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Lindsey ML, Kassiri Z, Virag JAI, de Castro Brás LE, Scherrer-Crosbie M. Guidelines for measuring cardiac physiology in mice. Am J Physiol Heart Circ Physiol 2018; 314:H733-H752. [PMID: 29351456 PMCID: PMC5966769 DOI: 10.1152/ajpheart.00339.2017] [Citation(s) in RCA: 252] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Cardiovascular disease is a leading cause of death, and translational research is needed to understand better mechanisms whereby the left ventricle responds to injury. Mouse models of heart disease have provided valuable insights into mechanisms that occur during cardiac aging and in response to a variety of pathologies. The assessment of cardiovascular physiological responses to injury or insult is an important and necessary component of this research. With increasing consideration for rigor and reproducibility, the goal of this guidelines review is to provide best-practice information regarding how to measure accurately cardiac physiology in animal models. In this article, we define guidelines for the measurement of cardiac physiology in mice, as the most commonly used animal model in cardiovascular research. Listen to this article’s corresponding podcast at http://ajpheart.podbean.com/e/guidelines-for-measuring-cardiac-physiology-in-mice/.
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Affiliation(s)
- Merry L Lindsey
- Department of Physiology and Biophysics, Mississippi Center for Heart Research, University of Mississippi Medical Center , Jackson, Mississippi.,Research Service, G.V. (Sonny) Montgomery Veterans Affairs Medical Center , Jackson, Mississippi
| | - Zamaneh Kassiri
- Department of Physiology, Cardiovascular Research Centre, Mazankowski Alberta Heart Institute, University of Alberta , Edmonton, Alberta , Canada
| | - Jitka A I Virag
- Department of Physiology, Brody School of Medicine, East Carolina University , Greenville, North Carolina
| | - Lisandra E de Castro Brás
- Department of Physiology, Brody School of Medicine, East Carolina University , Greenville, North Carolina
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Vanhoutte L, Gerber BL, Gallez B, Po C, Magat J, Balligand JL, Feron O, Moniotte S. High field magnetic resonance imaging of rodents in cardiovascular research. Basic Res Cardiol 2016; 111:46. [PMID: 27287250 DOI: 10.1007/s00395-016-0565-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2015] [Accepted: 06/01/2016] [Indexed: 02/07/2023]
Abstract
Transgenic and gene knockout rodent models are primordial to study pathophysiological processes in cardiovascular research. Over time, cardiac MRI has become a gold standard for in vivo evaluation of such models. Technical advances have led to the development of magnets with increasingly high field strength, allowing specific investigation of cardiac anatomy, global and regional function, viability, perfusion or vascular parameters. The aim of this report is to provide a review of the various sequences and techniques available to image mice on 7-11.7 T magnets and relevant to the clinical setting in humans. Specific technical aspects due to the rise of the magnetic field are also discussed.
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Affiliation(s)
- Laetitia Vanhoutte
- Department of Paediatric Cardiology, Cliniques universitaires Saint Luc, Université Catholique de Louvain (UCL), Brussels, Belgium. .,Pole of Pharmacology and Therapeutics (FATH), Institute of Experimental and Clinical Research (IREC), Université Catholique de Louvain (UCL), Brussels, Belgium.
