1
|
Winter L, Periquito J, Kolbitsch C, Pellicer-Guridi R, Nunes RG, Häuer M, Broche L, O'Reilly T. Open-source magnetic resonance imaging: Improving access, science, and education through global collaboration. NMR IN BIOMEDICINE 2024; 37:e5052. [PMID: 37986655 DOI: 10.1002/nbm.5052] [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: 01/08/2023] [Revised: 08/01/2023] [Accepted: 09/09/2023] [Indexed: 11/22/2023]
Abstract
Open-source practices and resources in magnetic resonance imaging (MRI) have increased substantially in recent years. This trend started with software and data being published open-source and, more recently, open-source hardware designs have become increasingly available. These developments towards a culture of sharing and establishing nonexclusive global collaborations have already improved the reproducibility and reusability of code and designs, while providing a more inclusive approach, especially for low-income settings. Community-driven standardization and documentation efforts are further strengthening and expanding these milestones. The future of open-source MRI is bright and we have just started to discover its full collaborative potential. In this review we will give an overview of open-source software and open-source hardware projects in human MRI research.
Collapse
Affiliation(s)
- Lukas Winter
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - João Periquito
- Department of Infection, Immunity & Cardiovascular Disease, The University of Sheffield, Sheffield, UK
| | - Christoph Kolbitsch
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | | | - Rita G Nunes
- Institute for Systems and Robotics and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Martin Häuer
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
- Open Source Ecology Germany e.V. (nonprofit), Berlin, Germany
| | - Lionel Broche
- Biomedical Physics, University of Aberdeen, Aberdeen, UK
| | - Tom O'Reilly
- Leiden University Medical Center (LUMC), Leiden, The Netherlands
| |
Collapse
|
2
|
Liu Q, Ning L, Shaik IA, Liao C, Gagoski B, Bilgic B, Grissom W, Nielsen JF, Zaitsev M, Rathi Y. Reduced cross-scanner variability using vendor-agnostic sequences for single-shell diffusion MRI. Magn Reson Med 2024; 92:246-256. [PMID: 38469671 PMCID: PMC11055665 DOI: 10.1002/mrm.30062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 01/31/2024] [Accepted: 02/05/2024] [Indexed: 03/13/2024]
Abstract
PURPOSE To reduce the inter-scanner variability of diffusion MRI (dMRI) measures between scanners from different vendors by developing a vendor-neutral dMRI pulse sequence using the open-source vendor-agnostic Pulseq platform. METHODS We implemented a standard EPI based dMRI sequence in Pulseq. We tested it on two clinical scanners from different vendors (Siemens Prisma and GE Premier), systematically evaluating and comparing the within- and inter-scanner variability across the vendors, using both the vendor-provided and Pulseq dMRI sequences. Assessments covered both a diffusion phantom and three human subjects, using standard error (SE) and Lin's concordance correlation to measure the repeatability and reproducibility of standard DTI metrics including fractional anisotropy (FA) and mean diffusivity (MD). RESULTS Identical dMRI sequences were executed on both scanners using Pulseq. On the phantom, the Pulseq sequence showed more than a 2.5× reduction in SE (variability) across Siemens and GE scanners. Furthermore, Pulseq sequences exhibited markedly reduced SE in-vivo, maintaining scan-rescan repeatability while delivering lower variability in FA and MD (more than 50% reduction in cortical/subcortical regions) compared to vendor-provided sequences. CONCLUSION The Pulseq diffusion sequence reduces the cross-scanner variability for both phantom and in-vivo data, which will benefit multi-center neuroimaging studies and improve the reproducibility of neuroimaging studies.
Collapse
Affiliation(s)
- Qiang Liu
- Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Lipeng Ning
- Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Imam Ahmed Shaik
- Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Congyu Liao
- Department of Radiology, Stanford University, Stanford, CA, United States
| | - Borjan Gagoski
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, Boston, MA, United States
| | - Berkin Bilgic
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Harvard/MIT Health Sciences and Technology, Cambridge, MA, United States
| | - William Grissom
- Department of Biomedical Engineering, Case School of Medicine, Case Western Reserve University, Cleveland, OH, United States
| | - Jon-Fredrik Nielsen
- fMRI Laboratory and Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States
| | - Maxim Zaitsev
- Division of Medical Physics, Department of Radiology, University Medical Center Freiburg, Freiburg, Germany
| | - Yogesh Rathi
- Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| |
Collapse
|
3
|
Foley MJ, Rajkumar CA, Ahmed-Jushuf F, Simader F, Pathimagaraj RH, Nijjer S, Sen S, Petraco R, Clesham G, Johnson T, Harrell FE, Kellman P, Francis D, Shun-Shin M, Howard J, Cole GD, Al-Lamee R. A double-blind, randomised, placebo-controlled trial of the coronary sinus Reducer in refractory angina: design and rationale of the ORBITA-COSMIC trial. EUROINTERVENTION 2024; 20:e216-e223. [PMID: 38214677 PMCID: PMC10836388 DOI: 10.4244/eij-d-23-00567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 11/12/2023] [Indexed: 01/13/2024]
Abstract
The coronary sinus Reducer (CSR) is an hourglass-shaped device which creates an artificial stenosis in the coronary sinus. Whilst placebo-controlled data show an improvement in angina, these results are unreplicated and are the subject of further confirmatory research. The mechanism of action of this unintuitive therapy is unknown. The Coronary Sinus Reducer Objective Impact on Symptoms, MRI Ischaemia, and Microvascular Resistance (ORBITA-COSMIC) trial is a randomised, placebo-controlled, double-blind trial investigating the efficacy of the CSR. Patients with (i) established epicardial coronary artery disease, (ii) angina on maximally tolerated antianginal medication, (iii) evidence of myocardial ischaemia and (iv) no further options for percutaneous coronary intervention or coronary artery bypass grafting will be enrolled. Upon enrolment, angina and quality-of-life questionnaires, treadmill exercise testing and quantitative stress perfusion cardiac magnetic resonance (CMR) imaging will be performed. Participants will record their symptoms daily on a smartphone application throughout the trial. After a 2-week symptom assessment phase, participants will be randomised in the cardiac catheterisation laboratory to CSR or a placebo procedure. After 6 months of blinded follow-up, all prerandomisation tests will be repeated. A prespecified subgroup will undergo invasive coronary physiology assessment at prerandomisation and follow-up. The primary outcome is stress myocardial blood flow on CMR. Secondary outcomes include angina frequency, quality of life and treadmill exercise time. (ClinicalTrials.gov: NCT04892537).
Collapse
Affiliation(s)
- Michael J Foley
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Christopher A Rajkumar
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Fiyyaz Ahmed-Jushuf
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Florentina Simader
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Rachel H Pathimagaraj
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Sukhjinder Nijjer
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Sayan Sen
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Ricardo Petraco
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | | | - Thomas Johnson
- Bristol Heart Institute, University Hospitals Bristol NHS Foundation Trust, Bristol, United Kingdom
| | - Frank E Harrell
- Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Peter Kellman
- National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD, USA
| | - Darrel Francis
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Matthew Shun-Shin
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - James Howard
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Graham D Cole
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Rasha Al-Lamee
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| |
Collapse
|
4
|
Campbell-Washburn AE, Varghese J, Nayak KS, Ramasawmy R, Simonetti OP. Cardiac MRI at Low Field Strengths. J Magn Reson Imaging 2024; 59:412-430. [PMID: 37530545 PMCID: PMC10834858 DOI: 10.1002/jmri.28890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 06/16/2023] [Accepted: 06/16/2023] [Indexed: 08/03/2023] Open
Abstract
Cardiac MR imaging is well established for assessment of cardiovascular structure and function, myocardial scar, quantitative flow, parametric mapping, and myocardial perfusion. Despite the clear evidence supporting the use of cardiac MRI for a wide range of indications, it is underutilized clinically. Recent developments in low-field MRI technology, including modern data acquisition and image reconstruction methods, are enabling high-quality low-field imaging that may improve the cost-benefit ratio for cardiac MRI. Studies to-date confirm that low-field MRI offers high measurement concordance and consistent interpretation with clinical imaging for several routine sequences. Moreover, low-field MRI may enable specific new clinical opportunities for cardiac imaging such as imaging near metal implants, MRI-guided interventions, combined cardiopulmonary assessment, and imaging of patients with severe obesity. In this review, we discuss the recent progress in low-field cardiac MRI with a focus on technical developments and early clinical validation studies. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 1.
Collapse
Affiliation(s)
- Adrienne E Campbell-Washburn
- Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda MD USA
| | - Juliet Varghese
- Department of Biomedical Engineering, The Ohio State University, Columbus, OH, USA
| | - Krishna S Nayak
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
- Alfred Mann Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
| | - Rajiv Ramasawmy
- Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda MD USA
| | - Orlando P Simonetti
- Division of Cardiovascular Medicine, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH, USA
- Department of Radiology, The Ohio State University, Columbus, Ohio, USA
| |
Collapse
|
5
|
Chen X, Li J, Chen D, Zhou Y, Tu Z, Lin M, Kang T, Lin J, Gong T, Zhu L, Zhou J, Lin OY, Guo J, Dong J, Guo D, Qu X. CloudBrain-MRS: An intelligent cloud computing platform for in vivo magnetic resonance spectroscopy preprocessing, quantification, and analysis. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2024; 358:107601. [PMID: 38039654 DOI: 10.1016/j.jmr.2023.107601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 11/26/2023] [Accepted: 11/27/2023] [Indexed: 12/03/2023]
Abstract
Magnetic resonance spectroscopy (MRS) is an important clinical imaging method for diagnosis of diseases. MRS spectrum is used to observe the signal intensity of metabolites or further infer their concentrations. Although the magnetic resonance vendors commonly provide basic functions of spectrum plots and metabolite quantification, the spread of clinical research of MRS is still limited due to the lack of easy-to-use processing software or platform. To address this issue, we have developed CloudBrain-MRS, a cloud-based online platform that provides powerful hardware and advanced algorithms. The platform can be accessed simply through a web browser, without the need of any program installation on the user side. CloudBrain-MRS also integrates the classic LCModel and advanced artificial intelligence algorithms and supports batch preprocessing, quantification, and analysis of MRS data from different vendors. Additionally, the platform offers useful functions: (1) Automatically statistical analysis to find biomarkers for diseases; (2) Consistency verification between the classic and artificial intelligence quantification algorithms; (3) Colorful three-dimensional visualization for easy observation of individual metabolite spectrum. Last, data of both healthy subjects and patients with mild cognitive impairment are used to demonstrate the functions of the platform. To the best of our knowledge, this is the first cloud computing platform for in vivo MRS with artificial intelligence processing. We have shared our cloud platform at MRSHub, providing at least two years of free access and service. If you are interested, please visit https://mrshub.org/software_all/#CloudBrain-MRS or https://csrc.xmu.edu.cn/CloudBrain.html.
