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Affiliation(s)
- Camila Munoz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Anastasia Fotaki
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - René M Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile.,Millenium Institute for Intelligent Healthcare Engineering iHEALTH, Santiago, Chile
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile.,Millenium Institute for Intelligent Healthcare Engineering iHEALTH, Santiago, Chile
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Abstract
Myocardial inflammation occurs following activation of the cardiac immune system, producing characteristic changes in the myocardial tissue. Cardiovascular magnetic resonance is the non-invasive imaging gold standard for myocardial tissue characterization, and is able to detect image signal changes that may occur resulting from inflammation, including edema, hyperemia, capillary leak, necrosis, and fibrosis. Conventional cardiovascular magnetic resonance for the detection of myocardial inflammation and its sequela include T2-weighted imaging, parametric T1- and T2-mapping, and gadolinium-based contrast-enhanced imaging. Emerging techniques seek to image several parameters simultaneously for myocardial tissue characterization, and to depict subtle immune-mediated changes, such as immune cell activity in the myocardium and cardiac cell metabolism. This review article outlines the underlying principles of current and emerging cardiovascular magnetic resonance methods for imaging myocardial inflammation.
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Affiliation(s)
- Katharine E Thomas
- University of Oxford Centre for Clinical Magnetic Resonance Research (OCMR), Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom (K.E.T., V.M.F.)
| | - Anastasia Fotaki
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, United Kingdom (A.F., R.M.B.)
| | - René M Botnar
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, United Kingdom (A.F., R.M.B.)
- Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B.)
- Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.M.B.)
| | - Vanessa M Ferreira
- University of Oxford Centre for Clinical Magnetic Resonance Research (OCMR), Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom (K.E.T., V.M.F.)
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Eyre K, Lindsay K, Razzaq S, Chetrit M, Friedrich M. Simultaneous multi-parametric acquisition and reconstruction techniques in cardiac magnetic resonance imaging: Basic concepts and status of clinical development. Front Cardiovasc Med 2022; 9:953823. [PMID: 36277755 PMCID: PMC9582154 DOI: 10.3389/fcvm.2022.953823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 09/22/2022] [Indexed: 11/13/2022] Open
Abstract
Simultaneous multi-parametric acquisition and reconstruction techniques (SMART) are gaining attention for their potential to overcome some of cardiovascular magnetic resonance imaging's (CMR) clinical limitations. The major advantages of SMART lie within their ability to simultaneously capture multiple "features" such as cardiac motion, respiratory motion, T1/T2 relaxation. This review aims to summarize the overarching theory of SMART, describing key concepts that many of these techniques share to produce co-registered, high quality CMR images in less time and with less requirements for specialized personnel. Further, this review provides an overview of the recent developments in the field of SMART by describing how they work, the parameters they can acquire, their status of clinical testing and validation, and by providing examples for how their use can improve the current state of clinical CMR workflows. Many of the SMART are in early phases of development and testing, thus larger scale, controlled trials are needed to evaluate their use in clinical setting and with different cardiac pathologies.
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Affiliation(s)
- Katerina Eyre
- McGill University Health Centre, Montreal, QC, Canada,Department of Experimental Medicine, McGill University, Montreal, QC, Canada,*Correspondence: Katerina Eyre,
| | - Katherine Lindsay
- McGill University Health Centre, Montreal, QC, Canada,Department of Experimental Medicine, McGill University, Montreal, QC, Canada
| | - Saad Razzaq
- Department of Experimental Medicine, McGill University, Montreal, QC, Canada
| | - Michael Chetrit
- McGill University Health Centre, Montreal, QC, Canada,Department of Experimental Medicine, McGill University, Montreal, QC, Canada
| | - Matthias Friedrich
- McGill University Health Centre, Montreal, QC, Canada,Department of Experimental Medicine, McGill University, Montreal, QC, Canada
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Sridi S, Nuñez-Garcia M, Sermesant M, Maillot A, Hamrani DE, Magat J, Naulin J, Laurent F, Montaudon M, Jaïs P, Stuber M, Cochet H, Bustin A. Improved myocardial scar visualization with fast free-breathing motion-compensated black-blood T 1-rho-prepared late gadolinium enhancement MRI. Diagn Interv Imaging 2022; 103:607-617. [PMID: 35961843 DOI: 10.1016/j.diii.2022.07.003] [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: 04/27/2022] [Revised: 07/12/2022] [Accepted: 07/19/2022] [Indexed: 11/19/2022]
Abstract
PURPOSE Clinical guidelines recommend the use of bright-blood late gadolinium enhancement (BR-LGE) for the detection and quantification of regional myocardial fibrosis and scar. This technique, however, may suffer from poor contrast at the blood-scar interface, particularly in patients with subendocardial myocardial infarction. The purpose of this study was to assess the clinical performance of a two-dimensional black-blood LGE (BL-LGE) sequence, which combines free-breathing T1-rho-prepared single-shot acquisitions with an advanced non-rigid motion-compensated patch-based reconstruction. MATERIALS AND METHODS Extended phase graph simulations and phantom experiments were performed to investigate the performance of the motion-correction algorithm and to assess the black-blood properties of the proposed sequence. Fifty-one patients (37 men, 14 women; mean age, 55 ± 15 [SD] years; age range: 19-81 years) with known or suspected cardiac disease prospectively underwent free-breathing T1-rho-prepared BL-LGE imaging with inline non-rigid motion-compensated patch-based reconstruction at 1.5T. Conventional breath-held BR-LGE images were acquired for comparison purposes. Acquisition times were recorded. Two readers graded the image quality and relative contrasts were calculated. Presence, location, and extent of LGE were evaluated. RESULTS BL-LGE images were acquired with full ventricular coverage in 115 ± 25 (SD) sec (range: 64-160 sec). Image quality was significantly higher on free-breathing BL-LGE imaging than on its breath-held BR-LGE counterpart (3.6 ± 0.7 [SD] [range: 2-4] vs. 3.9 ± 0.2 [SD] [range: 3-4]) (P <0.01) and was graded as diagnostic for 44/51 (86%) patients. The mean scar-to-myocardium and scar-to-blood relative contrasts were significantly higher on BL-LGE images (P < 0.01 for both). The extent of LGE was larger on BL-LGE (median, 5 segments [IQR: 2, 7 segments] vs. median, 4 segments [IQR: 1, 6 segments]) (P < 0.01), the method being particularly sensitive in segments with LGE involving the subendocardium or papillary muscles. In eight patients (16%), BL-LGE could ascertain or rule out a diagnosis otherwise inconclusive on BR-LGE. CONCLUSION Free-breathing T1-rho-prepared BL-LGE imaging with inline motion compensated reconstruction offers a promising diagnostic technology for the non-invasive assessment of myocardial injuries.
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Affiliation(s)
- Soumaya Sridi
- Department of Cardiovascular Imaging, Groupe Hospitalier Sud, CHU Bordeaux, 33000, Pessac, France.
| | - Marta Nuñez-Garcia
- IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, INSERM U1045, 33600, Pessac, France
| | - Maxime Sermesant
- IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, INSERM U1045, 33600, Pessac, France; INRIA, Université Côte d'Azur, Sophia Antipolis, 06902, Valbonne, France
| | - Aurélien Maillot
- IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, INSERM U1045, 33600, Pessac, France
| | - Dounia El Hamrani
- IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, INSERM U1045, 33600, Pessac, France
| | - Julie Magat
- IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, INSERM U1045, 33600, Pessac, France
| | - Jérôme Naulin
- IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, INSERM U1045, 33600, Pessac, France
| | - François Laurent
- Department of Cardiovascular Imaging, Groupe Hospitalier Sud, CHU Bordeaux, 33000, Pessac, France
| | - Michel Montaudon
- Department of Cardiovascular Imaging, Groupe Hospitalier Sud, CHU Bordeaux, 33000, Pessac, France
| | - Pierre Jaïs
- IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, INSERM U1045, 33600, Pessac, France; Department of Cardiac Electrophysiologhy, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, 33600, Pessac, France
| | - Matthias Stuber
- IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, INSERM U1045, 33600, Pessac, France; Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, 1011, Lausanne, Switzerland; Center for Biomedical Imaging (CIBM), 1015, Lausanne, Switzerland
| | - Hubert Cochet
- Department of Cardiovascular Imaging, Groupe Hospitalier Sud, CHU Bordeaux, 33000, Pessac, France; IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, INSERM U1045, 33600, Pessac, France
| | - Aurélien Bustin
- Department of Cardiovascular Imaging, Groupe Hospitalier Sud, CHU Bordeaux, 33000, Pessac, France; IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, INSERM U1045, 33600, Pessac, France; Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, 1011, Lausanne, Switzerland
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Fenski M, Grandy TH, Viezzer D, Kertusha S, Schmidt M, Forman C, Schulz-Menger J. Isotropic 3D compressed sensing (CS) based sequence is comparable to 2D-LGE in left ventricular scar quantification in different disease entities. Int J Cardiovasc Imaging 2022; 38:1837-1850. [PMID: 35243574 PMCID: PMC10509092 DOI: 10.1007/s10554-022-02571-6] [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: 10/26/2021] [Accepted: 02/14/2022] [Indexed: 11/27/2022]
Abstract
The goal of this study was to evaluate a three-dimensional compressed sensing (3D-CS) LGE prototype sequence for the detection and quantification of myocardial fibrosis in patients with chronic myocardial infarction (CMI) and myocarditis (MYC) compared with a 2D-LGE standard. Patients with left-ventricular LGE due to CMI (n = 33) or MYC (n = 20) were prospectively recruited. 2D-LGE and 3D-CS images were acquired in random order at 1.5 Tesla. 3D-CS short axis (SAX) images were reconstructed corresponding to 2D SAX images. LGE was quantitatively assessed on patient and segment level using semi-automated threshold methods. Image quality (4-point scoring system), Contrast-ratio (CR) and acquisition times were compared. There was no significant difference between 2D and 3D sequences regarding global LGE (%) (CMI [2D-LGE: 11.4 ± 7.5; 3D-LGE: 11.5 ± 8.5; p = 0.99]; MYC [2D-LGE: 27.0 ± 15.7; 3D-LGE: 26.2 ± 13.1; p = 0.70]) and segmental LGE-extent (p = 0.63). 3D-CS identified papillary infarction in 5 cases which was not present in 2D images. 2D-LGE acquisition time was shorter (2D: median: 06:59 min [IQR: 05:51-08:18]; 3D: 14:48 min [12:45-16:57]). 3D-CS obtained better quality scores (2D: 2.06 ± 0.56 vs. 3D: 2.29 ± 0.61). CR did not differ (p = 0.63) between basal and apical regions in 3D-CS images but decreased significantly in 2D apical images (CR basal: 2D: 0.77 ± 0.11, 3D: 0.59 ± 0.10; CR apical: 2D: 0.64 ± 0.17, 3D: 0.53 ± 0.11). 3D-LGE shows high congruency with standard LGE and allows better identification of small lesions. However, the current 3D-CS LGE sequence did not provide PSIR reconstruction and acquisition time was longer.