| | - Bernhard L Gerber
- Division of Cardiology, Cliniques universitaires Saint Luc, Université Catholique de Louvain (UCL), Brussels, Belgium.,Pole of Cardiovascular Research (CARD), Institute of Experimental and Clinical Research (IREC), Université Catholique de Louvain (UCL), Brussels, Belgium
| | - Bernard Gallez
- Biomedical Magnetic Resonance Unit (REMA), Louvain Drug Research Institute (LDRI), Université Catholique de Louvain (UCL), Brussels, Belgium
| | - Chrystelle Po
- CNRS, ICube, FMTS, Institut de Physique Biologique, Faculté de Médecine, Université de Strasbourg, Strasbourg, France
| | - Julie Magat
- L'Institut de RYthmologie et de Modélisation Cardiaque (LIRYC), Inserm U1045, Bordeaux, France
| | - Jean-Luc Balligand
- Pole of Pharmacology and Therapeutics (FATH), Institute of Experimental and Clinical Research (IREC), Université Catholique de Louvain (UCL), Brussels, Belgium
| | - Olivier Feron
- Pole of Pharmacology and Therapeutics (FATH), Institute of Experimental and Clinical Research (IREC), Université Catholique de Louvain (UCL), Brussels, Belgium
| | - Stéphane Moniotte
- Department of Paediatric Cardiology, Cliniques universitaires Saint Luc, Université Catholique de Louvain (UCL), Brussels, Belgium
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Bakermans AJ, Abdurrachim D, Moonen RPM, Motaal AG, Prompers JJ, Strijkers GJ, Vandoorne K, Nicolay K. Small animal cardiovascular MR imaging and spectroscopy. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2015; 88-89:1-47. [PMID: 26282195 DOI: 10.1016/j.pnmrs.2015.03.001] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2014] [Revised: 03/09/2015] [Accepted: 03/09/2015] [Indexed: 06/04/2023]
Abstract
The use of MR imaging and spectroscopy for studying cardiovascular disease processes in small animals has increased tremendously over the past decade. This is the result of the remarkable advances in MR technologies and the increased availability of genetically modified mice. MR techniques provide a window on the entire timeline of cardiovascular disease development, ranging from subtle early changes in myocardial metabolism that often mark disease onset to severe myocardial dysfunction associated with end-stage heart failure. MR imaging and spectroscopy techniques play an important role in basic cardiovascular research and in cardiovascular disease diagnosis and therapy follow-up. This is due to the broad range of functional, structural and metabolic parameters that can be quantified by MR under in vivo conditions non-invasively. This review describes the spectrum of MR techniques that are employed in small animal cardiovascular disease research and how the technological challenges resulting from the small dimensions of heart and blood vessels as well as high heart and respiratory rates, particularly in mice, are tackled.
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Affiliation(s)
- Adrianus J Bakermans
- Biomedical NMR, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Desiree Abdurrachim
- Biomedical NMR, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Rik P M Moonen
- Biomedical NMR, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Abdallah G Motaal
- Biomedical NMR, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Jeanine J Prompers
- Biomedical NMR, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Gustav J Strijkers
- Biomedical NMR, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Katrien Vandoorne
- Biomedical NMR, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Klaas Nicolay
- Biomedical NMR, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
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Srinivasan A, Sundaram S. Applications of deformable models for in-dopth analysis and feature extraction from medical images—A review. PATTERN RECOGNITION AND IMAGE ANALYSIS 2013. [DOI: 10.1134/s1054661813020132] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Punithakumar K, Ben Ayed I, Islam A, Goela A, Ross IG, Chong J, Li S. Regional heart motion abnormality detection: an information theoretic approach. Med Image Anal 2013; 17:311-24. [PMID: 23375719 DOI: 10.1016/j.media.2012.11.007] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2011] [Revised: 10/11/2012] [Accepted: 11/30/2012] [Indexed: 02/04/2023]
Abstract
Tracking regional heart motion and detecting the corresponding abnormalities play an essential role in the diagnosis of cardiovascular diseases. Based on functional images, which are subject to noise and segmentation/registration inaccuracies, regional heart motion analysis is acknowledged as a difficult problem and, therefore, incorporation of prior knowledge is desirable to enhance accuracy. Given noisy data and a nonlinear dynamic model to describe myocardial motion, an unscented Kalman smoother is proposed in this study to estimate the myocardial points. Due to the similarity between the statistical information of normal and abnormal heart motions, detecting and classifying abnormality is a challenging problem. We use the Shannon's differential entropy of the distributions of potential classifier features to detect and locate regional heart motion abnormality. A naive Bayes classifier algorithm is constructed from the Shannon's differential entropy of different features to automatically detect abnormal functional regions of the myocardium. Using 174 segmented short-axis magnetic resonance cines obtained from 58 subjects (21 normal and 37 abnormal), the proposed method is quantitatively evaluated by comparison with ground truth classifications by radiologists over 928 myocardial segments. The proposed method performed significantly better than other recent methods, and yielded an accuracy of 86.5% (base), 89.4% (mid-cavity) and 84.5% (apex). The overall classification accuracy was 87.1%. Furthermore, standard kappa statistic comparisons between the proposed method and visual wall motion scoring by radiologists showed that the proposed algorithm can yield a kappa measure of 0.73.
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Affiliation(s)
- Kumaradevan Punithakumar
- Servier Virtual Cardiac Centre, Department of Radiology & Diagnostic Imaging, University of Alberta, Edmonton, AB, Canada.