Collapse
Affiliation(s)
- Xiaodie Chen
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Jiayu Li
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Dicheng Chen
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Yirong Zhou
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Zhangren Tu
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Meijin Lin
- Department of Applied Marine Physics & Engineering, Xiamen University, Xiamen, China
| | - Taishan Kang
- Department of Radiology, Zhongshan Hospital Affiliated to Xiamen University, Xiamen, China
| | - Jianzhong Lin
- Department of Radiology, Zhongshan Hospital Affiliated to Xiamen University, Xiamen, China
| | - Tao Gong
- Departments of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Liuhong Zhu
- Department of Radiology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China
| | - Jianjun Zhou
- Department of Radiology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China
| | - Ou-Yang Lin
- Department of Medical Imaging of Southeast Hospital, Medical College of Xiamen University, Xiamen, China
| | - Jiefeng Guo
- Department of Microelectronics and Integrated Circuit, Xiamen University, Xiamen, China
| | - Jiyang Dong
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Di Guo
- School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China
| | - Xiaobo Qu
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China.
| |
Collapse
|
6
|
Webber M, Joy G, Bennett J, Chan F, Falconer D, Shiwani H, Davies RH, Krausz G, Tanackovic S, Guger C, Gonzalez P, Martin E, Wong A, Rapala A, Direk K, Kellman P, Pierce I, Rudy Y, Vijayakumar R, Chaturvedi N, Hughes AD, Moon JC, Lambiase PD, Tao X, Koncar V, Orini M, Captur G. Technical development and feasibility of a reusable vest to integrate cardiovascular magnetic resonance with electrocardiographic imaging. J Cardiovasc Magn Reson 2023; 25:73. [PMID: 38044439 PMCID: PMC10694972 DOI: 10.1186/s12968-023-00980-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 11/12/2023] [Indexed: 12/05/2023] Open
Abstract
BACKGROUND Electrocardiographic imaging (ECGI) generates electrophysiological (EP) biomarkers while cardiovascular magnetic resonance (CMR) imaging provides data about myocardial structure, function and tissue substrate. Combining this information in one examination is desirable but requires an affordable, reusable, and high-throughput solution. We therefore developed the CMR-ECGI vest and carried out this technical development study to assess its feasibility and repeatability in vivo. METHODS CMR was prospectively performed at 3T on participants after collecting surface potentials using the locally designed and fabricated 256-lead ECGI vest. Epicardial maps were reconstructed to generate local EP parameters such as activation time (AT), repolarization time (RT) and activation recovery intervals (ARI). 20 intra- and inter-observer and 8 scan re-scan repeatability tests. RESULTS 77 participants were recruited: 27 young healthy volunteers (HV, 38.9 ± 8.5 years, 35% male) and 50 older persons (77.0 ± 0.1 years, 52% male). CMR-ECGI was achieved in all participants using the same reusable, washable vest without complications. Intra- and inter-observer variability was low (correlation coefficients [rs] across unipolar electrograms = 0.99 and 0.98 respectively) and scan re-scan repeatability was high (rs between 0.81 and 0.93). Compared to young HV, older persons had significantly longer RT (296.8 vs 289.3 ms, p = 0.002), ARI (249.8 vs 235.1 ms, p = 0.002) and local gradients of AT, RT and ARI (0.40 vs 0.34 ms/mm, p = 0,01; 0.92 vs 0.77 ms/mm, p = 0.03; and 1.12 vs 0.92 ms/mm, p = 0.01 respectively). CONCLUSION Our high-throughput CMR-ECGI solution is feasible and shows good reproducibility in younger and older participants. This new technology is now scalable for high throughput research to provide novel insights into arrhythmogenesis and potentially pave the way for more personalised risk stratification. CLINICAL TRIAL REGISTRATION Title: Multimorbidity Life-Course Approach to Myocardial Health-A Cardiac Sub-Study of the MRC National Survey of Health and Development (NSHD) (MyoFit46). National Clinical Trials (NCT) number: NCT05455125. URL: https://clinicaltrials.gov/ct2/show/NCT05455125?term=MyoFit&draw=2&rank=1.
Collapse
Affiliation(s)
- Matthew Webber
- Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, ECIA 7BE, UK
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
- Centre for Inherited Heart Muscle Conditions, Department of Cardiology, Royal Free London NHS Foundation Trust, Pond Street, London, NW3 2QG, UK
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - George Joy
- Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, ECIA 7BE, UK
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
| | - Jonathan Bennett
- Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, ECIA 7BE, UK
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
| | - Fiona Chan
- Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, ECIA 7BE, UK
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
| | - Debbie Falconer
- Centre for Inherited Heart Muscle Conditions, Department of Cardiology, Royal Free London NHS Foundation Trust, Pond Street, London, NW3 2QG, UK
| | - Hunain Shiwani
- Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, ECIA 7BE, UK
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
| | - Rhodri H Davies
- Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, ECIA 7BE, UK
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
| | - Gunther Krausz
- g.Tec Medical Engineering GmbH, Siernigtrabe 14, 4521, Schiedlberg, Austria
| | | | - Christoph Guger
- g.Tec Medical Engineering GmbH, Siernigtrabe 14, 4521, Schiedlberg, Austria
| | - Pablo Gonzalez
- ELEM Biotech, S.L, Barcelona, Spain
- Department of Computer Applications in Science and Engineering, Barcelona Supercomputing Center (BSC), 08034, Barcelona, Spain
- Department of Information and Communication Technologies, Physense, Universitat Pempeu Fabra, Barcrlona, Spain
| | - Emma Martin
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Andrew Wong
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Alicja Rapala
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Kenan Direk
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Peter Kellman
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Iain Pierce
- Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, ECIA 7BE, UK
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Yoram Rudy
- Cardiac Bioelectricity and Arrhythmia Center, Washington University, St. Louis, MO, 63130, USA
- Department of Biomedical Engineering, Washington University, St. Louis, MO, 63130, USA
| | - Ramya Vijayakumar
- Cardiac Bioelectricity and Arrhythmia Center, Washington University, St. Louis, MO, 63130, USA
- Department of Biomedical Engineering, Washington University, St. Louis, MO, 63130, USA
| | - Nishi Chaturvedi
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Alun D Hughes
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - James C Moon
- Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, ECIA 7BE, UK
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
| | - Pier D Lambiase
- Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, ECIA 7BE, UK
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
| | - Xuyuan Tao
- École Nationale Supérieure des Arts et Industries Textiles, 2 allée Louise et Victor Champier, 59056, Roubaix CEDEX 1, France
| | - Vladan Koncar
- École Nationale Supérieure des Arts et Industries Textiles, 2 allée Louise et Victor Champier, 59056, Roubaix CEDEX 1, France
| | - Michele Orini
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Gabriella Captur
- Institute of Cardiovascular Science, University College London, Huntley Street, London, WC1E 6DD, UK.
- Centre for Inherited Heart Muscle Conditions, Department of Cardiology, Royal Free London NHS Foundation Trust, Pond Street, London, NW3 2QG, UK.
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK.
| |
Collapse
|
7
|
Hooper SM, Wu S, Davies RH, Bhuva A, Schelbert EB, Moon JC, Kellman P, Xue H, Langlotz C, Ré C. Evaluating semi-supervision methods for medical image segmentation: applications in cardiac magnetic resonance imaging. J Med Imaging (Bellingham) 2023; 10:024007. [PMID: 37009059 PMCID: PMC10061343 DOI: 10.1117/1.jmi.10.2.024007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 02/27/2023] [Indexed: 03/31/2023] Open
Abstract
Purpose Neural networks have potential to automate medical image segmentation but require expensive labeling efforts. While methods have been proposed to reduce the labeling burden, most have not been thoroughly evaluated on large, clinical datasets or clinical tasks. We propose a method to train segmentation networks with limited labeled data and focus on thorough network evaluation. Approach We propose a semi-supervised method that leverages data augmentation, consistency regularization, and pseudolabeling and train four cardiac magnetic resonance (MR) segmentation networks. We evaluate the models on multiinstitutional, multiscanner, multidisease cardiac MR datasets using five cardiac functional biomarkers, which are compared to an expert's measurements using Lin's concordance correlation coefficient (CCC), the within-subject coefficient of variation (CV), and the Dice coefficient. Results The semi-supervised networks achieve strong agreement using Lin's CCC ( > 0.8 ), CV similar to an expert, and strong generalization performance. We compare the error modes of the semi-supervised networks against fully supervised networks. We evaluate semi-supervised model performance as a function of labeled training data and with different types of model supervision, showing that a model trained with 100 labeled image slices can achieve a Dice coefficient within 1.10% of a network trained with 16,000+ labeled image slices. Conclusion We evaluate semi-supervision for medical image segmentation using heterogeneous datasets and clinical metrics. As methods for training models with little labeled data become more common, knowledge about how they perform on clinical tasks, how they fail, and how they perform with different amounts of labeled data is useful to model developers and users.