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Affiliation(s)
- Maximilian Fenski
- Working Group Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, Charité Medical Faculty, Max-Delbrück Center for Molecular Medicine, Helios Klinikum Berlin Buch, Department of Cardiology and Nephrology, Charité - Universitätsmedizin Berlin, Kardiologie - ECRC, Lindenberger Weg 80, 13125, Berlin, Germany
| | - Thomas Hiroshi Grandy
- Working Group Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, Charité Medical Faculty, Max-Delbrück Center for Molecular Medicine, Helios Klinikum Berlin Buch, Department of Cardiology and Nephrology, Charité - Universitätsmedizin Berlin, Kardiologie - ECRC, Lindenberger Weg 80, 13125, Berlin, Germany
| | - Darian Viezzer
- Working Group Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, Charité Medical Faculty, Max-Delbrück Center for Molecular Medicine, Helios Klinikum Berlin Buch, Department of Cardiology and Nephrology, Charité - Universitätsmedizin Berlin, Kardiologie - ECRC, Lindenberger Weg 80, 13125, Berlin, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site Berlin, Berlin, Germany
| | - Stela Kertusha
- Working Group Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, Charité Medical Faculty, Max-Delbrück Center for Molecular Medicine, Helios Klinikum Berlin Buch, Department of Cardiology and Nephrology, Charité - Universitätsmedizin Berlin, Kardiologie - ECRC, Lindenberger Weg 80, 13125, Berlin, Germany
| | | | | | - Jeanette Schulz-Menger
- Working Group Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, Charité Medical Faculty, Max-Delbrück Center for Molecular Medicine, Helios Klinikum Berlin Buch, Department of Cardiology and Nephrology, Charité - Universitätsmedizin Berlin, Kardiologie - ECRC, Lindenberger Weg 80, 13125, Berlin, Germany.
- DZHK (German Center for Cardiovascular Research), Partner Site Berlin, Berlin, Germany.
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8
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Argentiero A, Muscogiuri G, Rabbat MG, Martini C, Soldato N, Basile P, Baggiano A, Mushtaq S, Fusini L, Mancini ME, Gaibazzi N, Santobuono VE, Sironi S, Pontone G, Guaricci AI. The Applications of Artificial Intelligence in Cardiovascular Magnetic Resonance-A Comprehensive Review. J Clin Med 2022; 11:jcm11102866. [PMID: 35628992 PMCID: PMC9147423 DOI: 10.3390/jcm11102866] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 05/13/2022] [Accepted: 05/16/2022] [Indexed: 12/11/2022] Open
Abstract
Cardiovascular disease remains an integral field on which new research in both the biomedical and technological fields is based, as it remains the leading cause of mortality and morbidity worldwide. However, despite the progress of cardiac imaging techniques, the heart remains a challenging organ to study. Artificial intelligence (AI) has emerged as one of the major innovations in the field of diagnostic imaging, with a dramatic impact on cardiovascular magnetic resonance imaging (CMR). AI will be increasingly present in the medical world, with strong potential for greater diagnostic efficiency and accuracy. Regarding the use of AI in image acquisition and reconstruction, the main role was to reduce the time of image acquisition and analysis, one of the biggest challenges concerning magnetic resonance; moreover, it has been seen to play a role in the automatic correction of artifacts. The use of these techniques in image segmentation has allowed automatic and accurate quantification of the volumes and masses of the left and right ventricles, with occasional need for manual correction. Furthermore, AI can be a useful tool to directly help the clinician in the diagnosis and derivation of prognostic information of cardiovascular diseases. This review addresses the applications and future prospects of AI in CMR imaging, from image acquisition and reconstruction to image segmentation, tissue characterization, diagnostic evaluation, and prognostication.
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Affiliation(s)
- Adriana Argentiero
- University Cardiology Unit, Cardio-Thoracic Department, Policlinic University Hospital, 70121 Bari, Italy; (A.A.); (N.S.); (P.B.); (V.E.S.)
| | - Giuseppe Muscogiuri
- School of Medicine and Surgery, University of Milano-Bicocca, 20126 Milan, Italy; (G.M.); (S.S.)
- Department of Radiology, IRCCS Istituto Auxologico Italiano, San Luca Hospital, 20149 Milan, Italy
| | - Mark G. Rabbat
- Division of Cardiology, Loyola University of Chicago, Chicago, IL 60660, USA;
| | - Chiara Martini
- Radiologic Sciences, Department of Medicine and Surgery, University of Parma, 43126 Parma, Italy;
| | - Nicolò Soldato
- University Cardiology Unit, Cardio-Thoracic Department, Policlinic University Hospital, 70121 Bari, Italy; (A.A.); (N.S.); (P.B.); (V.E.S.)
| | - Paolo Basile
- University Cardiology Unit, Cardio-Thoracic Department, Policlinic University Hospital, 70121 Bari, Italy; (A.A.); (N.S.); (P.B.); (V.E.S.)
| | - Andrea Baggiano
- Perioperative and Cardiovascular Imaging Department, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy; (A.B.); (S.M.); (L.F.); (M.E.M.); (G.P.)
| | - Saima Mushtaq
- Perioperative and Cardiovascular Imaging Department, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy; (A.B.); (S.M.); (L.F.); (M.E.M.); (G.P.)
| | - Laura Fusini
- Perioperative and Cardiovascular Imaging Department, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy; (A.B.); (S.M.); (L.F.); (M.E.M.); (G.P.)
| | - Maria Elisabetta Mancini
- Perioperative and Cardiovascular Imaging Department, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy; (A.B.); (S.M.); (L.F.); (M.E.M.); (G.P.)
| | - Nicola Gaibazzi
- Department of Cardiology, Azienda Ospedaliero-Universitaria, 43126 Parma, Italy;
| | - Vincenzo Ezio Santobuono
- University Cardiology Unit, Cardio-Thoracic Department, Policlinic University Hospital, 70121 Bari, Italy; (A.A.); (N.S.); (P.B.); (V.E.S.)
| | - Sandro Sironi
- School of Medicine and Surgery, University of Milano-Bicocca, 20126 Milan, Italy; (G.M.); (S.S.)
- Department of Radiology, ASST Papa Giovanni XXIII Hospital, 24127 Bergamo, Italy
| | - Gianluca Pontone
- Perioperative and Cardiovascular Imaging Department, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy; (A.B.); (S.M.); (L.F.); (M.E.M.); (G.P.)
| | - Andrea Igoren Guaricci
- University Cardiology Unit, Cardio-Thoracic Department, Policlinic University Hospital, 70121 Bari, Italy; (A.A.); (N.S.); (P.B.); (V.E.S.)
- Department of Emergency and Organ Transplantation, University of Bari, 70121 Bari, Italy
- Correspondence:
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9
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Pradella S, Mazzoni LN, Letteriello M, Tortoli P, Bettarini S, De Amicis C, Grazzini G, Busoni S, Palumbo P, Belli G, Miele V. FLORA software: semi-automatic LGE-CMR analysis tool for cardiac lesions identification and characterization. Radiol Med 2022; 127:589-601. [DOI: 10.1007/s11547-022-01491-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 03/23/2022] [Indexed: 10/18/2022]
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10
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Malik N, Mukherjee M, Wu KC, Zimmerman SL, Zhan J, Calkins H, James CA, Gilotra NA, Sheikh FH, Tandri H, Kutty S, Hays AG. Multimodality Imaging in Arrhythmogenic Right Ventricular Cardiomyopathy. Circ Cardiovasc Imaging 2022; 15:e013725. [PMID: 35147040 DOI: 10.1161/circimaging.121.013725] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a rare, heritable myocardial disease associated with the development of ventricular arrhythmias, heart failure, and sudden cardiac death in early adulthood. Multimodality imaging is a central component in the diagnosis and evaluation of ARVC. Diagnostic criteria established by an international task force in 2010 include noninvasive parameters from echocardiography and cardiac magnetic resonance imaging. These criteria identify right ventricular structural abnormalities, chamber and outflow tract dilation, and reduced right ventricular function as features of ARVC. Echocardiography is a widely available and cost-effective technique, and it is often selected for initial evaluation. Beyond fulfillment of diagnostic criteria, features such as abnormal tricuspid annular plane excursion, increased right ventricular basal diameter, and abnormal strain patterns have been described. 3-dimensional echocardiography may also expand opportunities for structural and functional assessment of ARVC. Cardiac magnetic resonance has the ability to assess morphological and functional cardiac features of ARVC and is also a core modality in evaluation, however, tissue characterization of the right ventricle is limited by spatial resolution and low specificity for detection of pathological changes. Nonetheless, the ability of cardiac magnetic resonance to identify left ventricular involvement, offer high negative predictive value, and provide a reproducible structural evaluation of the right ventricle enhance the ability and scope of the modality. In this review, the prognostic significance of multimodality imaging is outlined, including the supplemental value of multidetector computed tomography and nuclear imaging. Strengths and weaknesses of imaging techniques, as well as future direction of multimodality assessment, are also described.
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Affiliation(s)
- Nitin Malik
- MedStar Heart and Vascular Institute, MedStar Washington Hospital Center, Washington, DC (N.M., F.H.S.).,Georgetown University, Washington, DC (N.M., F.H.S.)
| | - Monica Mukherjee
- Johns Hopkins University Department of Medicine, Division of Cardiology, Baltimore, MD (M.M., K.C.W., H.C., C.A.J., N.A.G., H.T., A.G.H.)
| | - Katherine C Wu
- Johns Hopkins University Department of Medicine, Division of Cardiology, Baltimore, MD (M.M., K.C.W., H.C., C.A.J., N.A.G., H.T., A.G.H.)
| | - Stefan L Zimmerman
- Johns Hopkins University Department of Radiology, Baltimore, MD (S.L.Z.)
| | - Junzhen Zhan
- Johns Hopkins University Department of Pediatrics, Division of Pediatric Cardiology, Baltimore, MD (J.Z., S.K.)
| | - Hugh Calkins
- Johns Hopkins University Department of Medicine, Division of Cardiology, Baltimore, MD (M.M., K.C.W., H.C., C.A.J., N.A.G., H.T., A.G.H.)
| | - Cynthia A James
- Johns Hopkins University Department of Medicine, Division of Cardiology, Baltimore, MD (M.M., K.C.W., H.C., C.A.J., N.A.G., H.T., A.G.H.)
| | - Nisha A Gilotra
- Johns Hopkins University Department of Medicine, Division of Cardiology, Baltimore, MD (M.M., K.C.W., H.C., C.A.J., N.A.G., H.T., A.G.H.)
| | - Farooq H Sheikh
- MedStar Heart and Vascular Institute, MedStar Washington Hospital Center, Washington, DC (N.M., F.H.S.).,Georgetown University, Washington, DC (N.M., F.H.S.)
| | - Harikrishna Tandri
- Johns Hopkins University Department of Medicine, Division of Cardiology, Baltimore, MD (M.M., K.C.W., H.C., C.A.J., N.A.G., H.T., A.G.H.)
| | - Shelby Kutty
- Johns Hopkins University Department of Pediatrics, Division of Pediatric Cardiology, Baltimore, MD (J.Z., S.K.)
| | - Allison G Hays
- Johns Hopkins University Department of Medicine, Division of Cardiology, Baltimore, MD (M.M., K.C.W., H.C., C.A.J., N.A.G., H.T., A.G.H.)
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11
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Peters DC, Lamy J, Sinusas AJ, Baldassarre LA. Left atrial evaluation by cardiovascular magnetic resonance: sensitive and unique biomarkers. Eur Heart J Cardiovasc Imaging 2021; 23:14-30. [PMID: 34718484 DOI: 10.1093/ehjci/jeab221] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 10/12/2021] [Indexed: 12/12/2022] Open
Abstract
Left atrial (LA) imaging is still not routinely used for diagnosis and risk stratification, although recent studies have emphasized its importance as an imaging biomarker. Cardiovascular magnetic resonance is able to evaluate LA structure and function, metrics that serve as early indicators of disease, and provide prognostic information, e.g. regarding diastolic dysfunction, and atrial fibrillation (AF). MR angiography defines atrial anatomy, useful for planning ablation procedures, and also for characterizing atrial shapes and sizes that might predict cardiovascular events, e.g. stroke. Long-axis cine images can be evaluated to define minimum, maximum, and pre-atrial contraction LA volumes, and ejection fractions (EFs). More modern feature tracking of these cine images provides longitudinal LA strain through the cardiac cycle, and strain rates. Strain may be a more sensitive marker than EF and can predict post-operative AF, AF recurrence after ablation, outcomes in hypertrophic cardiomyopathy, stratification of diastolic dysfunction, and strain correlates with atrial fibrosis. Using high-resolution late gadolinium enhancement (LGE), the extent of fibrosis in the LA can be estimated and post-ablation scar can be evaluated. The LA LGE method is widely available, its reproducibility is good, and validations with voltage-mapping exist, although further scan-rescan studies are needed, and consensus regarding atrial segmentation is lacking. Using LGE, scar patterns after ablation in AF subjects can be reproducibly defined. Evaluation of 'pre-existent' atrial fibrosis may have roles in predicting AF recurrence after ablation, predicting new-onset AF and diastolic dysfunction in patients without AF. LA imaging biomarkers are ready to enter into diagnostic clinical practice.