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Gilliam AD, Epstein FH. Automated motion estimation for 2-D cine DENSE MRI. IEEE TRANSACTIONS ON MEDICAL IMAGING 2012; 31:1669-81. [PMID: 22575669 PMCID: PMC3968545 DOI: 10.1109/tmi.2012.2195194] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
Cine displacement encoding with stimulated echoes (DENSE) is a magnetic resonance (MR) method that directly encodes tissue displacement into MR phase images. This technique has successfully interrogated many forms of tissue motion, but is most commonly used to evaluate cardiac mechanics. Currently, motion analysis from cine DENSE images requires manually delineated anatomical structures. An automated analysis would improve measurement throughput, simplify data interpretation, and potentially access important physiological information during the MR exam. In this paper, we present the first fully automated solution for the estimation of tissue motion and strain from 2-D cine DENSE data. Results using both simulated and human cardiac cine DENSE data indicate good agreement between the automated algorithm and the standard semi-manual analysis method.
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Affiliation(s)
| | - Frederick H. Epstein
- Departments of Biomedical Engineering and Radiology, University of Virginia, Charlottesville, VA 22904 USA ()
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Ibrahim ESH. Myocardial tagging by cardiovascular magnetic resonance: evolution of techniques--pulse sequences, analysis algorithms, and applications. J Cardiovasc Magn Reson 2011; 13:36. [PMID: 21798021 PMCID: PMC3166900 DOI: 10.1186/1532-429x-13-36] [Citation(s) in RCA: 187] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2011] [Accepted: 07/28/2011] [Indexed: 02/06/2023] Open
Abstract
Cardiovascular magnetic resonance (CMR) tagging has been established as an essential technique for measuring regional myocardial function. It allows quantification of local intramyocardial motion measures, e.g. strain and strain rate. The invention of CMR tagging came in the late eighties, where the technique allowed for the first time for visualizing transmural myocardial movement without having to implant physical markers. This new idea opened the door for a series of developments and improvements that continue up to the present time. Different tagging techniques are currently available that are more extensive, improved, and sophisticated than they were twenty years ago. Each of these techniques has different versions for improved resolution, signal-to-noise ratio (SNR), scan time, anatomical coverage, three-dimensional capability, and image quality. The tagging techniques covered in this article can be broadly divided into two main categories: 1) Basic techniques, which include magnetization saturation, spatial modulation of magnetization (SPAMM), delay alternating with nutations for tailored excitation (DANTE), and complementary SPAMM (CSPAMM); and 2) Advanced techniques, which include harmonic phase (HARP), displacement encoding with stimulated echoes (DENSE), and strain encoding (SENC). Although most of these techniques were developed by separate groups and evolved from different backgrounds, they are in fact closely related to each other, and they can be interpreted from more than one perspective. Some of these techniques even followed parallel paths of developments, as illustrated in the article. As each technique has its own advantages, some efforts have been made to combine different techniques together for improved image quality or composite information acquisition. In this review, different developments in pulse sequences and related image processing techniques are described along with the necessities that led to their invention, which makes this article easy to read and the covered techniques easy to follow. Major studies that applied CMR tagging for studying myocardial mechanics are also summarized. Finally, the current article includes a plethora of ideas and techniques with over 300 references that motivate the reader to think about the future of CMR tagging.
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Carranza-Herrezuelo N, Bajo A, Sroubek F, Santamarta C, Cristobal G, Santos A, Ledesma-Carbayo MJ. Motion estimation of tagged cardiac magnetic resonance images using variational techniques. Comput Med Imaging Graph 2010; 34:514-22. [PMID: 20413267 DOI: 10.1016/j.compmedimag.2010.03.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2009] [Revised: 01/20/2010] [Accepted: 03/18/2010] [Indexed: 10/19/2022]
Abstract
This work presents a new method for motion estimation of tagged cardiac magnetic resonance sequences based on variational techniques. The variational method has been improved by adding a new term in the optical flow equation that incorporates tracking points with high stability of phase. Results were obtained through simulated and real data, and were validated by manual tracking and with respect to a reference state-of-the-art method: harmonic phase imaging (HARP). The error, measured in pixels per frame, obtained with the proposed variational method is one order of magnitude smaller than the one achieved by the reference method, and it requires a lower computational cost.
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Pattichis CS, Schizas CN, Pattichis MS, Micheli-Tzanakou E, Kyriakou EC, Fotiadis DI. Introduction to the special section on computational intelligence in medical systems. IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE : A PUBLICATION OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY 2009; 13:667-672. [PMID: 19726262 DOI: 10.1109/titb.2009.2030025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
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