Collapse
Affiliation(s)
- Sarah M. Hooper
- Stanford University, Department of Electrical Engineering, Stanford, California, United States
| | - Sen Wu
- Stanford University, Department of Computer Science, Stanford, California, United States
| | - Rhodri H. Davies
- Barts Health NHS Trust, Barts Heart Centre, London, United Kingdom
- University of College London, Institute of Cardiovascular Sciences, London, United Kingdom
- University of College London, MRC Centre for Lifelong Health and Ageing, London, United Kingdom
| | - Anish Bhuva
- Barts Health NHS Trust, Barts Heart Centre, London, United Kingdom
- University of College London, Institute of Cardiovascular Sciences, London, United Kingdom
| | - Erik B. Schelbert
- United Hospital, St. Paul, Minnesota, and Abbott Northwestern Hospital, Minneapolis Heart Institute, Minneapolis, Minnesota, United States
- UPMC Cardiovascular Magnetic Resonance Center, UPMC, Pittsburgh, Pennsylvania, United States
- University of Pittsburgh School of Medicine, Department of Medicine, Pittsburgh, Pennsylvania, United States
| | - James C. Moon
- Barts Health NHS Trust, Barts Heart Centre, London, United Kingdom
- University of College London, Institute of Cardiovascular Sciences, London, United Kingdom
| | - Peter Kellman
- National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, United States
| | - Hui Xue
- National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, United States
| | - Curtis Langlotz
- Stanford University, Department of Radiology, Department of Biomedical Informatics, Stanford, California, United States
| | - Christopher Ré
- Stanford University, Department of Computer Science, Stanford, California, United States
| |
Collapse
|
8
|
Eck BL, Yim M, Hamilton JI, da Cruz GJL, Li X, Flamm SD, Tang WHW, Prieto C, Seiberlich N, Kwon DH. Cardiac Magnetic Resonance Fingerprinting: Potential Clinical Applications. Curr Cardiol Rep 2023; 25:119-131. [PMID: 36805913 PMCID: PMC10134477 DOI: 10.1007/s11886-022-01836-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/10/2022] [Indexed: 02/21/2023]
Abstract
PURPOSE OF REVIEW Cardiac magnetic resonance fingerprinting (cMRF) has developed as a technique for rapid, multi-parametric tissue property mapping that has potential to both improve cardiac MRI exam efficiency and expand the information captured. In this review, we describe the cMRF technique, summarize technical developments and in vivo reports, and highlight potential clinical applications. RECENT FINDINGS Technical developments in cMRF continue to progress rapidly, including motion compensated reconstruction, additional tissue property quantification, signal time course analysis, and synthetic LGE image generation. Such technical developments can enable simplified CMR protocols by combining multiple evaluations into a single protocol and reducing the number of breath-held scans. cMRF continues to be reported for use in a range of pathologies; however barriers to clinical implementation remain. Technical developments are described in this review, followed by a focus on potential clinical applications that they may support. Clinical translation of cMRF could shorten protocols, improve CMR accessibility, and provide additional information as compared to conventional cardiac parametric mapping methods. Current needs for clinical implementation are discussed, as well as how those needs may be met in order to bring cMRF from its current research setting to become a viable tool for patient care.
Collapse
Affiliation(s)
- Brendan L Eck
- Imaging Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Michael Yim
- Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Jesse I Hamilton
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Gastao José Lima da Cruz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, England, UK
| | - Xiaojuan Li
- Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Scott D Flamm
- Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, OH, USA
- Imaging Institute, Cleveland Clinic, Cleveland, OH, USA
| | - W H Wilson Tang
- Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, England, UK
- School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Nicole Seiberlich
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Deborah H Kwon
- Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, OH, USA.
- Imaging Institute, Cleveland Clinic, Cleveland, OH, USA.
| |
Collapse
|
9
|
Inam O, Qureshi M, Laraib Z, Akram H, Omer H. GPU accelerated Cartesian GRAPPA reconstruction using CUDA. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2022; 337:107175. [PMID: 35259611 DOI: 10.1016/j.jmr.2022.107175] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 02/10/2022] [Accepted: 02/21/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND AND OBJECTIVE GRAPPA (Generalized Auto-calibrating Partially Parallel Acquisition) is an advanced parallel MRI reconstruction method (pMRI) that enables under-sampled data acquisition with multiple receiver coils to reduce the MRI scan time and reconstructs artifact free image from the acquired under-sampled data. However, the reduction in MRI scan time comes at the expense of long reconstruction time. It is because the GRAPPA reconstruction time shows exponential growth with increasing number of receiver coils. Consequently, the conventional CPU platforms may not adhere to the requirements of fast data processing for MR image reconstruction. METHODS Graphics Processing Units (GPUs) have recently emerged as a viable commodity hardware to reduce the reconstruction time of pMRI methods. This paper presents a novel GPU based implementation of GRAPPA using custom built CUDA kernels, to meet the rising demands of fast MRI processing. The proposed framework exploits intrinsic parallelism in the calibration and synthesis phases of GRAPPA reconstruction process, aiming to achieve high speed MR image reconstruction for various GRAPPA configuration settings using different number of receiver coils, auto-calibration signals (ACS), sizes of GRAPPA kernel and acceleration factors. In-vivo experiments (using 8, 12 and 30 receiver coils) are performed to compare the performance of the proposed GPU accelerated GRAPPA with the CPU based GRAPPA extensions and GPU counterpart. RESULTS The results indicate that the proposed method achieves up to ≈47.8× , ≈17× and ≈3.8× speed up gains over multicore CPU (single thread), multicore CPU (8 thread) and Gadgetron (GPU based GRAPPA) respectively, without compromising the reconstruction accuracy. CONCLUSIONS The proposed method reduces the GRAPPA reconstruction time by employing the calibration phase (GRAPPA weights estimation) and synthesis phase (interpolation) on GPU. Our study shows that the proposed GPU based parallel framework for GRAPPA reconstruction provides a solution for high-speed image reconstruction while maintaining the quality of the reconstructed images.
Collapse
Affiliation(s)
- Omair Inam
- Medical Image Processing Research Group (MIPRG), Department of Electrical & Computer Engineering, COMSATS University Islamabad, Pakistan.
| | - Mahmood Qureshi
- Medical Image Processing Research Group (MIPRG), Department of Electrical & Computer Engineering, COMSATS University Islamabad, Pakistan.
| | - Zoia Laraib
- Medical Image Processing Research Group (MIPRG), Department of Electrical & Computer Engineering, COMSATS University Islamabad, Pakistan
| | - Hamza Akram
- Medical Image Processing Research Group (MIPRG), Department of Electrical & Computer Engineering, COMSATS University Islamabad, Pakistan
| | - Hammad Omer
- Medical Image Processing Research Group (MIPRG), Department of Electrical & Computer Engineering, COMSATS University Islamabad, Pakistan.
| |
Collapse
|
10
|
Feasibility of Magnetic Resonance Fingerprinting on Aging MRI Hardware. Tomography 2021; 8:10-21. [PMID: 35076600 PMCID: PMC8788417 DOI: 10.3390/tomography8010002] [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: 11/18/2021] [Revised: 12/15/2021] [Accepted: 12/17/2021] [Indexed: 11/17/2022] Open
Abstract
The purpose of this work is to evaluate the feasibility of performing magnetic resonance fingerprinting (MRF) on older and lower-performance MRI hardware as a means to bring advanced imaging to the aging MRI install base. Phantom and in vivo experiments were performed on a 1.5T Siemens Aera (installed 2015) and 1.5T Siemens Symphony (installed 2002). A 2D spiral MRF sequence for simultaneous T1/T2/M0 mapping was implemented on both scanners with different gradient trajectories to accommodate system specifications. In phantom, for T1/T2 values in a physiologically relevant range (T1: 195-1539 ms; T2: 20-267 ms), scanners had strong correlation (R2 > 0.999) with average absolute percent difference of 8.1% and 10.1%, respectively. Comparison of the two trajectories on the newer scanner showed differences of 2.6% (T1) and 10.9% (T2), suggesting a partial explanation of the observed inter-scanner bias. Inter-scanner agreement was better when the same trajectory was used, with differences of 6.0% (T1) and 4.0% (T2). Intra-scanner coefficient of variation (CV) of T1 and T2 estimates in phantom were <2.0% and in vivo were ≤3.5%. In vivo inter-scanner white matter CV was 4.8% (T1) and 5.1% (T2). White matter measurements on the aging scanner after two months were consistent, with differences of 1.9% (T1) and 3.9% (T2). In conclusion, MRF is feasible on an aging MRI scanner and required only changes to the gradient trajectory.
Collapse
|
11
|
Kumar PA, Gunasundari R, Aarthi R. Systematic Analysis and Review of Magnetic Resonance Imaging (MRI) Reconstruction Techniques. Curr Med Imaging 2021; 17:943-955. [PMID: 33402090 DOI: 10.2174/1573405616666210105125542] [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: 05/18/2020] [Revised: 10/24/2020] [Accepted: 11/12/2020] [Indexed: 11/22/2022]
Abstract
BACKGROUND Magnetic Resonance Imaging (MRI) plays an important role in the field of medical diagnostic imaging as it poses non-invasive acquisition and high soft-tissue contrast. However, a huge time is needed for the MRI scanning process that results in motion artifacts, degrades image quality, misinterprets the data, and may cause discomfort to the patient. Thus, the main goal of MRI research is to accelerate data acquisition processing without affecting the quality of the image. INTRODUCTION This paper presents a survey based on distinct conventional MRI reconstruction methodologies. In addition, a novel MRI reconstruction strategy is proposed based on weighted Compressive Sensing (CS), Penalty-aided minimization function, and Meta-heuristic optimization technique. METHODS An illustrative analysis is done concerning adapted methods, datasets used, execution tools, performance measures, and values of evaluation metrics. Moreover, the issues of existing methods and the research gaps considering conventional MRI reconstruction schemes are elaborated to obtain improved contribution for devising significant MRI reconstruction techniques. RESULTS The proposed method will reduce conventional aliasing artifact problems, may attain lower Mean Square Error (MSE), higher Peak Signal-to-Noise Ratio (PSNR), and Structural SIMilarity (SSIM) index. CONCLUSION The issues of existing methods and the research gaps considering conventional MRI reconstruction schemes are elaborated to devising an improved significant MRI reconstruction technique.