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Affiliation(s)
- Dana C Peters
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Jérôme Lamy
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Albert J Sinusas
- Department of Cardiology, Yale School of Medicine, New Haven, CT, USA
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12
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Bustin A, Sridi S, Gravinay P, Legghe B, Gosse P, Ouattara A, Rozé H, Coste P, Gerbaud E, Desclaux A, Boyer A, Prevel R, Gruson D, Bonnet F, Issa N, Montaudon M, Laurent F, Stuber M, Camou F, Cochet H. High-resolution Free-breathing late gadolinium enhancement Cardiovascular magnetic resonance to diagnose myocardial injuries following COVID-19 infection. Eur J Radiol 2021; 144:109960. [PMID: 34600236 PMCID: PMC8450147 DOI: 10.1016/j.ejrad.2021.109960] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 08/30/2021] [Accepted: 09/15/2021] [Indexed: 12/14/2022]
Abstract
PURPOSE High-resolution free-breathing late gadolinium enhancement (HR-LGE) was shown valuable for the diagnosis of acute coronary syndromes with non-obstructed coronary arteries. The method may be useful to detect COVID-related myocardial injuries but is hampered by prolonged acquisition times. We aimed to introduce an accelerated HR-LGE technique for the diagnosis of COVID-related myocardial injuries. METHOD An undersampled navigator-gated HR-LGE (acquired resolution of 1.25 mm3) sequence combined with advanced patch-based low-rank reconstruction was developed and validated in a phantom and in 23 patients with structural heart disease (test cohort; 15 men; 55 ± 16 years). Twenty patients with laboratory-confirmed COVID-19 infection associated with troponin rise (COVID cohort; 15 men; 46 ± 24 years) prospectively underwent cardiovascular magnetic resonance (CMR) with the proposed sequence in our center. Image sharpness, quality, signal intensity differences and diagnostic value of free-breathing HR-LGE were compared against conventional breath-held low-resolution LGE (LR-LGE, voxel size 1.8x1.4x6mm). RESULTS Structures sharpness in the phantom showed no differences with the fully sampled image up to an undersampling factor of x3.8 (P > 0.5). In patients (N = 43), this acceleration allowed for acquisition times of 7min21s ± 1min12s at 1.25 mm3 resolution. Compared with LR-LGE, HR-LGE showed higher image quality (P = 0.03) and comparable signal intensity differences (P > 0.5). In patients with structural heart disease, all LGE-positive segments on LR-LGE were also detected on HR-LGE (80/391) with 21 additional enhanced segments visible only on HR-LGE (101/391, P < 0.001). In 4 patients with COVID-19 history, HR-LGE was definitely positive while LR-LGE was either definitely negative (1 microinfarction and 1 myocarditis) or inconclusive (2 myocarditis). CONCLUSIONS Undersampled free-breathing isotropic HR-LGE can detect additional areas of late enhancement as compared to conventional breath-held LR-LGE. In patients with history of COVID-19 infection associated with troponin rise, the method allows for detailed characterization of myocardial injuries in acceptable scan times and without the need for repeated breath holds.
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Affiliation(s)
- Aurélien Bustin
- Department of Cardiovascular Imaging, Groupe Hospitalier Sud, CHU Bordeaux, Pessac, France; IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux - INSERM U1045, Avenue du Haut Lévêque, Pessac, France; Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
| | - Soumaya Sridi
- Department of Cardiovascular Imaging, Groupe Hospitalier Sud, CHU Bordeaux, Pessac, France
| | - Pierre Gravinay
- Cardiac Intensive Care Unit, Hôpital St André, CHU Bordeaux, Bordeaux, France
| | - Benoit Legghe
- Department of Cardiovascular Imaging, Groupe Hospitalier Sud, CHU Bordeaux, Pessac, France
| | - Philippe Gosse
- Cardiac Intensive Care Unit, Hôpital St André, CHU Bordeaux, Bordeaux, France
| | - Alexandre Ouattara
- Department of Anaesthesia and Critical Care, Groupe Hospitalier Sud, CHU Bordeaux, Pessac, France
| | - Hadrien Rozé
- Department of Anaesthesia and Critical Care, Groupe Hospitalier Sud, CHU Bordeaux, Pessac, France
| | - Pierre Coste
- Cardiac Intensive Care Unit, Groupe Hospitalier Sud, CHU de Bordeaux, Pessac, France
| | - Edouard Gerbaud
- Cardiac Intensive Care Unit, Groupe Hospitalier Sud, CHU de Bordeaux, Pessac, France
| | - Arnaud Desclaux
- Infectious disease Unit, Hôpital Pellegrin, CHU Bordeaux, Bordeaux, France
| | - Alexandre Boyer
- Medical Intensive Care Unit, Hôpital Pellegrin, CHU Bordeaux, Bordeaux, France
| | - Renaud Prevel
- Medical Intensive Care Unit, Hôpital Pellegrin, CHU Bordeaux, Bordeaux, France
| | - Didier Gruson
- Medical Intensive Care Unit, Hôpital Pellegrin, CHU Bordeaux, Bordeaux, France
| | - Fabrice Bonnet
- Infectious Disease Unit, Hôpital St André, CHU Bordeaux, Bordeaux, France
| | - Nahema Issa
- Intensive Care Unit, Hôpital St André, CHU Bordeaux, Bordeaux, France
| | - Michel Montaudon
- Department of Cardiovascular Imaging, Groupe Hospitalier Sud, CHU Bordeaux, Pessac, France
| | - François Laurent
- Department of Cardiovascular Imaging, Groupe Hospitalier Sud, CHU Bordeaux, Pessac, France
| | - Matthias Stuber
- IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux - INSERM U1045, Avenue du Haut Lévêque, Pessac, France; Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; CIBM Center for Biomedical Imaging, Lausanne, Switzerland
| | - Fabrice Camou
- Intensive Care Unit, Hôpital St André, CHU Bordeaux, Bordeaux, France
| | - Hubert Cochet
- Department of Cardiovascular Imaging, Groupe Hospitalier Sud, CHU Bordeaux, Pessac, France; IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux - INSERM U1045, Avenue du Haut Lévêque, Pessac, France
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13
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Guo R, Weingärtner S, Šiurytė P, T Stoeck C, Füetterer M, E Campbell-Washburn A, Suinesiaputra A, Jerosch-Herold M, Nezafat R. Emerging Techniques in Cardiac Magnetic Resonance Imaging. J Magn Reson Imaging 2021; 55:1043-1059. [PMID: 34331487 DOI: 10.1002/jmri.27848] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 07/08/2021] [Accepted: 07/09/2021] [Indexed: 11/10/2022] Open
Abstract
Cardiovascular disease is the leading cause of death and a significant contributor of health care costs. Noninvasive imaging plays an essential role in the management of patients with cardiovascular disease. Cardiac magnetic resonance (MR) can noninvasively assess heart and vascular abnormalities, including biventricular structure/function, blood hemodynamics, myocardial tissue composition, microstructure, perfusion, metabolism, coronary microvascular function, and aortic distensibility/stiffness. Its ability to characterize myocardial tissue composition is unique among alternative imaging modalities in cardiovascular disease. Significant growth in cardiac MR utilization, particularly in Europe in the last decade, has laid the necessary clinical groundwork to position cardiac MR as an important imaging modality in the workup of patients with cardiovascular disease. Although lack of availability, limited training, physician hesitation, and reimbursement issues have hampered widespread clinical adoption of cardiac MR in the United States, growing clinical evidence will ultimately overcome these challenges. Advances in cardiac MR techniques, particularly faster image acquisition, quantitative myocardial tissue characterization, and image analysis have been critical to its growth. In this review article, we discuss recent advances in established and emerging cardiac MR techniques that are expected to strengthen its capability in managing patients with cardiovascular disease. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Rui Guo
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Sebastian Weingärtner
- Department of Imaging Physics, Magnetic Resonance Systems Lab, Delft University of Technology, Delft, The Netherlands
| | - Paulina Šiurytė
- Department of Imaging Physics, Magnetic Resonance Systems Lab, Delft University of Technology, Delft, The Netherlands
| | - Christian T Stoeck
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Maximilian Füetterer
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Adrienne E Campbell-Washburn
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Avan Suinesiaputra
- Faculty of Engineering and Physical Sciences, University of Leeds, Leeds, UK
| | - Michael Jerosch-Herold
- Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
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14
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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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15
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Toupin S, Pezel T, Bustin A, Cochet H. Whole-Heart High-Resolution Late Gadolinium Enhancement: Techniques and Clinical Applications. J Magn Reson Imaging 2021; 55:967-987. [PMID: 34155715 PMCID: PMC9292698 DOI: 10.1002/jmri.27732] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Revised: 04/13/2021] [Accepted: 04/14/2021] [Indexed: 12/15/2022] Open
Abstract
In cardiovascular magnetic resonance, late gadolinium enhancement (LGE) has become the cornerstone of myocardial tissue characterization. It is widely used in clinical routine to diagnose and characterize the myocardial tissue in a wide range of ischemic and nonischemic cardiomyopathies. The recent growing interest in imaging left atrial fibrosis has led to the development of novel whole‐heart high‐resolution late gadolinium enhancement (HR‐LGE) techniques. Indeed, conventional LGE is acquired in multiple breath‐holds with limited spatial resolution: ~1.4–1.8 mm in plane and 6–8 mm slice thickness, according to the Society for Cardiovascular Magnetic Resonance standardized guidelines. Such large voxel size prevents its use in thin structures such as the atrial or right ventricular walls. Whole‐heart 3D HR‐LGE images are acquired in free breathing to increase the spatial resolution (up to 1.3 × 1.3 × 1.3 mm3) and offer a better detection and depiction of focal atrial fibrosis. The downside of this increased resolution is the extended scan time of around 10 min, which hampers the spread of HR‐LGE in clinical practice. Initially introduced for atrial fibrosis imaging, HR‐LGE interest has evolved to be a tool to detect small scars in the ventricles and guide ablation procedures. Indeed, the detection of scars, nonvisible with conventional LGE, can be crucial in the diagnosis of myocardial infarction with nonobstructed coronary arteries, in the detection of the arrhythmogenic substrate triggering ventricular arrhythmia, and improve the confidence of clinicians in the challenging diagnoses such as the arrhythmogenic right ventricular cardiomyopathy. HR‐LGE also offers a precise visualization of left ventricular scar morphology that is particularly useful in planning ablation procedures and guiding them through the fusion of HR‐LGE images with electroanatomical mapping systems. In this narrative review, we attempt to summarize the technical particularities of whole‐heart HR‐LGE acquisition and provide an overview of its clinical applications with a particular focus on the ventricles.