Collapse
Affiliation(s)
- Penta Anil Kumar
- Department of Electronics and Communication Engineering, Pondicherry Engineering College, Puducherry, India
| | - Ramalingam Gunasundari
- Department of Electronics and Communication Engineering, Pondicherry Engineering College, Puducherry, India
| | | |
Collapse
|
12
|
Hughes RK, Camaioni C, Augusto JB, Knott K, Quinn E, Captur G, Seraphim A, Joy G, Syrris P, Elliott PM, Mohiddin S, Kellman P, Xue H, Lopes LR, Moon JC. Myocardial Perfusion Defects in Hypertrophic Cardiomyopathy Mutation Carriers. J Am Heart Assoc 2021; 10:e020227. [PMID: 34310159 PMCID: PMC8475659 DOI: 10.1161/jaha.120.020227] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Background Impaired myocardial blood flow (MBF) in the absence of epicardial coronary disease is a feature of hypertrophic cardiomyopathy (HCM). Although most evident in hypertrophied or scarred segments, reduced MBF can occur in apparently normal segments. We hypothesized that impaired MBF and myocardial perfusion reserve, quantified using perfusion mapping cardiac magnetic resonance, might occur in the absence of overt left ventricular hypertrophy (LVH) and late gadolinium enhancement, in mutation carriers without LVH criteria for HCM (genotype‐positive, left ventricular hypertrophy‐negative). Methods and Results A single center, case‐control study investigated MBF and myocardial perfusion reserve (the ratio of MBF at stress:rest), along with other pre‐phenotypic features of HCM. Individuals with genotype‐positive, left ventricular hypertrophy‐negative (n=50) with likely pathogenic/pathogenic variants and no evidence of LVH, and matched controls (n=28) underwent cardiac magnetic resonance. Cardiac magnetic resonance identified LVH‐fulfilling criteria for HCM in 5 patients who were excluded. Individuals with genotype‐positive, left ventricular hypertrophy‐negative had longer indexed anterior mitral valve leaflet length (12.52±2.1 versus 11.55±1.6 mm/m2, P=0.03), lower left ventricular end‐systolic volume (21.0±6.9 versus 26.7±6.2 mm/m2, P≤0.005) and higher left ventricular ejection fraction (71.9±5.5 versus 65.8±4.4%, P≤0.005). Maximum wall thickness was not significantly different (9.03±1.95 versus 8.37±1.2 mm, P=0.075), and no subject had significant late gadolinium enhancement (minor right ventricle‒insertion point late gadolinium enhancement only). Perfusion mapping demonstrated visual perfusion defects in 9 (20%) carriers versus 0 controls (P=0.011). These were almost all septal or near right ventricle insertion points. Globally, myocardial perfusion reserve was lower in carriers (2.77±0.83 versus 3.24±0.63, P=0.009), with a subendocardial:subepicardial myocardial perfusion reserve gradient (2.55±0.75 versus 3.2±0.65, P=<0.005; 3.01±0.96 versus 3.47±0.75, P=0.026) but equivalent MBF (2.75±0.82 versus 2.65±0.69 mL/g per min, P=0.826). Conclusions Regional and global impaired myocardial perfusion can occur in HCM mutation carriers, in the absence of significant hypertrophy or scarring.
Collapse
Affiliation(s)
- Rebecca K Hughes
- Institute of Cardiovascular ScienceUniversity College London London UK.,Barts Heart CentreThe Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases UnitSt Bartholomew's Hospital London UK
| | - Claudia Camaioni
- Barts Heart CentreThe Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases UnitSt Bartholomew's Hospital London UK
| | - João B Augusto
- Institute of Cardiovascular ScienceUniversity College London London UK.,Barts Heart CentreThe Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases UnitSt Bartholomew's Hospital London UK
| | - Kristopher Knott
- Institute of Cardiovascular ScienceUniversity College London London UK.,Barts Heart CentreThe Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases UnitSt Bartholomew's Hospital London UK
| | - Ellie Quinn
- Barts Heart CentreThe Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases UnitSt Bartholomew's Hospital London UK
| | - Gabriella Captur
- Institute of Cardiovascular ScienceUniversity College London London UK.,Department of Cardiology Inherited Heart Muscle Conditions ClinicRoyal Free HospitalNHS Trust London UK.,University College London MRC Unit of Lifelong Health and Ageing London UK
| | - Andreas Seraphim
- Institute of Cardiovascular ScienceUniversity College London London UK.,Barts Heart CentreThe Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases UnitSt Bartholomew's Hospital London UK
| | - George Joy
- Barts Heart CentreThe Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases UnitSt Bartholomew's Hospital London UK
| | - Petros Syrris
- Institute of Cardiovascular ScienceUniversity College London London UK
| | - Perry M Elliott
- Institute of Cardiovascular ScienceUniversity College London London UK.,Barts Heart CentreThe Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases UnitSt Bartholomew's Hospital London UK
| | - Saidi Mohiddin
- Barts Heart CentreThe Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases UnitSt Bartholomew's Hospital London UK.,William Harvey instituteQueen Mary University of London London UK
| | - Peter Kellman
- National Heart, Lung, and Blood InstituteNational Institutes of HealthDHHS Bethesda MD
| | - Hui Xue
- National Heart, Lung, and Blood InstituteNational Institutes of HealthDHHS Bethesda MD
| | - Luis R Lopes
- Institute of Cardiovascular ScienceUniversity College London London UK.,Barts Heart CentreThe Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases UnitSt Bartholomew's Hospital London UK
| | - James C Moon
- Institute of Cardiovascular ScienceUniversity College London London UK.,Barts Heart CentreThe Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases UnitSt Bartholomew's Hospital London UK
| |
Collapse
|
13
|
Abstract
Clinical MRI systems have continually improved over the years since their introduction in the 1980s. In MRI technical development, the developments in each MRI system component, including data acquisition, image reconstruction, and hardware systems, have impacted the others. Progress in each component has induced new technology development opportunities in other components. New technologies outside of the MRI field, for example, computer science, data processing, and semiconductors, have been immediately incorporated into MRI development, which resulted in innovative applications. With high performance computing and MR technology innovations, MRI can now provide large volumes of functional and anatomical image datasets, which are important tools in various research fields. MRI systems are now combined with other modalities, such as positron emission tomography (PET) or therapeutic devices. These hybrid systems provide additional capabilities. In this review, MRI advances in the last two decades will be considered. We will discuss the progress of MRI systems, the enabling technology, established applications, current trends, and the future outlook.
Collapse
Affiliation(s)
- Hiroyuki Kabasawa
- Department of Radiological Sciences, School of Health Sciences at Narita, International University of Health and Welfare
| |
Collapse
|
14
|
Zhang Y, She H, Du YP. Dynamic MRI of the abdomen using parallel non-Cartesian convolutional recurrent neural networks. Magn Reson Med 2021; 86:964-973. [PMID: 33749023 DOI: 10.1002/mrm.28774] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Revised: 02/25/2021] [Accepted: 02/25/2021] [Indexed: 11/10/2022]
Abstract
PURPOSE To improve the image quality and reduce computational time for the reconstruction of undersampled non-Cartesian abdominal dynamic parallel MR data using the deep learning approach. METHODS An algorithm of parallel non-Cartesian convolutional recurrent neural networks (PNCRNNs) was developed to enable the use of the redundant information in both spatial and temporal domains, and achieve data fidelity for the reconstruction of non-Cartesian parallel MR data. The performance of PNCRNNs was evaluated for various acceleration rates, motion patterns, and imaging applications in comparison with that of the state-of-the-art algorithms of dynamic imaging, including extra-dimensional golden-angle radial sparse parallel MRI (XD-GRASP), low-rank plus sparse matrix decomposition (L+S), blind compressive sensing (BCS), and 3D convolutional neural networks (3D CNNs). RESULTS PNCRNNs increased the peak SNR of 9.07 dB compared with XD-GRASP, 9.26 dB compared with L+S, 3.48 dB compared with BCS, and 3.14 dB compared with 3D CNN at R = 16. The reconstruction time was 18 ms for each bin, which was two orders faster than that of XD-GRASP, L+S, and BCS. PNCRNNs provided good reconstruction for various motion patterns, k-space trajectories, and imaging applications. CONCLUSION The proposed PNCRNN provides substantial improvement of the image quality for dynamic golden-angle radial imaging of the abdomen in comparison with XD-GRASP, L+S, BCS, and 3D CNN. The reconstruction time of PNCRNN can be as fast as 50 bins per second, due to the use of the highly computational efficient Toeplitz approach.
Collapse
Affiliation(s)
- Yufei Zhang
- Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Huajun She
- Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yiping P Du
- Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| |
Collapse
|
15
|
Motion-corrected cardiac MRI is associated with decreased anesthesia exposure in children. Pediatr Radiol 2020; 50:1709-1716. [PMID: 32696111 PMCID: PMC8351617 DOI: 10.1007/s00247-020-04766-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 05/20/2020] [Accepted: 07/01/2020] [Indexed: 12/21/2022]
Abstract
BACKGROUND The benefits of cardiac magnetic resonance imaging (MRI) in the pediatric population must be balanced with the risk and cost of anesthesia. Segmented imaging using multiple averages attempts to avoid breath-holds requiring general anesthesia; however, cardiorespiratory artifacts and prolonged scan times limit its use. Thus, breath-held imaging with general anesthesia is used in many pediatric centers. The advent of free-breathing, motion-corrected (MOCO) cines by real-time re-binned reconstruction offers reduced anesthesia exposure without compromising image quality. OBJECTIVE This study evaluates sedation utilization in our pediatric cardiac MR practice before and after clinical introduction of free-breathing MOCO imaging for cine and late gadolinium enhancement. MATERIALS AND METHODS In a retrospective study, patients referred for a clinical cardiac MR who would typically be offered sedation for their scan (n=295) were identified and divided into two eras, those scanned before the introduction of MOCO cine and late gadolinium enhancement sequences and those scanned following their introduction. Anesthesia use was compared across eras and disease-specific cohorts. RESULTS The incidence of non-sedation studies performed in children nearly tripled following the introduction of MOCO imaging (25% [pre-MOCO] to 69% [post-MOCO], P<0.01), with the greatest effect in patients with simple congenital heart disease. Eleven percent of the post-MOCO cohort comprised infants younger than 3 months of age who could forgo sedation with the combination of MOCO imaging and a "feed-and-bundle" positioning technique. CONCLUSION Implementation of cardiac MR with MOCO cine and late gadolinium enhancement imaging in a pediatric population is associated with significantly decreased sedation utilization.
Collapse
|
16
|
Bandettini WP, Shanbhag SM, Mancini C, McGuirt DR, Kellman P, Xue H, Henry JL, Lowery M, Thein SL, Chen MY, Campbell-Washburn AE. A comparison of cine CMR imaging at 0.55 T and 1.5 T. J Cardiovasc Magn Reson 2020; 22:37. [PMID: 32423456 PMCID: PMC7232838 DOI: 10.1186/s12968-020-00618-y] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2019] [Accepted: 03/20/2020] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND There is a renewed interest in lower field magnetic resonance imaging (MRI) systems for cardiovascular magnetic resonance (CMR), due to their favorable physical properties, reduced costs, and increased accessibility to patients with implants. We sought to assess the diagnostic capabilities of high-performance low-field (0.55 T) CMR imaging for quantification of right and left ventricular volumes and systolic function in both healthy subjects and patients referred for clinical CMR. METHODS Sixty-five subjects underwent paired exams at 1.5 T using a clinical CMR scanner and using an identical CMR system modified to operate at 0.55 T. Volumetric coverage of the right ventricle (RV) and left ventricles (LV) was obtained using either a breath-held cine balanced steady-state free-precession acquisition or a motion-corrected free-breathing re-binned cine acquisition. Bland-Altman analysis was used to compare LV and RV end-systolic volume (ESV), end-diastolic volume (EDV), ejection fraction (EF), and LV mass. Diagnostic confidence was scored on a Likert-type ordinal scale by blinded readers. RESULTS There were no significant differences in LV and RV EDV between the two scanners (e.g., LVEDV: p = 0.77, bias = 0.40 mL, correlation coefficient = 0.99; RVEDV: p = 0.17, bias = - 1.6 mL, correlation coefficient = 0.98), and regional wall motion abnormality scoring was similar (kappa 0.99). Blood-myocardium contrast-to-noise ratio (CNR) at 0.55 T was 48 ± 7% of the 1.5 T CNR, and contrast was sufficient for endocardial segmentation in all cases. Diagnostic confidence of images was scored as "good" to "excellent" for the two field strengths in the majority of studies. CONCLUSION A high-performance 0.55 T system offers good bSSFP CMR image quality, and quantification of biventricular volumes and systolic function that is comparable to 1.5 T in patients. TRIAL REGISTRATION Clinicaltrials.gov NCT03331380, NCT03581318.
Collapse
Affiliation(s)
- W Patricia Bandettini
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Department of Health and Human Services, Building 10, Room BID-47, 10 Center Dr, Bethesda, MD, 20892, USA
| | - Sujata M Shanbhag
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Department of Health and Human Services, Building 10, Room BID-47, 10 Center Dr, Bethesda, MD, 20892, USA
| | - Christine Mancini
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Department of Health and Human Services, Building 10, Room BID-47, 10 Center Dr, Bethesda, MD, 20892, USA
| | - Delaney R McGuirt
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Department of Health and Human Services, Building 10, Room BID-47, 10 Center Dr, Bethesda, MD, 20892, USA
| | - Peter Kellman
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Department of Health and Human Services, Building 10, Room BID-47, 10 Center Dr, Bethesda, MD, 20892, USA
| | - Hui Xue
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Department of Health and Human Services, Building 10, Room BID-47, 10 Center Dr, Bethesda, MD, 20892, USA
| | - Jennifer L Henry
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Department of Health and Human Services, Building 10, Room BID-47, 10 Center Dr, Bethesda, MD, 20892, USA
| | - Margaret Lowery
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Department of Health and Human Services, Building 10, Room BID-47, 10 Center Dr, Bethesda, MD, 20892, USA
| | - Swee Lay Thein
- Sickle Cell Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Department of Health and Human Services, Bethesda, MD, USA
| | - Marcus Y Chen
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Department of Health and Human Services, Building 10, Room BID-47, 10 Center Dr, Bethesda, MD, 20892, USA
| | - Adrienne E Campbell-Washburn
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Department of Health and Human Services, Building 10, Room BID-47, 10 Center Dr, Bethesda, MD, 20892, USA.
| |
Collapse
|
17
|
Xue H, Tseng E, Knott KD, Kotecha T, Brown L, Plein S, Fontana M, Moon JC, Kellman P. Automated detection of left ventricle in arterial input function images for inline perfusion mapping using deep learning: A study of 15,000 patients. Magn Reson Med 2020; 84:2788-2800. [DOI: 10.1002/mrm.28291] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2019] [Revised: 03/30/2020] [Accepted: 03/30/2020] [Indexed: 12/21/2022]
Affiliation(s)
- Hui Xue
- National Heart, Lung and Blood Institute National Institutes of Health Bethesda Maryland USA
| | - Ethan Tseng
- National Heart, Lung and Blood Institute National Institutes of Health Bethesda Maryland USA
| | | | - Tushar Kotecha
- National Amyloidosis Centre Royal Free Hospital London UK
| | - Louise Brown
- Department of Biomedical Imaging Science Leeds Institute of Cardiovascular and Metabolic Medicine University of Leeds Leeds UK
| | - Sven Plein
- Department of Biomedical Imaging Science Leeds Institute of Cardiovascular and Metabolic Medicine University of Leeds Leeds UK
| | | | | | - Peter Kellman
- National Heart, Lung and Blood Institute National Institutes of Health Bethesda Maryland USA
| |
Collapse
|
18
|
Olivieri LJ, Jiang J, Hamann K, Loke YH, Campbell-Washburn A, Xue H, McCarter R, Cross R. Normal right and left ventricular volumes prospectively obtained from cardiovascular magnetic resonance in awake, healthy, 0- 12 year old children. J Cardiovasc Magn Reson 2020; 22:11. [PMID: 32013998 PMCID: PMC6998283 DOI: 10.1186/s12968-020-0602-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Accepted: 01/13/2020] [Indexed: 01/15/2023] Open
Abstract
INTRODUCTION Pediatric z scores are necessary to describe size and structure of the heart in growing children, however, development of an accurate z score calculator requires robust normal datasets, which are difficult to obtain with cardiovascular magnetic resonance (CMR) in children. Motion-corrected (MOCO) cines from re-binned, reconstructed real-time cine offer a free-breathing, rapid acquisition resulting in cines with high spatial and temporal resolution. In combination with child-friendly positioning and entertainment, MOCO cine technique allows for rapid cine volumetry in patients of all ages without sedation. Thus, our aim was to prospectively enroll normal infants and children birth-12 years for creation and validation of a z score calculator describing normal right ventricular (RV) and left ventricular (LV) size. METHODS With IRB approval and consent/assent, 149 normal children successfully underwent a brief noncontrast CMR on a 1.5 T scanner including MOCO cines in the short axis, and RV and LV volumes were measured. 20% of scans were re-measured for interobserver variability analyses. A general linear modeling (GLM) framework was employed to identify and properly represent the relationship between CMR-based assessments and anthropometric data. Scatter plots of model fit and Akaike's information criteria (AIC) results were used to guide the choice among alternative models. RESULTS A total of 149 subjects aged 22 days-12 years (average 5.1 ± 3.6 years), with body surface area (BSA) range 0.21-1.63 m2 (average 0.8 ± 0.35 m2) were scanned. All ICC values were > 95%, reflecting excellent agreement between raters. The model that provided the best fit of volume measure to the data included BSA with higher order effects and gender as independent variables. Compared with earlier z score models, there is important additional growth inflection in early toddlerhood with similar z score prediction in later childhood. CONCLUSIONS Free-breathing, MOCO cines allow for accurate, reliable RV and LV volumetry in a wide range of infants and children while awake. Equations predicting fit between LV and RV normal values and BSA are reported herein for purposes of creating z scores. TRIAL REGISTRATION clinicaltrials.gov NCT02892136, Registered 7/21/2016.
Collapse
Affiliation(s)
- Laura J Olivieri
- Division of Cardiology, Children's National Medical Center, W3-200, 111 Michigan Ave NW, Washington, DC, 20010, USA.
| | - Jiji Jiang
- Children's Research Institute, Children's National Medical Center, 111 Michigan Ave NW, Washington, DC, USA
| | - Karin Hamann
- Division of Cardiology, Children's National Medical Center, W3-200, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Yue-Hin Loke
- Division of Cardiology, Children's National Medical Center, W3-200, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | | | - Hui Xue
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Robert McCarter
- Children's Research Institute, Children's National Medical Center, 111 Michigan Ave NW, Washington, DC, USA
| | - Russell Cross
- Division of Cardiology, Children's National Medical Center, W3-200, 111 Michigan Ave NW, Washington, DC, 20010, USA
| |
Collapse
|
19
|
Xue H, Brown LA, Nielles-Vallespin S, Plein S, Kellman P. Automatic in-line quantitative myocardial perfusion mapping: Processing algorithm and implementation. Magn Reson Med 2020; 83:712-730. [PMID: 31441550 PMCID: PMC8400845 DOI: 10.1002/mrm.27954] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Revised: 06/27/2019] [Accepted: 07/27/2019] [Indexed: 02/03/2023]
Abstract
PURPOSE Quantitative myocardial perfusion mapping has advantages over qualitative assessment, including the ability to detect global flow reduction. However, it is not clinically available and remains a research tool. Building upon the previously described imaging sequence, this study presents algorithm and implementation of an automated solution for inline perfusion flow mapping with step by step performance characterization. METHODS Proposed workflow consists of motion correction (MOCO), arterial input function blood detection, intensity to gadolinium concentration conversion, and pixel-wise mapping. A distributed kinetics model, blood-tissue exchange model, is implemented, computing pixel-wise maps of myocardial blood flow (mL/min/g), permeability-surface-area product (mL/min/g), blood volume (mL/g), and interstitial volume (mL/g). RESULTS Thirty healthy subjects (11 men; 26.4 ± 10.4 years) were recruited and underwent adenosine stress perfusion cardiovascular MR. Mean MOCO quality score was 3.6 ± 0.4 for stress and 3.7 ± 0.4 for rest. Myocardial Dice similarity coefficients after MOCO were significantly improved (P < 1e-6), 0.87 ± 0.05 for stress and 0.86 ± 0.06 for rest. Arterial input function peak gadolinium concentration was 4.4 ± 1.3 mmol/L at stress and 5.2 ± 1.5 mmol/L at rest. Mean myocardial blood flow at stress and rest were 2.82 ± 0.47 mL/min/g and 0.68 ± 0.16 mL/min/g, respectively. The permeability-surface-area product was 1.32 ± 0.26 mL/min/g at stress and 1.09 ± 0.21 mL/min/g at rest (P < 1e-3). Blood volume was 12.0 ± 0.8 mL/100 g at stress and 9.7 ± 1.0 mL/100 g at rest (P < 1e-9), indicating good adenosine vasodilation response. Interstitial volume was 20.8 ± 2.5 mL/100 g at stress and 20.3 ± 2.9 mL/100 g at rest (P = 0.50). CONCLUSIONS An inline perfusion flow mapping workflow is proposed and demonstrated on normal volunteers. Initial evaluation demonstrates this fully automated solution for the respiratory MOCO, arterial input function left ventricle mask detection, and pixel-wise mapping, from free-breathing myocardial perfusion imaging.