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Affiliation(s)
- Solenn Toupin
- Siemens Healthcare France, Saint-Denis, France.,IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Bordeaux, France.,Université de Bordeaux, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France.,INSERM, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France
| | - Théo Pezel
- Division of Cardiology, Johns Hopkins University, Baltimore, Maryland, USA.,Department of Cardiology, Lariboisiere Hospital, APHP, University of Paris, Paris, France
| | - Aurélien Bustin
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Bordeaux, France.,Université de Bordeaux, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France.,INSERM, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France.,Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Hubert Cochet
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Bordeaux, France.,Université de Bordeaux, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France.,INSERM, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France.,Bordeaux University Hospital (CHU), Pessac, France
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16
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Gómez-Talavera S, Fernandez-Jimenez R, Fuster V, Nothnagel ND, Kouwenhoven M, Clemence M, García-Lunar I, Gómez-Rubín MC, Navarro F, Pérez-Asenjo B, Fernández-Friera L, Calero MJ, Orejas M, Cabrera JA, Desco M, Pizarro G, Ibáñez B, Sánchez-González J. Clinical Validation of a 3-Dimensional Ultrafast Cardiac Magnetic Resonance Protocol Including Single Breath-Hold 3-Dimensional Sequences. JACC Cardiovasc Imaging 2021; 14:1742-1754. [PMID: 33865783 PMCID: PMC8421247 DOI: 10.1016/j.jcmg.2021.02.031] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 01/05/2021] [Accepted: 02/05/2021] [Indexed: 11/02/2022]
Abstract
OBJECTIVES This study sought to clinically validate a novel 3-dimensional (3D) ultrafast cardiac magnetic resonance (CMR) protocol including cine (anatomy and function) and late gadolinium enhancement (LGE), each in a single breath-hold. BACKGROUND CMR is the reference tool for cardiac imaging but is time-consuming. METHODS A protocol comprising isotropic 3D cine (Enhanced sensitivity encoding [SENSE] by Static Outer volume Subtraction [ESSOS]) and isotropic 3D LGE sequences was compared with a standard cine+LGE protocol in a prospective study of 107 patients (age 58 ± 11 years; 24% female). Left ventricular (LV) mass, volumes, and LV and right ventricular (RV) ejection fraction (LVEF, RVEF) were assessed by 3D ESSOS and 2D cine CMR. LGE (% LV) was assessed using 3D and 2D sequences. RESULTS Three-dimensional and LGE acquisitions lasted 24 and 22 s, respectively. Three-dimensional and LGE images were of good quality and allowed quantification in all cases. Mean LVEF by 3D and 2D CMR were 51 ± 12% and 52 ± 12%, respectively, with excellent intermethod agreement (intraclass correlation coefficient [ICC]: 0.96; 95% confidence interval [CI]: 0.94 to 0.97) and insignificant bias. Mean RVEF 3D and 2D CMR were 60.4 ± 5.4% and 59.7 ± 5.2%, respectively, with acceptable intermethod agreement (ICC: 0.73; 95% CI: 0.63 to 0.81) and insignificant bias. Both 2D and 3D LGE showed excellent agreement, and intraobserver and interobserver agreement were excellent for 3D LGE. CONCLUSIONS ESSOS single breath-hold 3D CMR allows accurate assessment of heart anatomy and function. Combining ESSOS with 3D LGE allows complete cardiac examination in <1 min of acquisition time. This protocol expands the indication for CMR, reduces costs, and increases patient comfort.
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Affiliation(s)
- Sandra Gómez-Talavera
- Clinical Research Department, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain; Department of Cardiology, IIS-Hospital Fundacion Jiménez Díaz, Madrid, Spain; CIBER de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | - Rodrigo Fernandez-Jimenez
- Clinical Research Department, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain; CIBER de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain; Department of Cardiology, Hospital Universitario Clinico San Carlos, Madrid, Spain
| | - Valentín Fuster
- Clinical Research Department, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain; Department of Cardiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | | | | | | | - Inés García-Lunar
- Clinical Research Department, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain; CIBER de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain; Department of Cardiology, Hospital Universitario Quiron UEM, Madrid, Spain
| | | | - Felipe Navarro
- Department of Cardiology, IIS-Hospital Fundacion Jiménez Díaz, Madrid, Spain; CIBER de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | - Braulio Pérez-Asenjo
- Clinical Research Department, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain
| | - Leticia Fernández-Friera
- Clinical Research Department, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain; CIBER de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain; Department of Cardiology, Hospital Montepríncipe-CEU, Madrid, Spain
| | - María J Calero
- Department of Cardiology, Hospital Universtario Rey Juan Carlos-Móstoles, Madrid, Spain
| | - Miguel Orejas
- Department of Cardiology, IIS-Hospital Fundacion Jiménez Díaz, Madrid, Spain
| | - José A Cabrera
- Department of Cardiology, Hospital Universitario Quiron UEM, Madrid, Spain
| | - Manuel Desco
- Clinical Research Department, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain; Departamento de Bioingeniería e Ingeniería Aerospacial, Universidad Carlos III, Madrid, Spain
| | - Gonzalo Pizarro
- Clinical Research Department, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain; CIBER de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain; Department of Cardiology, Hospital Universitario Quiron UEM, Madrid, Spain
| | - Borja Ibáñez
- Clinical Research Department, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain; Department of Cardiology, IIS-Hospital Fundacion Jiménez Díaz, Madrid, Spain; CIBER de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain.
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17
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Pennig L, Lennartz S, Wagner A, Sokolowski M, Gajzler M, Ney S, Laukamp KR, Persigehl T, Bunck AC, Maintz D, Weiss K, Naehle CP, Doerner J. Clinical application of free-breathing 3D whole heart late gadolinium enhancement cardiovascular magnetic resonance with high isotropic spatial resolution using Compressed SENSE. J Cardiovasc Magn Reson 2020; 22:89. [PMID: 33327958 PMCID: PMC7745391 DOI: 10.1186/s12968-020-00673-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Accepted: 09/15/2020] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) represents the gold standard for assessment of myocardial viability. The purpose of this study was to investigate the clinical potential of Compressed SENSE (factor 5) accelerated free-breathing three-dimensional (3D) whole heart LGE with high isotropic spatial resolution (1.4 mm3 acquired voxel size) compared to standard breath-hold LGE imaging. METHODS This was a retrospective, single-center study of 70 consecutive patients (45.8 ± 18.1 years, 27 females; February-November 2019), who were referred for assessment of left ventricular myocardial viability and received free-breathing and breath-hold LGE sequences at 1.5 T in clinical routine. Two radiologists independently evaluated global and segmental LGE in terms of localization and transmural extent. Readers scored scans regarding image quality (IQ), artifacts, and diagnostic confidence (DC) using 5-point scales (1 non-diagnostic-5 excellent/none). Effects of heart rate and body mass index (BMI) on IQ, artifacts, and DC were evaluated with ordinal logistic regression analysis. RESULTS Global LGE (n = 33) was identical for both techniques. Using free-breathing LGE (average scan time: 04:33 ± 01:17 min), readers detected more hyperenhanced lesions (28.2% vs. 23.5%, P < .05) compared to breath-hold LGE (05:15 ± 01:23 min, P = .0104), pronounced at subepicardial localization and for 1-50% of transmural extent. For free-breathing LGE, readers graded scans with good/excellent IQ in 80.0%, with low-impact/no artifacts in 78.6%, and with good/high DC in 82.1% of cases. Elevated BMI was associated with increased artifacts (P = .0012) and decreased IQ (P = .0237). Increased heart rate negatively influenced artifacts (P = .0013) and DC (P = .0479) whereas IQ (P = .3025) was unimpaired. CONCLUSIONS In a clinical setting, free-breathing Compressed SENSE accelerated 3D high isotropic spatial resolution whole heart LGE provides good to excellent image quality in 80% of scans independent of heart rate while enabling improved depiction of small and particularly non-ischemic hyperenhanced lesions in a shorter scan time than standard breath-hold LGE.
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Affiliation(s)
- Lenhard Pennig
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Straße 62, 50937, Cologne, Germany.
| | - Simon Lennartz
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Straße 62, 50937, Cologne, Germany
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114, USA
- Else Kröner Forschungskolleg Clonal Evolution in Cancer, University Hospital Cologne, Weyertal 115b, 50931, Cologne, Germany
| | - Anton Wagner
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Straße 62, 50937, Cologne, Germany
| | - Marcel Sokolowski
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Straße 62, 50937, Cologne, Germany
| | - Matej Gajzler
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Straße 62, 50937, Cologne, Germany
| | - Svenja Ney
- Department III of Internal Medicine, Heart Center, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Straße 62, 50937, Cologne, Germany
| | - Kai Roman Laukamp
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Straße 62, 50937, Cologne, Germany
- Department of Radiology, University Hospitals Cleveland Medical Center, 11000 Euclid Ave, Cleveland, OH, 44106, USA
- Department of Radiology, Case Western Reserve University, 11000 Euclid Ave, Cleveland, OH, 44106, USA
| | - Thorsten Persigehl
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Straße 62, 50937, Cologne, Germany
| | - Alexander Christian Bunck
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Straße 62, 50937, Cologne, Germany
| | - David Maintz
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Straße 62, 50937, Cologne, Germany
| | - Kilian Weiss
- Philips GmbH, Röntgenstraße 22, 22335, Hamburg, Germany
| | - Claas Philip Naehle
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Straße 62, 50937, Cologne, Germany
| | - Jonas Doerner
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Straße 62, 50937, Cologne, Germany
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18
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Detecting a subendocardial infarction in a child with coronary anomaly by three-dimensional late gadolinium enhancement MRI using compressed sensing. Radiol Case Rep 2020; 16:377-380. [PMID: 33318777 PMCID: PMC7726481 DOI: 10.1016/j.radcr.2020.11.048] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 11/27/2020] [Accepted: 11/28/2020] [Indexed: 11/21/2022] Open
Abstract
Three-dimensional high-resolution late gadolinium enhancement (3D HR LGE) magnetic resonance imaging (MRI) using compressed sensing can help detect small myocardial infarcts. We discuss the case of an 11-year-old child with an anomalous aortic origin of the left coronary artery. Since he was suspected to have coronary stenosis due to anomalous aortic origin of the left coronary artery, cardiovascular MRI, including conventional two-dimensional (2D) LGE MRI and HR 3D LGE MRI, was conducted. Myocardial scars were not clearly observed via 2D LGE MRI; however, 3D HR MRI revealed subendocardial infarction of the anteroseptal wall, which corresponded to the left coronary artery. By applying the compressed sensing technique, 3D HR LGE, MRI enables a detailed assessment of small myocardial infarcts in a clinically feasible scan time.
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Casella M, Gasperetti A, Sicuso R, Conte E, Catto V, Sommariva E, Bergonti M, Vettor G, Rizzo S, Pompilio G, Andreini D, Saguner AM, Duru F, Natale A, Thiene G, Basso C, Dello Russo A, Tondo C. Characteristics of Patients With Arrhythmogenic Left Ventricular Cardiomyopathy. Circ Arrhythm Electrophysiol 2020; 13:e009005. [DOI: 10.1161/circep.120.009005] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Background:
Arrhythmogenic left ventricular cardiomyopathy (ALVC) is an under-characterized phenotype of arrhythmogenic cardiomyopathy involving the LV ab initio. ALVC was not included in the 2010 International Task Force Criteria for arrhythmogenic right ventricular cardiomyopathy diagnosis and data regarding this phenotype are scarce.
Methods:
Clinical characteristics were reported from all consecutive patients diagnosed with ALVC, defined as a LV isolated late gadolinium enhancement and fibro-fatty replacement at cardiac magnetic resonance plus genetic variants associated with arrhythmogenic right ventricular cardiomyopathy and of an endomyocardial biopsy showing fibro-fatty replacement complying with the 2010 International Task Force Criteria in the LV.
Results:
Twenty-five patients ALVC (53 [48–59] years, 60% male) were enrolled. T wave inversion in infero-lateral and left precordial leads were the most common ECG abnormalities. Overall arrhythmic burden at study inclusion was 56%. Cardiac magnetic resonance showed LV late gadolinium enhancement in the LV lateral and posterior basal segments in all patients. In 72% of the patients an invasive evaluation was performed, in which electroanatomical voltage mapping and electroanatomical voltage mapping-guided endomyocardial biopsy showed low endocardial voltages and fibro-fatty replacement in areas of late gadolinium enhancement presence. Genetic variants in desmosomal genes (desmoplakin and desmoglein-2) were identified in 12/25 of the cohort presenting pathogenic/likely pathogenic variants. A definite/borderline 2010 International Task Force Criteria arrhythmogenic right ventricular cardiomyopathy diagnosis was reached only in 11/25 patients.