Collapse
Affiliation(s)
- Hui Xue
- National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | - Louise A.E. Brown
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | | | - Sven Plein
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Peter Kellman
- National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland
| |
Collapse
|
20
|
Houghton JSM, Nduwayo S, Nickinson ATO, Payne TJ, Sterland S, Nath M, Gray LJ, McMahon GS, Rayt HS, Singh SJ, Robinson TG, Conroy SP, Haunton VJ, McCann GP, Bown MJ, Davies RSM, Sayers RD. Leg ischaemia management collaboration (LIMb): study protocol for a prospective cohort study at a single UK centre. BMJ Open 2019; 9:e031257. [PMID: 31481569 PMCID: PMC6731919 DOI: 10.1136/bmjopen-2019-031257] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
INTRODUCTION Severe limb ischaemia (SLI) is the end stage of peripheral arterial occlusive disease where the viability of the limb is threatened. Around 25% of patients with SLI will ultimately require a major lower limb amputation, which has a substantial adverse impact on quality of life. A newly established rapid-access vascular limb salvage clinic and modern revascularisation techniques may reduce amputation rate. The aim of this study was to investigate the 12-month amputation rate in a contemporary cohort of patients and compare this to a historical cohort. Secondary aims are to investigate the use of frailty and cognitive assessments, and cardiac MRI in risk-stratifying patients with SLI undergoing intervention and establish a biobank for future biomarker analyses. METHODS AND ANALYSIS This single-centre prospective cohort study will recruit patients aged 18-110 years presenting with SLI. Those undergoing intervention will be eligible to undergo additional venepuncture (for biomarker analysis) and/or cardiac MRI. Those aged ≥65 years and undergoing intervention will also be eligible to undergo additional frailty and cognitive assessments. Follow-up will be at 12 and 24 months and subsequently via data linkage with NHS Digital to 10 years postrecruitment. Those undergoing cardiac MRI and/or frailty assessments will receive additional follow-up during the first 12 months to investigate for perioperative myocardial infarction and frailty-related outcomes, respectively. A sample size of 420 patients will be required to detect a 10% reduction in amputation rate in comparison to a similar sized historical cohort, with 90% power and 5% type I error rate. Statistical analysis of this comparison will be by adjusted and unadjusted logistic regression analyses. ETHICS AND DISSEMINATION Ethical approval for this study has been granted by the UK National Research Ethics Service (19/LO/0132). Results will be disseminated to participants via scientific meetings, peer-reviewed medical journals and social media. TRIAL REGISTRATION NUMBER NCT04027244.
Collapse
Affiliation(s)
- John S M Houghton
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- Leicester Vascular Institute, University Hospitals of Leicester NHS Trust, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre - The Glenfield Hospital, Leicester, UK
| | - Sarah Nduwayo
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- Leicester Vascular Institute, University Hospitals of Leicester NHS Trust, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre - The Glenfield Hospital, Leicester, UK
| | - Andrew T O Nickinson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- Leicester Vascular Institute, University Hospitals of Leicester NHS Trust, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre - The Glenfield Hospital, Leicester, UK
| | - Tanya J Payne
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre - The Glenfield Hospital, Leicester, UK
| | - Sue Sterland
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre - The Glenfield Hospital, Leicester, UK
| | - Mintu Nath
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre - The Glenfield Hospital, Leicester, UK
| | - Laura J Gray
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Greg S McMahon
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- Leicester Vascular Institute, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Harjeet S Rayt
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- Leicester Vascular Institute, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Sally J Singh
- Cardiac/Pulmonary Rehabilitation, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Thompson G Robinson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre - The Glenfield Hospital, Leicester, UK
| | - Simon P Conroy
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Victoria J Haunton
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| | - Gerry P McCann
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre - The Glenfield Hospital, Leicester, UK
| | - Matthew J Bown
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- Leicester Vascular Institute, University Hospitals of Leicester NHS Trust, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre - The Glenfield Hospital, Leicester, UK
| | - Robert S M Davies
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- Leicester Vascular Institute, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Rob D Sayers
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- Leicester Vascular Institute, University Hospitals of Leicester NHS Trust, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre - The Glenfield Hospital, Leicester, UK
| |
Collapse
|
21
|
Joint intracranial and carotid vessel wall imaging in 5 minutes using compressed sensing accelerated DANTE-SPACE. Eur Radiol 2019; 30:119-127. [DOI: 10.1007/s00330-019-06366-7] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Revised: 06/22/2019] [Accepted: 07/10/2019] [Indexed: 11/25/2022]
|
22
|
Knott KD, Augusto JB, Nordin S, Kozor R, Camaioni C, Xue H, Hughes RK, Manisty C, Brown LAE, Kellman P, Ramaswami U, Hughes D, Plein S, Moon JC. Quantitative Myocardial Perfusion in Fabry Disease. Circ Cardiovasc Imaging 2019; 12:e008872. [PMID: 31269811 DOI: 10.1161/circimaging.119.008872] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
BACKGROUND Fabry disease (FD) is an X-linked lysosomal storage disease resulting in tissue accumulation of sphingolipids. Key myocardial processes that lead to adverse outcomes in FD include storage, hypertrophy, inflammation, and fibrosis. These are quantifiable by multiparametric cardiovascular magnetic resonance. Recent developments in cardiovascular magnetic resonance perfusion mapping allow rapid in-line perfusion quantification permitting broader clinical application, including the assessment of microvascular dysfunction. We hypothesized that microvascular dysfunction in FD would be associated with storage, fibrosis, and edema. METHODS A prospective, observational study of 44 FD patients (49 years, 43% male, 24 [55%] with left ventricular hypertrophy [LVH]) and 27 healthy controls with multiparametric cardiovascular magnetic resonance including vasodilator stress perfusion mapping. Myocardial blood flow (MBF) was measured and its associations with other processes investigated. RESULTS Compared with LVH- FD, LVH+ FD had higher left ventricular ejection fraction (73% versus 68%), more late gadolinium enhancement (85% versus 15%), and a lower stress MBF (1.76 versus 2.36 mL/g per minute). The reduction in stress MBF was more pronounced in the subendocardium than subepicardium. LVH- FD had lower stress MBF than controls (2.36 versus 3.00 mL/g per minute; P=0.002). Across all FD, late gadolinium enhancement and low native T1 were independently associated with reduced stress MBF. On a per-segment basis, stress MBF was independently associated with wall thickness, T2, extracellular volume fraction, and late gadolinium enhancement. CONCLUSIONS FD patients have reduced perfusion, particularly in the subendocardium with greater reductions with LVH, storage, edema, and scar. Perfusion is reduced even without LVH suggesting it is an early disease marker.
Collapse
Affiliation(s)
- Kristopher D Knott
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., J.B.A., S.N., R.K.H., C.M., J.C.M.).,Advanced Cardiac Imaging, Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London, United Kingdom (K.D.K., J.B.A., S.N., C.C., R.K.H., C.M., J.C.M.)
| | - Joao B Augusto
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., J.B.A., S.N., R.K.H., C.M., J.C.M.).,Advanced Cardiac Imaging, Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London, United Kingdom (K.D.K., J.B.A., S.N., C.C., R.K.H., C.M., J.C.M.)
| | - Sabrina Nordin
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., J.B.A., S.N., R.K.H., C.M., J.C.M.).,Advanced Cardiac Imaging, Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London, United Kingdom (K.D.K., J.B.A., S.N., C.C., R.K.H., C.M., J.C.M.)
| | - Rebecca Kozor
- Sydney Medical School, University of Sydney, Australia (R.K.)
| | - Claudia Camaioni
- Advanced Cardiac Imaging, Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London, United Kingdom (K.D.K., J.B.A., S.N., C.C., R.K.H., C.M., J.C.M.)
| | - Hui Xue
- Medical Signal and Image Processing, National Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, Bethesda, MD (H.X., P.K.)
| | - Rebecca K Hughes
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., J.B.A., S.N., R.K.H., C.M., J.C.M.).,Advanced Cardiac Imaging, Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London, United Kingdom (K.D.K., J.B.A., S.N., C.C., R.K.H., C.M., J.C.M.)
| | - Charlotte Manisty
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., J.B.A., S.N., R.K.H., C.M., J.C.M.).,Advanced Cardiac Imaging, Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London, United Kingdom (K.D.K., J.B.A., S.N., C.C., R.K.H., C.M., J.C.M.)
| | - Louise A E Brown
- Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, United Kingdom (L.A.E.B., S.P.)
| | - Peter Kellman
- Medical Signal and Image Processing, National Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, Bethesda, MD (H.X., P.K.)
| | - Uma Ramaswami
- Lysosomal Storage Disorder Unit, Royal Free Hospital, London, United Kingdom (U.R., D.H.)
| | - Derralyn Hughes
- Lysosomal Storage Disorder Unit, Royal Free Hospital, London, United Kingdom (U.R., D.H.)
| | - Sven Plein
- Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, United Kingdom (L.A.E.B., S.P.)
| | - James C Moon
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., J.B.A., S.N., R.K.H., C.M., J.C.M.).,Advanced Cardiac Imaging, Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London, United Kingdom (K.D.K., J.B.A., S.N., C.C., R.K.H., C.M., J.C.M.)
| |
Collapse
|
23
|
Captur G, Lobascio I, Ye Y, Culotta V, Boubertakh R, Xue H, Kellman P, Moon JC. Motion-corrected free-breathing LGE delivers high quality imaging and reduces scan time by half: an independent validation study. Int J Cardiovasc Imaging 2019; 35:1893-1901. [PMID: 31104178 PMCID: PMC6773664 DOI: 10.1007/s10554-019-01620-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Accepted: 05/06/2019] [Indexed: 02/05/2023]
Abstract
Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) sequences have evolved. Free-breathing motion-corrected (MOCO) LGE has potential advantages over breath-held (bh) LGE including minimal user input for the short axis (SAX) stack without breath-holds. It has previously been shown that MOCO-LGE delivers high image quality compared to bh-LGE. We sought to conduct an independent validation study to investigate real-world performance of bh-LGE versus MOCO-LGE in a high-throughput CMR center immediately after the introduction of the MOCO-LGE sequence and with elementary staff induction in its use. Four-hundred consecutive patients, referred for CMR and graded by clinical complexity, underwent CMR on either of two scanners (1.5 T, both Siemens) in a UK tertiary cardiac center. Scar imaging was by bh-LGE or MOCO-LGE (both with phase sensitive inversion recovery). Image quality, scan time, reader confidence and report reproducibility were compared between those scanned by bh-LGE versus MOCO-LGE. Readers had > 3 years CMR experience. Categorical variables were compared by χ2 or Fisher’s exact tests and continuous variables by unpaired Student’s t-test. Inter-rater agreement of LGE reports was by Cohen’s kappa. Image quality (low score = better) was better for MOCO-LGE (median, interquartile range [Q1–Q3]: 0 [0–0] vs. 2 [0–3], P < 0.0001). This persisted when just clinically complex patients were assessed (0 [0–1] vs. 2 [1–4] P < 0.0001). Readers were more confident in their MOCO-LGE rulings (P < 0.001) and reports more reproducible [bh-LGE vs. MOCO-LGE: kappa 0.76, confidence interval (CI) 0.7–0.9 vs. 0.82, CI 0.7–0.9]. MOCO-LGE significantly shortened LGE acquisition times compared to bh-LGE (for left ventricle SAX stack: 03:22 ± 01:14 vs 06:09 ± 01:47 min respectively, P < 0.0001). In a busy clinical service, immediately after its introduction and with elementary staff training, MOCO-LGE is demonstrably faster to bh-LGE, providing better images that are easier to interpret, even in the sickest of patients.
Collapse
Affiliation(s)
- Gabriella Captur
- Institute of Cardiovascular Science, University College London, Gower Street, London, UK
| | - Ilaria Lobascio
- Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit, St Bartholomew's Hospital, West Smithfield, London, UK
| | - Yang Ye
- Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit, St Bartholomew's Hospital, West Smithfield, London, UK.,Department of Cardiology, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, No. 3 Qingchun East Road, Hangzhou, 310016, Zhejiang, People's Republic of China
| | - Veronica Culotta
- Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit, St Bartholomew's Hospital, West Smithfield, London, UK
| | - Redha Boubertakh
- Cardiovascular Biomedical Research Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Hui Xue
- National Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, Bethesda, MD, USA
| | - Peter Kellman
- National Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, Bethesda, MD, USA
| | - James C Moon
- Institute of Cardiovascular Science, University College London, Gower Street, London, UK. .,Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit, St Bartholomew's Hospital, West Smithfield, London, UK.
| |
Collapse
|
24
|
Merlocco A, Olivieri L, Kellman P, Xue H, Cross R. Improved Workflow for Quantification of Right Ventricular Volumes Using Free-Breathing Motion Corrected Cine Imaging. Pediatr Cardiol 2019; 40:79-88. [PMID: 30136135 PMCID: PMC9581608 DOI: 10.1007/s00246-018-1963-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Accepted: 08/12/2018] [Indexed: 01/20/2023]
Abstract
Cardiac MR traditionally requires breath-holding for cine imaging. Younger or less stable patients benefit from free-breathing during cardiac MR but current free-breathing cine images can be spatially blurred. Motion corrected re-binning (MOC) is a novel approach that acquires and then reformats real-time images over multiple cardiac cycles with high spatial resolution. The technique was previously limited by reconstruction time but distributed computing has reduced these times. Using this technique, left ventricular volumetry has compared favorably to breath-held balanced steady-state free precession cine imaging (BH), the current gold-standard, however, right ventricular volumetry validation remains incomplete, limiting the applicability of MOC in clinical practice. Fifty subjects underwent cardiac MR for evaluation of right ventricular size and function by end-diastolic (EDV) and end-systolic (ESV) volumetry. Measurements using MOC were compared to those using BH. Pearson correlation coefficients and Bland-Altman plots tested agreement across techniques. Total scan plus reconstruction times were tested for significant differences using paired t-test. Volumes obtained by MOC compared favorably to BH (R = 0.9911 for EDV, 0.9690 for ESV). Combined acquisition and reconstruction time (previously reported) were reduced 37% for MOC, requiring a mean of 5.2 min compared to 8.2 min for BH (p < 0.0001). Right ventricular volumetry compares favorably to BH using MOC image reconstruction, but is obtained in a fraction of the time. Combined with previous validation of its use for the left ventricle, this novel method now offers an alternative imaging approach in appropriate clinical settings.
Collapse
Affiliation(s)
- Anthony Merlocco
- Division of Cardiology, Children's National Health System, and the Department of Pediatrics, George Washington Medical School, Washington, DC, USA. .,University of Tennessee Health Science Center, Le Bonheur Children's Hospital, 49 N. Dunlap Room 363, Memphis, TN, 38103, USA.
| | - Laura Olivieri
- Division of Cardiology, Children’s National Health System, and the Department of Pediatrics, George Washington Medical School, Washington, DC, USA
| | - Peter Kellman
- National Institutes of Health/NHLBI, 10 Center Dr., Bethesda, MD, USA
| | - Hui Xue
- National Institutes of Health/NHLBI, 10 Center Dr., Bethesda, MD, USA
| | - Russell Cross
- Division of Cardiology, Children’s National Health System, and the Department of Pediatrics, George Washington Medical School, Washington, DC, USA
| |
Collapse
|
25
|
Merlocco A, Cross RR, Kellman P, Xue H, Olivieri L. Validation of cardiac magnetic-resonance-derived left ventricular strain measurements from free-breathing motion-corrected cine imaging. Pediatr Radiol 2019; 49:68-75. [PMID: 30244412 PMCID: PMC8432251 DOI: 10.1007/s00247-018-4251-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Revised: 06/18/2018] [Accepted: 08/29/2018] [Indexed: 10/28/2022]
Abstract
BACKGROUND Myocardial strain is an important measure of cardiac function and can be assessed on cardiac magnetic resonance (MR) through the current gold standard of breath-held segmented steady-state free precession (SSFP) cine imaging. Novel free-breathing techniques have been validated for volumetry and systolic function, allowing for evaluation of sicker and younger children who cannot reliably hold their breath. It is unclear whether strain measurements can be reliably performed on free-breathing, motion-corrected, re-binning cine images. OBJECTIVE To compare strain analysis from motion-corrected retrospective re-binning images to the breath-held SSFP cine images to explore their validity. MATERIALS AND METHODS Twenty-five children and young adults, ages (2.1-18.6 years) underwent breath-held and motion-corrected retrospective re-binning cine techniques during the same MR examination on a 1.5-tesla magnet. We measured endocardial end-systolic global circumferential strain and endocardial averaged segmental strain using commercial software (MEDIS QStrain 2.1). We used Pearson correlation coefficients to test agreement across techniques. RESULTS Analysis was possible in all 25 breath-held and motion-corrected retrospective re-binning studies. Global circumferential strain and endocardial averaged segmental strain obtained by motion-corrected retrospective re-binning compared favorably to breath-held studies. Global circumferential strain linear regression models demonstrated acceptable agreement, with coefficients of determination of 0.75 for breath-held compared to motion-corrected retrospective re-binning (P<0.001) and for endocardial averaged segmental strain comparisons yielded 0.77 for breath-held vs. motion-corrected retrospective re-binning (P<0.001). Bland-Altman assessment demonstrated minimal bias for breath-held compared to motion-corrected retrospective re-binning (mean 2.4 and 1.9, respectively, for global circumferential strain and endocardial averaged segmental strain). CONCLUSION Free-breathing imaging by motion-corrected retrospective re-binning cine imaging provides adequate spatial and temporal resolution to measure myocardial deformation when compared to the gold-standard breath-held SSFP cine imaging in children with normal or borderline systolic function.
Collapse
Affiliation(s)
- Anthony Merlocco
- Division of Cardiology, Children's National Health System, Department of Pediatrics, George Washington Medical School, Washington, DC, USA.
- Division of Cardiology, Le Bonheur Children's Hospital, Department of Pediatrics, University of Tennessee Health Science Center, 49 North Dunlap St., Faculty Office Building, 3rd floor, Memphis, TN, 38105, USA.
| | - Russell R Cross
- Division of Cardiology, Children's National Health System, Department of Pediatrics, George Washington Medical School, Washington, DC, USA
| | - Peter Kellman
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Hui Xue
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Laura Olivieri
- Division of Cardiology, Children's National Health System, Department of Pediatrics, George Washington Medical School, Washington, DC, USA
| |
Collapse
|
26
|
Restivo MC, Campbell-Washburn AE, Kellman P, Xue H, Ramasawmy R, Hansen MS. A framework for constraining image SNR loss due to MR raw data compression. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2018; 32:213-225. [PMID: 30361947 DOI: 10.1007/s10334-018-0709-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Revised: 10/03/2018] [Accepted: 10/15/2018] [Indexed: 11/25/2022]
Abstract
INTRODUCTION Computationally intensive image reconstruction algorithms can be used online during MRI exams by streaming data to remote high-performance computers. However, data acquisition rates often exceed the bandwidth of the available network resources creating a bottleneck. Data compression is, therefore, desired to ensure fast data transmission. METHODS The added noise variance due to compression was determined through statistical analysis for two compression libraries (one custom and one generic) that were implemented in this framework. Limiting the compression error variance relative to the measured thermal noise allowed for image signal-to-noise ratio loss to be explicitly constrained. RESULTS Achievable compression ratios are dependent on image SNR, user-defined SNR loss tolerance, and acquisition type. However, a 1% reduction in SNR yields approximately four to ninefold compression ratios across MRI acquisition strategies. For free-breathing cine data reconstructed in the cloud, the streaming bandwidth was reduced from 37 to 6.1 MB/s, alleviating the network transmission bottleneck. CONCLUSION Our framework enabled data compression for online reconstructions and allowed SNR loss to be constrained based on a user-defined SNR tolerance. This practical tool will enable real-time data streaming and greater than fourfold faster cloud upload times.