Conclusions:
ALVC presents with a preferential involvement of the lateral and postero-lateral basal LV and is associated mostly with variants in desmoplakin and desmoglein-2 genes. An amendment to the current International Task Force Criteria is reasonable to better diagnose patients with ALVC.
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Affiliation(s)
- Michela Casella
- Heart Rhythm Center (M.C., A.G., R.S., V.C., M.B., G.V., C.T.), Centro Cardiologico Monzino IRCCS, Milano
- Cardiology and Arrhythmology Clinic, Department of Clinical, Special and Dental Sciences (M.C.), University Hospital “Umberto I-Lancisi-Salesi”, Marche Polytechnic University, Ancona, Italy
| | - Alessio Gasperetti
- Heart Rhythm Center (M.C., A.G., R.S., V.C., M.B., G.V., C.T.), Centro Cardiologico Monzino IRCCS, Milano
- Cardiology and Arrhythmology Clinic, Department of Biomedical Sciences and Public Health (A.G., A.D.R.), University Hospital “Umberto I-Lancisi-Salesi”, Marche Polytechnic University, Ancona, Italy
- University Heart Center, University Hospital Zurich, Switzerland (A.G., A.M.S., F.D.)
| | - Rita Sicuso
- Heart Rhythm Center (M.C., A.G., R.S., V.C., M.B., G.V., C.T.), Centro Cardiologico Monzino IRCCS, Milano
| | - Edoardo Conte
- Dipartimento di Imaging Cardiovascolare (E.C., D.A.), Centro Cardiologico Monzino IRCCS, Milano
| | - Valentina Catto
- Heart Rhythm Center (M.C., A.G., R.S., V.C., M.B., G.V., C.T.), Centro Cardiologico Monzino IRCCS, Milano
| | - Elena Sommariva
- Unit of Vascular Biology and Regenerative Medicine (E.S., G.P.), Centro Cardiologico Monzino IRCCS, Milano
| | - Marco Bergonti
- Heart Rhythm Center (M.C., A.G., R.S., V.C., M.B., G.V., C.T.), Centro Cardiologico Monzino IRCCS, Milano
| | - Giulia Vettor
- Heart Rhythm Center (M.C., A.G., R.S., V.C., M.B., G.V., C.T.), Centro Cardiologico Monzino IRCCS, Milano
| | - Stefania Rizzo
- Cardiovascular Pathology Unit, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, Azienda Ospedaliera-University of Padua, Padova (S.R., G.T., C.B.)
| | - Giulio Pompilio
- Unit of Vascular Biology and Regenerative Medicine (E.S., G.P.), Centro Cardiologico Monzino IRCCS, Milano
- Department of Clinical Sciences and Community Health, University of Milan, Italy (G.P., D.A., C.T.)
| | - Daniele Andreini
- Dipartimento di Imaging Cardiovascolare (E.C., D.A.), Centro Cardiologico Monzino IRCCS, Milano
- Department of Clinical Sciences and Community Health, University of Milan, Italy (G.P., D.A., C.T.)
| | - Ardan Muammer Saguner
- University Heart Center, University Hospital Zurich, Switzerland (A.G., A.M.S., F.D.)
| | - Firat Duru
- University Heart Center, University Hospital Zurich, Switzerland (A.G., A.M.S., F.D.)
| | - Andrea Natale
- Texas Cardiac Arrhythmia Institute, St. David’s Hospital, Austin (A.N.)
| | - Gaetano Thiene
- Cardiovascular Pathology Unit, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, Azienda Ospedaliera-University of Padua, Padova (S.R., G.T., C.B.)
| | - Cristina Basso
- Cardiovascular Pathology Unit, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, Azienda Ospedaliera-University of Padua, Padova (S.R., G.T., C.B.)
| | - Antonio Dello Russo
- Cardiology and Arrhythmology Clinic, Department of Biomedical Sciences and Public Health (A.G., A.D.R.), University Hospital “Umberto I-Lancisi-Salesi”, Marche Polytechnic University, Ancona, Italy
| | - Claudio Tondo
- Heart Rhythm Center (M.C., A.G., R.S., V.C., M.B., G.V., C.T.), Centro Cardiologico Monzino IRCCS, Milano
- Department of Clinical Sciences and Community Health, University of Milan, Italy (G.P., D.A., C.T.)
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20
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Zhang L, Lai P, Roifman I, Pop M, Wright GA. Multi-contrast volumetric imaging with isotropic resolution for assessing infarct heterogeneity: Initial clinical experience. NMR IN BIOMEDICINE 2020; 33:e4253. [PMID: 32026547 DOI: 10.1002/nbm.4253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2018] [Revised: 11/14/2019] [Accepted: 12/05/2019] [Indexed: 06/10/2023]
Abstract
BACKGROUND To evaluate accelerated multi-contrast volumetric imaging with isotropic resolution reconstructed using low-rank and spatially varying edge-preserving constrained compressed sensing parallel imaging reconstruction (CP-LASER), for assessing infarct heterogeneity on post-infarction patients as a precursor to studies of utility for predicting ventricular arrhythmias. METHODS Eleven patients with prior myocardial infarction were included in the study. All subjects underwent cardiovascular magnetic resonance (CMR) scans including conventional two-dimensional late gadolinium enhancement (2D LGE) and three-dimensional multi-contrast late enhancement (3D MCLE) post-contrast. The extent of the infarct core and peri-infarct gray zone of a limited mid-ventricular slab were derived respectively by analyzing MCLE images with an isotropic resolution of 2.2 mm and an anisotropic resolution of 2.2×2.2×8.8 mm 3 , and LGE images with a resolution of 1.37×2.7×8 mm 3 ; the respective measures across all subjects were statistically compared. RESULTS Using 3D MCLE, the infarct core size measured with isotropic resolution was similar to that measured with anisotropic resolution, while the peri-infarct gray zone size measured with isotropic resolution was smaller than that measured with anisotropic resolution ( p<0.001 , Cohen's dz=1.33 ). Isotropic 3D MCLE yielded a significantly smaller measure of the peri-infarct gray zone size than conventional 2D LGE ( p=0.0016 , Cohen's dz=1.20 ). Overall, we have successfully shown the utility of isotropic 3D MCLE in a pilot patient study. Our results suggest that smaller voxels lead to more accurate differentiation between isotropic 3D MCLE-derived gray zone and core infarct because of diminished partial volume effect. CONCLUSION The CP-LASER accelerated 3D MCLE with isotropic resolution can be used in patients and yields excellent delineation of infarct and peri-infarct gray zone characteristics.
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Affiliation(s)
- Li Zhang
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Peng Lai
- Global Applied Science Laboratory, GE Healthcare, Menlo Park, California, USA
| | - Idan Roifman
- Schulich Heart Research Program, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Mihaela Pop
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Ontario, Canada
- Schulich Heart Research Program, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Graham A Wright
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Ontario, Canada
- Schulich Heart Research Program, Sunnybrook Research Institute, Toronto, Ontario, Canada
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21
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Olde Nordkamp LRA, Boekholdt SM, de Groot JR. Different road maps for ventricular tachycardia ablation. Neth Heart J 2020; 28:571-572. [PMID: 33079333 PMCID: PMC7596152 DOI: 10.1007/s12471-020-01507-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/12/2020] [Indexed: 10/25/2022] Open
Affiliation(s)
- L R A Olde Nordkamp
- Department of Cardiology, Heart Center, Amsterdam UMC, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands
| | - S M Boekholdt
- Department of Cardiology, Heart Center, Amsterdam UMC, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands
| | - J R de Groot
- Department of Cardiology, Heart Center, Amsterdam UMC, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands.
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22
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Munoz C, Bustin A, Neji R, Kunze KP, Forman C, Schmidt M, Hajhosseiny R, Masci PG, Zeilinger M, Wuest W, Botnar RM, Prieto C. Motion-corrected 3D whole-heart water-fat high-resolution late gadolinium enhancement cardiovascular magnetic resonance imaging. J Cardiovasc Magn Reson 2020; 22:53. [PMID: 32684167 PMCID: PMC7370486 DOI: 10.1186/s12968-020-00649-5] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Accepted: 06/17/2020] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Conventional 2D inversion recovery (IR) and phase sensitive inversion recovery (PSIR) late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) have been widely incorporated into routine CMR for the assessment of myocardial viability. However, reliable suppression of fat signal, and increased isotropic spatial resolution and volumetric coverage within a clinically feasible scan time remain a challenge. In order to address these challenges, this work proposes a highly efficient respiratory motion-corrected 3D whole-heart water/fat LGE imaging framework. METHODS An accelerated IR-prepared 3D dual-echo acquisition and motion-corrected reconstruction framework for whole-heart water/fat LGE imaging was developed. The acquisition sequence includes 2D image navigators (iNAV), which are used to track the respiratory motion of the heart and enable 100% scan efficiency. Non-rigid motion information estimated from the 2D iNAVs and from the data itself is integrated into a high-dimensional patch-based undersampled reconstruction technique (HD-PROST), to produce high-resolution water/fat 3D LGE images. A cohort of 20 patients with known or suspected cardiovascular disease was scanned with the proposed 3D water/fat LGE approach. 3D water LGE images were compared to conventional breath-held 2D LGE images (2-chamber, 4-chamber and stack of short-axis views) in terms of image quality (1: full diagnostic to 4: non-diagnostic) and presence of LGE findings. RESULTS Image quality was considered diagnostic in 18/20 datasets for both 2D and 3D LGE magnitude images, with comparable image quality scores (2D: 2.05 ± 0.72, 3D: 1.88 ± 0.90, p-value = 0.62) and overall agreement in LGE findings. Acquisition time for isotropic high-resolution (1.3mm3) water/fat LGE images was 8.0 ± 1.4 min (3-fold acceleration, 60-88 slices covering the whole heart), while 2D LGE images were acquired in 5.6 ± 2.2 min (12-18 slices, including pauses between breath-holds) albeit with a lower spatial resolution (1.40-1.75 mm in-plane × 8 mm slice thickness). CONCLUSION A novel framework for motion-corrected whole-heart 3D water/fat LGE imaging has been introduced. The method was validated in patients with known or suspected cardiovascular disease, showing good agreement with conventional breath-held 2D LGE imaging, but offering higher spatial resolution, improved volumetric coverage and good image quality from a free-breathing acquisition with 100% scan efficiency and predictable scan time.
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Affiliation(s)
- Camila Munoz
- School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, 3rd Floor, Lambeth Wing, London, SE1 7EH, UK.
| | - Aurelien Bustin
- School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, 3rd Floor, Lambeth Wing, London, SE1 7EH, UK
| | - Radhouene Neji
- School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, 3rd Floor, Lambeth Wing, London, SE1 7EH, UK
- MR Research Collaborations, Siemens Healthcare, Frimley, UK
| | - Karl P Kunze
- MR Research Collaborations, Siemens Healthcare, Frimley, UK
| | - Christoph Forman
- Cardiovascular MR Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Michaela Schmidt
- Cardiovascular MR Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Reza Hajhosseiny
- School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, 3rd Floor, Lambeth Wing, London, SE1 7EH, UK
| | - Pier-Giorgio Masci
- School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, 3rd Floor, Lambeth Wing, London, SE1 7EH, UK
| | - Martin Zeilinger
- Institute of Radiology, University Hospital Erlangen, Erlangen, Germany
| | - Wolfgang Wuest
- Institute of Radiology, University Hospital Erlangen, Erlangen, Germany
| | - René M Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, 3rd Floor, Lambeth Wing, London, SE1 7EH, UK
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, 3rd Floor, Lambeth Wing, London, SE1 7EH, UK
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23
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El-Rewaidy H, Neisius U, Mancio J, Kucukseymen S, Rodriguez J, Paskavitz A, Menze B, Nezafat R. Deep complex convolutional network for fast reconstruction of 3D late gadolinium enhancement cardiac MRI. NMR IN BIOMEDICINE 2020; 33:e4312. [PMID: 32352197 DOI: 10.1002/nbm.4312] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Revised: 03/19/2020] [Accepted: 03/24/2020] [Indexed: 06/11/2023]
Abstract
Several deep-learning models have been proposed to shorten MRI scan time. Prior deep-learning models that utilize real-valued kernels have limited capability to learn rich representations of complex MRI data. In this work, we utilize a complex-valued convolutional network (ℂNet) for fast reconstruction of highly under-sampled MRI data and evaluate its ability to rapidly reconstruct 3D late gadolinium enhancement (LGE) data. ℂNet preserves the complex nature and optimal combination of real and imaginary components of MRI data throughout the reconstruction process by utilizing complex-valued convolution, novel radial batch normalization, and complex activation function layers in a U-Net architecture. A prospectively under-sampled 3D LGE cardiac MRI dataset of 219 patients (17 003 images) at acceleration rates R = 3 through R = 5 was used to evaluate ℂNet. The dataset was further retrospectively under-sampled to a maximum of R = 8 to simulate higher acceleration rates. We created three reconstructions of the 3D LGE dataset using (1) ℂNet, (2) a compressed-sensing-based low-dimensional-structure self-learning and thresholding algorithm (LOST), and (3) a real-valued U-Net (realNet) with the same number of parameters as ℂNet. LOST-reconstructed data were considered the reference for training and evaluation of all models. The reconstructed images were quantitatively evaluated using mean-squared error (MSE) and the structural similarity index measure (SSIM), and subjectively evaluated by three independent readers. Quantitatively, ℂNet-reconstructed images had significantly improved MSE and SSIM values compared with realNet (MSE, 0.077 versus 0.091; SSIM, 0.876 versus 0.733, respectively; p < 0.01). Subjective quality assessment showed that ℂNet-reconstructed image quality was similar to that of compressed sensing and significantly better than that of realNet. ℂNet reconstruction was also more than 300 times faster than compressed sensing. Retrospective under-sampled images demonstrate the potential of ℂNet at higher acceleration rates. ℂNet enables fast reconstruction of highly accelerated 3D MRI with superior performance to real-valued networks, and achieves faster reconstruction than compressed sensing.
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Affiliation(s)
- Hossam El-Rewaidy
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
- Department of Computer Science, Technical University of Munich, Munich, Germany
| | - Ulf Neisius
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Jennifer Mancio
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Selcuk Kucukseymen
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Jennifer Rodriguez
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Amanda Paskavitz
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Bjoern Menze
- Department of Computer Science, Technical University of Munich, Munich, Germany
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
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Cochet H, Sacher F. Hello Doctor, Can I Get My MRI? JACC Clin Electrophysiol 2020; 6:736-738. [DOI: 10.1016/j.jacep.2019.11.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 11/21/2019] [Indexed: 10/24/2022]
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25
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Artificial Intelligence Pertaining to Cardiothoracic Imaging and Patient Care: Beyond Image Interpretation. J Thorac Imaging 2020; 35:137-142. [PMID: 32141963 DOI: 10.1097/rti.0000000000000486] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
Artificial intelligence (AI) is a broad field of computational science that includes many subsets. Today the most widely used subset in medical imaging is machine learning (ML). Many articles have focused on the use of ML for pattern recognition to detect and potentially diagnose various pathologies. However, AI algorithm development is now directed toward workflow management. AI can impact patient care at multiple stages of their imaging experience and assist in efficient and effective scheduling, imaging performance, worklist prioritization, image interpretation, and quality assurance. The purpose of this manuscript was to review the potential AI applications in radiology focusing on workflow management and discuss how ML will affect cardiothoracic imaging.
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26
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Bustin A, Fuin N, Botnar RM, Prieto C. From Compressed-Sensing to Artificial Intelligence-Based Cardiac MRI Reconstruction. Front Cardiovasc Med 2020; 7:17. [PMID: 32158767 PMCID: PMC7051921 DOI: 10.3389/fcvm.2020.00017] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 01/31/2020] [Indexed: 12/28/2022] Open
Abstract
Cardiac magnetic resonance (CMR) imaging is an important tool for the non-invasive assessment of cardiovascular disease. However, CMR suffers from long acquisition times due to the need of obtaining images with high temporal and spatial resolution, different contrasts, and/or whole-heart coverage. In addition, both cardiac and respiratory-induced motion of the heart during the acquisition need to be accounted for, further increasing the scan time. Several undersampling reconstruction techniques have been proposed during the last decades to speed up CMR acquisition. These techniques rely on acquiring less data than needed and estimating the non-acquired data exploiting some sort of prior information. Parallel imaging and compressed sensing undersampling reconstruction techniques have revolutionized the field, enabling 2- to 3-fold scan time accelerations to become standard in clinical practice. Recent scientific advances in CMR reconstruction hinge on the thriving field of artificial intelligence. Machine learning reconstruction approaches have been recently proposed to learn the non-linear optimization process employed in CMR reconstruction. Unlike analytical methods for which the reconstruction problem is explicitly defined into the optimization process, machine learning techniques make use of large data sets to learn the key reconstruction parameters and priors. In particular, deep learning techniques promise to use deep neural networks (DNN) to learn the reconstruction process from existing datasets in advance, providing a fast and efficient reconstruction that can be applied to all newly acquired data. However, before machine learning and DNN can realize their full potentials and enter widespread clinical routine for CMR image reconstruction, there are several technical hurdles that need to be addressed. In this article, we provide an overview of the recent developments in the area of artificial intelligence for CMR image reconstruction. The underlying assumptions of established techniques such as compressed sensing and low-rank reconstruction are briefly summarized, while a greater focus is given to recent advances in dictionary learning and deep learning based CMR reconstruction. In particular, approaches that exploit neural networks as implicit or explicit priors are discussed for 2D dynamic cardiac imaging and 3D whole-heart CMR imaging. Current limitations, challenges, and potential future directions of these techniques are also discussed.
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Affiliation(s)
- Aurélien Bustin
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Niccolo Fuin
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - René M. Botnar
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Claudia Prieto
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
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Hirai K, Kido T, Kido T, Ogawa R, Tanabe Y, Nakamura M, Kawaguchi N, Kurata A, Watanabe K, Yamaguchi O, Schmidt M, Forman C, Mochizuki T. Feasibility of contrast-enhanced coronary artery magnetic resonance angiography using compressed sensing. J Cardiovasc Magn Reson 2020; 22:15. [PMID: 32050982 PMCID: PMC7017458 DOI: 10.1186/s12968-020-0601-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Accepted: 01/09/2020] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Coronary magnetic resonance angiography (CMRA) is a promising technique for assessing the coronary arteries. However, a disadvantage of CMRA is the comparatively long acquisition time. Compressed sensing (CS) can considerably reduce the scan time. The aim of this study was to verify the feasibility of CS CMRA scanning during the waiting time between contrast injection and late gadolinium enhancement (LGE) scan in a clinical protocol. METHODS Fifty clinical patients underwent contrast-enhanced CS CMRA and conventional CMRA on a 3 T CMR scanner. After contrast injection, CS CMRA was scanned during the waiting time for LGE CMR. A conventional CMRA scan was performed after LGE CMR. We assessed acquisition times and coronary artery image quality for each segment on a 4-point scale. Visible vessel length, sharpness and diameter of right (RCA), left anterior descending (LAD), and left circumflex (LCX) coronary arteries were also quantitatively compared among the scans. RESULTS All CS CMRA scans were successfully performed within the LGE waiting time. The median total scan time was 207 s (163, 259 s) for CS and 785 s (698, 975 s) for conventional CMRA (p < 0.001). No significant differences were observed in image quality scores, vessel length measurements, sharpness, and diameter between CS and conventional CMRA. CONCLUSIONS We could achieve all CS CMRA scans within the LGE waiting time. Contrast-enhanced CS CMRA could considerably shorten the scan time while maintaining image quality compared with conventional CMRA.
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Affiliation(s)
- Kuniaki Hirai
- Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime 791-0295 Japan
| | - Teruhito Kido
- Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime 791-0295 Japan
| | - Tomoyuki Kido
- Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime 791-0295 Japan
| | - Ryo Ogawa
- Department of Radiology, Saiseikai Matsuyama Hospital, 880-2, Yamanishi, Matsuyama, Ehime 791-8026 Japan
| | - Yuki Tanabe
- Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime 791-0295 Japan
| | - Masashi Nakamura
- Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime 791-0295 Japan
| | - Naoto Kawaguchi
- Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime 791-0295 Japan
| | - Akira Kurata
- Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime 791-0295 Japan
| | - Kouki Watanabe
- Department of Cardiology, Saiseikai Matsuyama Hospital, 880-2, Yamanishi, Matsuyama, Ehime 791-8026 Japan
| | - Osamu Yamaguchi
- Department of Cardiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime 791-0295 Japan
| | - Michaela Schmidt
- Siemens Healthcare GmbH, Allee am Roethelheimpark 2, 91052 Erlangen, Germany
| | - Christoph Forman
- Siemens Healthcare GmbH, Allee am Roethelheimpark 2, 91052 Erlangen, Germany
| | - Teruhito Mochizuki
- Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime 791-0295 Japan
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Sandino CM, Cheng JY, Chen F, Mardani M, Pauly JM, Vasanawala SS. Compressed Sensing: From Research to Clinical Practice with Deep Neural Networks. IEEE SIGNAL PROCESSING MAGAZINE 2020; 37:111-127. [PMID: 33192036 PMCID: PMC7664163 DOI: 10.1109/msp.2019.2950433] [Citation(s) in RCA: 64] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Compressed sensing (CS) reconstruction methods leverage sparse structure in underlying signals to recover high-resolution images from highly undersampled measurements. When applied to magnetic resonance imaging (MRI), CS has the potential to dramatically shorten MRI scan times, increase diagnostic value, and improve overall patient experience. However, CS has several shortcomings which limit its clinical translation such as: 1) artifacts arising from inaccurate sparse modelling assumptions, 2) extensive parameter tuning required for each clinical application, and 3) clinically infeasible reconstruction times. Recently, CS has been extended to incorporate deep neural networks as a way of learning complex image priors from historical exam data. Commonly referred to as unrolled neural networks, these techniques have proven to be a compelling and practical approach to address the challenges of sparse CS. In this tutorial, we will review the classical compressed sensing formulation and outline steps needed to transform this formulation into a deep learning-based reconstruction framework. Supplementary open source code in Python will be used to demonstrate this approach with open databases. Further, we will discuss considerations in applying unrolled neural networks in the clinical setting.
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Leiner T, Rueckert D, Suinesiaputra A, Baeßler B, Nezafat R, Išgum I, Young AA. Machine learning in cardiovascular magnetic resonance: basic concepts and applications. J Cardiovasc Magn Reson 2019; 21:61. [PMID: 31590664 PMCID: PMC6778980 DOI: 10.1186/s12968-019-0575-y] [Citation(s) in RCA: 116] [Impact Index Per Article: 23.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2018] [Accepted: 09/02/2019] [Indexed: 12/18/2022] Open
Abstract
Machine learning (ML) is making a dramatic impact on cardiovascular magnetic resonance (CMR) in many ways. This review seeks to highlight the major areas in CMR where ML, and deep learning in particular, can assist clinicians and engineers in improving imaging efficiency, quality, image analysis and interpretation, as well as patient evaluation. We discuss recent developments in the field of ML relevant to CMR in the areas of image acquisition & reconstruction, image analysis, diagnostic evaluation and derivation of prognostic information. To date, the main impact of ML in CMR has been to significantly reduce the time required for image segmentation and analysis. Accurate and reproducible fully automated quantification of left and right ventricular mass and volume is now available in commercial products. Active research areas include reduction of image acquisition and reconstruction time, improving spatial and temporal resolution, and analysis of perfusion and myocardial mapping. Although large cohort studies are providing valuable data sets for ML training, care must be taken in extending applications to specific patient groups. Since ML algorithms can fail in unpredictable ways, it is important to mitigate this by open source publication of computational processes and datasets. Furthermore, controlled trials are needed to evaluate methods across multiple centers and patient groups.
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Affiliation(s)
- Tim Leiner
- Department of Radiology | E.01.132, Utrecht University Medical Center, Heidelberglaan 100, 3584CX Utrecht, The Netherlands
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Department of Computing, Imperial College, London, UK
| | - Avan Suinesiaputra
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
| | - Bettina Baeßler
- Department of Radiology, University Hospital of Cologne, Cologne, Germany
- Institute of Clinical Radiology and Nuclear Medicine, University Medical Centre Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA USA
| | - Ivana Išgum
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands
| | - 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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Clinical Diagnosis, Imaging, and Genetics of Arrhythmogenic Right Ventricular Cardiomyopathy/Dysplasia: JACC State-of-the-Art Review. J Am Coll Cardiol 2019; 72:784-804. [PMID: 30092956 DOI: 10.1016/j.jacc.2018.05.065] [Citation(s) in RCA: 167] [Impact Index Per Article: 33.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Revised: 05/24/2018] [Accepted: 05/31/2018] [Indexed: 01/30/2023]
Abstract
Arrhythmogenic right ventricular cardiomyopathy/dysplasia (ARVC/D) is an inherited cardiomyopathy that can lead to sudden cardiac death and heart failure. Our understanding of its pathophysiology and clinical expressivity is continuously evolving. The diagnosis of ARVC/D remains particularly challenging due to the absence of specific unique diagnostic criteria, its variable expressivity, and incomplete penetrance. Advances in genetics have enlarged the clinical spectrum of the disease, highlighting possible phenotypes that overlap with arrhythmogenic dilated cardiomyopathy and channelopathies. The principal challenges for ARVC/D diagnosis include the following: earlier detection of the disease, particularly in cases of focal right ventricular involvement; differential diagnosis from other arrhythmogenic diseases affecting the right ventricle; and the development of new objective electrocardiographic and imaging criteria for diagnosis. This review provides an update on the diagnosis of ARVC/D, focusing on the contribution of emerging imaging techniques, such as echocardiogram/magnetic resonance imaging strain measurements or computed tomography scanning, new electrocardiographic parameters, and high-throughput sequencing.
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Holtackers RJ, Van De Heyning CM, Nazir MS, Rashid I, Ntalas I, Rahman H, Botnar RM, Chiribiri A. Clinical value of dark-blood late gadolinium enhancement cardiovascular magnetic resonance without additional magnetization preparation. J Cardiovasc Magn Reson 2019; 21:44. [PMID: 31352900 PMCID: PMC6661833 DOI: 10.1186/s12968-019-0556-1] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Accepted: 06/14/2019] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND For two decades, bright-blood late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) has been considered the reference standard for the non-invasive assessment of myocardial viability. While bright-blood LGE can clearly distinguish areas of myocardial infarction from viable myocardium, it often suffers from poor scar-to-blood contrast, making subendocardial scar difficult to detect. Recently, we proposed a novel dark-blood LGE approach that increases scar-to-blood contrast and thereby improves subendocardial scar conspicuity. In the present study we sought to assess the clinical value of this novel approach in a large patient cohort with various non-congenital ischemic and non-ischemic cardiomyopathies on both 1.5 T and 3 T CMR scanners of different vendors. METHODS Three hundred consecutive patients referred for clinical CMR were randomly assigned to a 1.5 T or 3 T scanner. An entire short-axis stack and multiple long-axis views were acquired using conventional phase sensitive inversion recovery (PSIR) LGE with TI set to null myocardium (bright-blood) and proposed PSIR LGE with TI set to null blood (dark-blood), in a randomized order. The bright-blood LGE and dark-blood LGE images were separated, anonymized, and interpreted in a random order at different time points by one of five independent observers. Each case was analyzed for the type of scar, per-segment transmurality, papillary muscle enhancement, overall image quality, observer confidence, and presence of right ventricular scar and intraventricular thrombus. RESULTS Dark-blood LGE detected significantly more cases with ischemic scar compared to conventional bright-blood LGE (97 vs 89, p = 0.008), on both 1.5 T and 3 T, and led to a significantly increased total scar burden (3.3 ± 2.4 vs 3.0 ± 2.3 standard AHA segments, p = 0.015). Overall image quality significantly improved using dark-blood LGE compared to bright-blood LGE (81.3% vs 74.0% of all segments were of highest diagnostic quality, p = 0.006). Furthermore, dark-blood LGE led to significantly higher observer confidence (confident in 84.2% vs 78.4%, p = 0.033). CONCLUSIONS The improved detection of ischemic scar makes the proposed dark-blood LGE method a valuable diagnostic tool in the non-invasive assessment of myocardial scar. The applicability in routine clinical practice is further strengthened, as the present approach, in contrast to other recently proposed dark- and black-blood LGE techniques, is readily available without the need for scanner adjustments, extensive optimizations, or additional training.
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Affiliation(s)
- Robert J. Holtackers
- Department of Radiology, Maastricht University Medical Centre, Maastricht, the Netherlands
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, 4th Floor, Lambeth Wing, St Thomas’ Hospital, London, SE1 7EH UK
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, the Netherlands
| | - Caroline M. Van De Heyning
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, 4th Floor, Lambeth Wing, St Thomas’ Hospital, London, SE1 7EH UK
- Department of Cardiology, St Thomas’ Hospital, London, UK
- Department of Cardiology, Antwerp University Hospital, Edegem, Belgium
- Cardiovascular Diseases, University of Antwerp, Antwerp, Belgium
| | - Muhummad Sohaib Nazir
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, 4th Floor, Lambeth Wing, St Thomas’ Hospital, London, SE1 7EH UK
- Department of Cardiology, St Thomas’ Hospital, London, UK
| | - Imran Rashid
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, 4th Floor, Lambeth Wing, St Thomas’ Hospital, London, SE1 7EH UK
- Department of Cardiology, St Thomas’ Hospital, London, UK
| | - Ioannis Ntalas
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, 4th Floor, Lambeth Wing, St Thomas’ Hospital, London, SE1 7EH UK
- Department of Cardiology, St Thomas’ Hospital, London, UK
| | - Haseeb Rahman
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, 4th Floor, Lambeth Wing, St Thomas’ Hospital, London, SE1 7EH UK
- Department of Cardiology, St Thomas’ Hospital, London, UK
| | - René M. Botnar
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, 4th Floor, Lambeth Wing, St Thomas’ Hospital, London, SE1 7EH UK
- Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Amedeo Chiribiri
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, 4th Floor, Lambeth Wing, St Thomas’ Hospital, London, SE1 7EH UK
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Delattre BMA, Boudabbous S, Hansen C, Neroladaki A, Hachulla AL, Vargas MI. Compressed sensing MRI of different organs: ready for clinical daily practice? Eur Radiol 2019; 30:308-319. [PMID: 31264014 DOI: 10.1007/s00330-019-06319-0] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Revised: 05/28/2019] [Accepted: 06/11/2019] [Indexed: 10/26/2022]
Abstract
OBJECTIVES The aim was to evaluate the image quality and sensitivity to artifacts of compressed sensing (CS) acceleration technique, applied to 3D or breath-hold sequences in different clinical applications from brain to knee. METHODS CS with an acceleration from 30 to 60% and conventional MRI sequences were performed in 10 different applications in 107 patients, leading to 120 comparisons. Readers were blinded to the technique for quantitative (contrast-to-noise ratio or functional measurements for cardiac cine) and qualitative (image quality, artifacts, diagnostic findings, and preference) image analyses. RESULTS No statistically significant difference in image quality or artifacts was found for each sequence except for the cardiac cine CS for one of both readers and for the wrist 3D proton density (PD)-weighted CS sequence which showed less motion artifacts due to the reduced acquisition time. The contrast-to-noise ratio was lower for the elbow CS sequence but not statistically different in all other applications. Diagnostic findings were similar between conventional and CS sequence for all the comparisons except for four cases where motion artifacts corrupted either the conventional or the CS sequence. CONCLUSIONS The evaluated CS sequences are ready to be used in clinical daily practice except for the elbow application which requires a lower acceleration. The CS factor should be tuned for each organ and sequence to obtain good image quality. It leads to 30% to 60% acceleration in the applications evaluated in this study which has a significant impact on clinical workflow. KEY POINTS • Clinical implementation of compressed sensing (CS) reduced scan times of at least 30% with only minor penalty in image quality and no change in diagnostic findings. • The CS acceleration factor has to be tuned separately for each organ and sequence to guarantee similar image quality than conventional acquisition. • At least 30% and up to 60% acceleration is feasible in specific sequences in clinical routine.
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Affiliation(s)
| | - Sana Boudabbous
- Division of Radiology, Geneva University Hospitals, Rue Gabrielle-Perret-Gentil 4, 1211, Geneva 14, Switzerland
| | - Catrina Hansen
- Division of Radiology, Geneva University Hospitals, Rue Gabrielle-Perret-Gentil 4, 1211, Geneva 14, Switzerland
| | - Angeliki Neroladaki
- Division of Radiology, Geneva University Hospitals, Rue Gabrielle-Perret-Gentil 4, 1211, Geneva 14, Switzerland
| | - Anne-Lise Hachulla
- Division of Radiology, Geneva University Hospitals, Rue Gabrielle-Perret-Gentil 4, 1211, Geneva 14, Switzerland
| | - Maria Isabel Vargas
- Division of Neuroradiology, Geneva University Hospitals , Geneva, Switzerland
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Mukherjee RK, Whitaker J, Williams SE, Razavi R, O'Neill MD. Magnetic resonance imaging guidance for the optimization of ventricular tachycardia ablation. Europace 2019; 20:1721-1732. [PMID: 29584897 PMCID: PMC6212773 DOI: 10.1093/europace/euy040] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Accepted: 02/19/2018] [Indexed: 01/02/2023] Open
Abstract
Catheter ablation has an important role in the management of patients with ventricular tachycardia (VT) but is limited by modest long-term success rates. Magnetic resonance imaging (MRI) can provide valuable anatomic and functional information as well as potentially improve identification of target sites for ablation. A major limitation of current MRI protocols is the spatial resolution required to identify the areas of tissue responsible for VT but recent developments have led to new strategies which may improve substrate assessment. Potential ways in which detailed information gained from MRI may be utilized during electrophysiology procedures include image integration or performing a procedure under real-time MRI guidance. Image integration allows pre-procedural magnetic resonance (MR) images to be registered with electroanatomical maps to help guide VT ablation and has shown promise in preliminary studies. However, multiple errors can arise during this process due to the registration technique used, changes in ventricular geometry between the time of MRI and the ablation procedure, respiratory and cardiac motion. As isthmus sites may only be a few millimetres wide, reducing these errors may be critical to improve outcomes in VT ablation. Real-time MR-guided intervention has emerged as an alternative solution to address the limitations of pre-acquired imaging to guide ablation. There is now a growing body of literature describing the feasibility, techniques, and potential applications of real-time MR-guided electrophysiology. We review whether real-time MR-guided intervention could be applied in the setting of VT ablation and the potential challenges that need to be overcome.
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Affiliation(s)
- Rahul K Mukherjee
- School of Biomedical Engineering and Imaging Sciences, 4th Floor, North Wing, St Thomas' Hospital, King's College London, London, UK
| | - John Whitaker
- School of Biomedical Engineering and Imaging Sciences, 4th Floor, North Wing, St Thomas' Hospital, King's College London, London, UK
| | - Steven E Williams
- School of Biomedical Engineering and Imaging Sciences, 4th Floor, North Wing, St Thomas' Hospital, King's College London, London, UK.,Department of Cardiology, Guy's and St Thomas' Hospital NHS Foundation Trust, London, UK
| | - Reza Razavi
- School of Biomedical Engineering and Imaging Sciences, 4th Floor, North Wing, St Thomas' Hospital, King's College London, London, UK
| | - Mark D O'Neill
- School of Biomedical Engineering and Imaging Sciences, 4th Floor, North Wing, St Thomas' Hospital, King's College London, London, UK.,Department of Cardiology, Guy's and St Thomas' Hospital NHS Foundation Trust, London, UK
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Foley JR, Fent GJ, Garg P, Broadbent DA, Dobson LE, Chew PG, Brown LA, Swoboda PP, Plein S, Higgins DM, Greenwood JP. Feasibility study of a single breath-hold, 3D mDIXON pulse sequence for late gadolinium enhancement imaging of ischemic scar. J Magn Reson Imaging 2018; 49:1437-1445. [DOI: 10.1002/jmri.26519] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2018] [Revised: 09/05/2018] [Accepted: 09/06/2018] [Indexed: 11/11/2022] Open
Affiliation(s)
- James R.J. Foley
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Leeds Institute of Cardiovascular and Metabolic Medicine; University of Leeds; Leeds UK
| | - Graham J. Fent
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Leeds Institute of Cardiovascular and Metabolic Medicine; University of Leeds; Leeds UK
| | - Pankaj Garg
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Leeds Institute of Cardiovascular and Metabolic Medicine; University of Leeds; Leeds UK
| | - David A. Broadbent
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Leeds Institute of Cardiovascular and Metabolic Medicine; University of Leeds; Leeds UK
- Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust; Leeds UK
| | - Laura E. Dobson
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Leeds Institute of Cardiovascular and Metabolic Medicine; University of Leeds; Leeds UK
| | - Pei G. Chew
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Leeds Institute of Cardiovascular and Metabolic Medicine; University of Leeds; Leeds UK
| | - Louise A.E. Brown
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Leeds Institute of Cardiovascular and Metabolic Medicine; University of Leeds; Leeds UK
| | - Peter P. Swoboda
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Leeds Institute of Cardiovascular and Metabolic Medicine; University of Leeds; Leeds UK
| | - Sven Plein
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Leeds Institute of Cardiovascular and Metabolic Medicine; University of Leeds; Leeds UK
| | | | - John P. Greenwood
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Leeds Institute of Cardiovascular and Metabolic Medicine; University of Leeds; Leeds UK
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Jang J, Tschabrunn CM, Barkagan M, Anter E, Menze B, Nezafat R. Three-dimensional holographic visualization of high-resolution myocardial scar on HoloLens. PLoS One 2018; 13:e0205188. [PMID: 30296291 PMCID: PMC6175509 DOI: 10.1371/journal.pone.0205188] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2018] [Accepted: 08/28/2018] [Indexed: 11/18/2022] Open
Abstract
Visualization of the complex 3D architecture of myocardial scar could improve guidance of radio-frequency ablation in the treatment of ventricular tachycardia (VT). In this study, we sought to develop a framework for 3D holographic visualization of myocardial scar, imaged using late gadolinium enhancement (LGE), on the augmented reality HoloLens. 3D holographic LGE model was built using the high-resolution 3D LGE image. Smooth endo/epicardial surface meshes were generated using Poisson surface reconstruction. For voxel-wise 3D scar model, every scarred voxel was rendered into a cube which carries the actual resolution of the LGE sequence. For surface scar model, scar information was projected on the endocardial surface mesh. Rendered layers were blended with different transparency and color, and visualized on HoloLens. A pilot animal study was performed where 3D holographic visualization of the scar was performed in 5 swines who underwent controlled infarction and electroanatomic mapping to identify VT substrate. 3D holographic visualization enabled assessment of the complex 3D scar architecture with touchless interaction in a sterile environment. Endoscopic view allowed visualization of scar from the ventricular chambers. Upon completion of the animal study, operator and mapping specialist independently completed the perceived usefulness questionnaire in the six-item usefulness scale. Operator and mapping specialist found it useful (usefulness rating: operator, 5.8; mapping specialist, 5.5; 1–7 scale) to have scar information during the intervention. HoloLens 3D LGE provides a true 3D perception of the complex scar architecture with immersive experience to visualize scar in an interactive and interpretable 3D approach, which may facilitate MR-guided VT ablation.
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Affiliation(s)
- Jihye Jang
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, United States of America
- Department of Computer Science, Technical University of Munich, Munich, Germany
| | - Cory M. Tschabrunn
- Division of Cardiovascular Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
| | - Michael Barkagan
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, United States of America
| | - Elad Anter
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, United States of America
| | - Bjoern Menze
- Department of Computer Science, Technical University of Munich, Munich, Germany
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, United States of America
- * E-mail:
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von Spiczak J, Mannil M, Kozerke S, Alkadhi H, Manka R. 3D image fusion of whole-heart dynamic cardiac MR perfusion and late gadolinium enhancement: Intuitive delineation of myocardial hypoperfusion and scar. J Magn Reson Imaging 2018; 48:1129-1138. [DOI: 10.1002/jmri.26020] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2017] [Accepted: 03/01/2018] [Indexed: 11/05/2022] Open
Affiliation(s)
- Jochen von Spiczak
- Institute of Diagnostic and Interventional Radiology; University Hospital Zurich; Zurich Switzerland
| | - Manoj Mannil
- Institute of Diagnostic and Interventional Radiology; University Hospital Zurich; Zurich Switzerland
| | - Sebastian Kozerke
- Institute for Biomedical Engineering; University and ETH Zurich; Zurich Switzerland
| | - Hatem Alkadhi
- Institute of Diagnostic and Interventional Radiology; University Hospital Zurich; Zurich Switzerland
| | - Robert Manka
- Institute of Diagnostic and Interventional Radiology; University Hospital Zurich; Zurich Switzerland
- Institute for Biomedical Engineering; University and ETH Zurich; Zurich Switzerland
- Department of Cardiology; University Heart Center, University Hospital Zurich; Zurich Switzerland
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37
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Fahmy AS, Neisius U, Tsao CW, Berg S, Goddu E, Pierce P, Basha TA, Ngo L, Manning WJ, Nezafat R. Gray blood late gadolinium enhancement cardiovascular magnetic resonance for improved detection of myocardial scar. J Cardiovasc Magn Reson 2018; 20:22. [PMID: 29562921 PMCID: PMC5863465 DOI: 10.1186/s12968-018-0442-2] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2017] [Accepted: 03/02/2018] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Low scar-to-blood contrast in late gadolinium enhanced (LGE) MRI limits the visualization of scars adjacent to the blood pool. Nulling the blood signal improves scar detection but results in lack of contrast between myocardium and blood, which makes clinical evaluation of LGE images more difficult. METHODS GB-LGE contrast is achieved through partial suppression of the blood signal using T2 magnetization preparation between the inversion pulse and acquisition. The timing parameters of GB-LGE sequence are determined by optimizing a cost-function representing the desired tissue contrast. The proposed 3D GB-LGE sequence was evaluated using phantoms, human subjects (n = 45) and a swine model of myocardial infarction (n = 5). Two independent readers subjectively evaluated the image quality and ability to identify and localize scarring in GB-LGE compared to black-blood LGE (BB-LGE) (i.e., with complete blood nulling) and conventional (bright-blood) LGE. RESULTS GB-LGE contrast was successfully generated in phantoms and all in-vivo scans. The scar-to-blood contrast was improved in GB-LGE compared to conventional LGE in humans (1.1 ± 0.5 vs. 0.6 ± 0.4, P < 0.001) and in animals (1.5 ± 0.2 vs. -0.03 ± 0.2). In patients, GB-LGE detected more tissue scarring compared to BB-LGE and conventional LGE. The subjective scores of the GB-LGE ability for localizing LV scar and detecting papillary scar were improved as compared with both BB-LGE (P < 0.024) and conventional LGE (P < 0.001). In the swine infarction model, GB-LGE scores for the ability to localize LV scar scores were consistently higher than those of both BB-LGE and conventional-LGE. CONCLUSION GB-LGE imaging improves the ability to identify and localize myocardial scarring compared to both BB-LGE and conventional LGE. Further studies are warranted to histologically validate GB-LGE.
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Affiliation(s)
- Ahmed S. Fahmy
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 USA
- Biomedical Engineering Department, School of Engineering, Cairo University, Giza, Egypt
| | - Ulf Neisius
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 USA
| | - Connie W. Tsao
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 USA
| | - Sophie Berg
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 USA
| | - Elizabeth Goddu
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 USA
| | - Patrick Pierce
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 USA
| | - Tamer A. Basha
- Biomedical Engineering Department, School of Engineering, Cairo University, Giza, Egypt
| | - Long Ngo
- Department of Medicine (Division of General Medicine and Primary Care), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA USA
| | - Warren J. Manning
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 USA
- Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA USA
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 USA
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38
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Toledano-Massiah S, Sayadi A, de Boer R, Gelderblom J, Mahdjoub R, Gerber S, Zuber M, Zins M, Hodel J. Accuracy of the Compressed Sensing Accelerated 3D-FLAIR Sequence for the Detection of MS Plaques at 3T. AJNR Am J Neuroradiol 2018; 39:454-458. [PMID: 29348137 DOI: 10.3174/ajnr.a5517] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2017] [Accepted: 11/03/2017] [Indexed: 01/21/2023]
Abstract
BACKGROUND AND PURPOSE The use of 3D FLAIR improves the detection of brain lesions in MS patients, but requires long acquisition times. Compressed sensing reduces acquisition time by using the sparsity of MR images to randomly undersample the k-space. Our aim was to compare the image quality and diagnostic performance of 3D-FLAIR with and without compressed sensing for the detection of multiple sclerosis lesions at 3T. MATERIALS AND METHODS Twenty-three patients with relapsing-remitting MS underwent both conventional 3D-FLAIR and compressed sensing 3D-FLAIR on a 3T scanner (reduction in scan time 1 minute 25 seconds, 27%; compressed sensing factor of 1.3). Two blinded readers independently evaluated both conventional and compressed sensing FLAIR for image quality (SNR and contrast-to-noise ratio) and the number of MS lesions visible in the periventricular, intra-juxtacortical, infratentorial, and optic nerve regions. The volume of white matter lesions was measured with automatic postprocessing segmentation software for each FLAIR sequence. RESULTS Image quality and the number of MS lesions detected by the readers were similar between the 2 FLAIR acquisitions (P = .74 and P = .094, respectively). Almost perfect agreement was found between both FLAIR acquisitions for total MS lesion count (Lin concordance correlation coefficient = 0.99). Agreement between conventional and compressed sensing FLAIR was almost perfect for periventricular and infratentorial lesions and substantial for intrajuxtacortical and optic nerve lesions. Postprocessing with the segmentation software did not reveal a significant difference between conventional and compressed sensing FLAIR in total MS lesion volume (P = .63) or the number of MS lesions (P = .15). CONCLUSIONS With a compressed sensing factor of 1.3, 3D-FLAIR is 27% faster and preserves diagnostic performance for the detection of MS plaques at 3T.
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Affiliation(s)
| | - A Sayadi
- From the Departments of Radiology (S.T.-M., A.S., S.G., M.Zins)
| | - R de Boer
- Quantib B.V. (R.d.B., J.G.), Rotterdam, the Netherlands
| | - J Gelderblom
- Quantib B.V. (R.d.B., J.G.), Rotterdam, the Netherlands
| | | | - S Gerber
- From the Departments of Radiology (S.T.-M., A.S., S.G., M.Zins)
| | - M Zuber
- Neurology (M.Zuber), Fondation Hôpital Saint-Joseph, Paris, France
| | - M Zins
- From the Departments of Radiology (S.T.-M., A.S., S.G., M.Zins)
| | - J Hodel
- Department of Neuroradiology (J.H.), AP-HP, Hôpitaux Universitaires Henri Mondor, Université Paris est, Créteil, France
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