Collapse
Affiliation(s)
- Matthew C Restivo
- Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Rm B1D47, 10 Center Dr, Bethesda, MD, 20814, USA.
| | - Adrienne E Campbell-Washburn
- Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Rm B1D47, 10 Center Dr, Bethesda, MD, 20814, USA
| | - Peter Kellman
- Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Rm B1D47, 10 Center Dr, Bethesda, MD, 20814, USA
| | - Hui Xue
- Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Rm B1D47, 10 Center Dr, Bethesda, MD, 20814, USA
| | - Rajiv Ramasawmy
- Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Rm B1D47, 10 Center Dr, Bethesda, MD, 20814, USA
| | - Michael S Hansen
- Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Rm B1D47, 10 Center Dr, Bethesda, MD, 20814, USA
| |
Collapse
|
27
|
Bydder M, Zaaraoui W, Ridley B, Soubrier M, Bertinetti M, Confort-Gouny S, Schad L, Guye M, Ranjeva JP. Dynamic 23Na MRI - A non-invasive window on neuroglial-vascular mechanisms underlying brain function. Neuroimage 2018; 184:771-780. [PMID: 30292814 DOI: 10.1016/j.neuroimage.2018.09.071] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2018] [Revised: 09/21/2018] [Accepted: 09/25/2018] [Indexed: 11/17/2022] Open
Abstract
A novel magnetic resonance imaging (MRI) acquisition and reconstruction method for obtaining a series of dynamic sodium 23Na-MRI acquisitions was designed to non-invasively assess the signal variations of brain sodium during a hand motor task in 14 healthy human volunteers on an ultra high field (7T) MR scanner. Regions undergoing activation and deactivation were identified with reference to conventional task-related BOLD functional MRI (fMRI). Activation observed in the left central regions, the supplementary motor areas and the left cerebellum induced an increase in the sodium signal observed at ultra short echo time and a decrease in the 23Na signal observed at long echo time. Based on a simple model of two distinct sodium pools (namely, restricted and mobile sodium), the ultra short echo time measures the totality of sodium whereas the long echo time is mainly sensitive to mobile sodium. This activation pattern is consistent with previously described processes related to an influx of Na+ into the intracellular compartments and a moderate increase in the cerebral blood volume (CBV). In contrast, deactivation observed in the right central regions ipsilateral to the movement, the precuneus and the left cerebellum induced a slight decrease in sodium signal at ultra short echo time and an increase of sodium signal at longer echo times. This inhibitory pattern is compatible with a slight decrease in CBV and an efflux of intracellular Na+ to the extracellular compartments that may reflect neural dendritic spine and astrocytic shrinkage, and an increase of sodium in the extracellular fraction. In conclusion, cerebral dynamic 23Na MRI experiments can provide access to the ionic transients following a functional task occurring within the neuro-glial-vascular ensemble. This has the potential to open up a novel non-invasive window on the mechanisms underlying brain function.
Collapse
Affiliation(s)
- Mark Bydder
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, University Hospital Timone, CEMEREM, Marseille, France
| | - Wafaa Zaaraoui
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, University Hospital Timone, CEMEREM, Marseille, France
| | - Ben Ridley
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, University Hospital Timone, CEMEREM, Marseille, France
| | - Manon Soubrier
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, University Hospital Timone, CEMEREM, Marseille, France
| | - Marie Bertinetti
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, University Hospital Timone, CEMEREM, Marseille, France
| | - Sylviane Confort-Gouny
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, University Hospital Timone, CEMEREM, Marseille, France
| | - Lothar Schad
- Computer Assisted Clinical Medicine, Centre for Biomedicine and Medical Technology Mannheim, Heidelberg University, Mannheim, Germany
| | - Maxime Guye
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, University Hospital Timone, CEMEREM, Marseille, France
| | - Jean-Philippe Ranjeva
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, University Hospital Timone, CEMEREM, Marseille, France.
| |
Collapse
|
28
|
Moehlman TM, de Zwart JA, Chappel-Farley MG, Liu X, McClain IB, Chang C, Mandelkow H, Özbay PS, Johnson NL, Bieber RE, Fernandez KA, King KA, Zalewski CK, Brewer CC, van Gelderen P, Duyn JH, Picchioni D. All-night functional magnetic resonance imaging sleep studies. J Neurosci Methods 2018; 316:83-98. [PMID: 30243817 DOI: 10.1016/j.jneumeth.2018.09.019] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2018] [Revised: 08/08/2018] [Accepted: 09/17/2018] [Indexed: 01/24/2023]
Abstract
BACKGROUND Previous functional magnetic resonance imaging (fMRI) sleep studies have been hampered by the difficulty of obtaining extended amounts of sleep in the sleep-adverse environment of the scanner and often have resorted to manipulations such as sleep depriving subjects before scanning. These manipulations limit the generalizability of the results. NEW METHOD The current study is a methodological validation of procedures aimed at obtaining all-night fMRI data in sleeping subjects with minimal exposure to experimentally induced sleep deprivation. Specifically, subjects slept in the scanner on two consecutive nights, allowing the first night to serve as an adaptation night. RESULTS/COMPARISON WITH EXISTING METHOD(S) Sleep scoring results from simultaneously acquired electroencephalography data on Night 2 indicate that subjects (n = 12) reached the full spectrum of sleep stages including slow-wave (M = 52.1 min, SD = 26.5 min) and rapid eye movement (REM, M = 45.2 min, SD = 27.9 min) sleep and exhibited a mean of 2.1 (SD = 1.1) nonREM-REM sleep cycles. CONCLUSIONS It was found that by diligently applying fundamental principles and methodologies of sleep and neuroimaging science, performing all-night fMRI sleep studies is feasible. However, because the two nights of the study were performed consecutively, some sleep deprivation from Night 1 as a cause of the Night 2 results is likely, so consideration should be given to replicating the current study with a washout period. It is envisioned that other laboratories can adopt the core features of this protocol to obtain similar results.
Collapse
Affiliation(s)
- Thomas M Moehlman
- Advanced Magnetic Resonance Imaging Section, National Institute of Neurological Disorders and Stroke, USA
| | - Jacco A de Zwart
- Advanced Magnetic Resonance Imaging Section, National Institute of Neurological Disorders and Stroke, USA
| | - Miranda G Chappel-Farley
- Advanced Magnetic Resonance Imaging Section, National Institute of Neurological Disorders and Stroke, USA
| | - Xiao Liu
- Advanced Magnetic Resonance Imaging Section, National Institute of Neurological Disorders and Stroke, USA; Department of Biomedical Engineering, Pennsylvania State University, USA
| | - Irene B McClain
- Office of the Clinical Director, National Institute of Neurological Disorders and Stroke, USA
| | - Catie Chang
- Advanced Magnetic Resonance Imaging Section, National Institute of Neurological Disorders and Stroke, USA; Department of Electrical Engineering and Computer Science, Vanderbilt University, USA
| | - Hendrik Mandelkow
- Advanced Magnetic Resonance Imaging Section, National Institute of Neurological Disorders and Stroke, USA
| | - Pinar S Özbay
- Advanced Magnetic Resonance Imaging Section, National Institute of Neurological Disorders and Stroke, USA
| | - Nicholas L Johnson
- Advanced Magnetic Resonance Imaging Section, National Institute of Neurological Disorders and Stroke, USA
| | - Rebecca E Bieber
- Audiology Unit, National Institute on Deafness and Other Communication Disorders, USA
| | - Katharine A Fernandez
- Section on Sensory Cell Biology, National Institute on Deafness and Other Communication Disorders, USA
| | - Kelly A King
- Audiology Unit, National Institute on Deafness and Other Communication Disorders, USA
| | | | - Carmen C Brewer
- Audiology Unit, National Institute on Deafness and Other Communication Disorders, USA
| | - Peter van Gelderen
- Advanced Magnetic Resonance Imaging Section, National Institute of Neurological Disorders and Stroke, USA
| | - Jeff H Duyn
- Advanced Magnetic Resonance Imaging Section, National Institute of Neurological Disorders and Stroke, USA
| | - Dante Picchioni
- Advanced Magnetic Resonance Imaging Section, National Institute of Neurological Disorders and Stroke, USA; Section on Neuroadaptation and Protein Metabolism, National Institute of Mental Health, USA.
| |
Collapse
|
29
|
Engel M, Kasper L, Barmet C, Schmid T, Vionnet L, Wilm B, Pruessmann KP. Single‐shot spiral imaging at 7
T. Magn Reson Med 2018; 80:1836-1846. [DOI: 10.1002/mrm.27176] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Revised: 02/15/2018] [Accepted: 02/18/2018] [Indexed: 01/18/2023]
Affiliation(s)
- Maria Engel
- Institute for Biomedical EngineeringETH Zurich and University of ZurichZurich Switzerland
| | - Lars Kasper
- Institute for Biomedical EngineeringETH Zurich and University of ZurichZurich Switzerland
- Translational Neuromodeling Unit, Institute for Biomedical EngineeringUniversity of Zurich and ETH ZurichZurich Switzerland
| | - Christoph Barmet
- Institute for Biomedical EngineeringETH Zurich and University of ZurichZurich Switzerland
- Skope Magnetic Resonance Technologies AGZurich Switzerland
| | - Thomas Schmid
- Institute for Biomedical EngineeringETH Zurich and University of ZurichZurich Switzerland
| | - Laetitia Vionnet
- Institute for Biomedical EngineeringETH Zurich and University of ZurichZurich Switzerland
| | - Bertram Wilm
- Institute for Biomedical EngineeringETH Zurich and University of ZurichZurich Switzerland
- Skope Magnetic Resonance Technologies AGZurich Switzerland
| | - Klaas P. Pruessmann
- Institute for Biomedical EngineeringETH Zurich and University of ZurichZurich Switzerland
| |
Collapse
|
30
|
Wang H, Peng H, Chang Y, Liang D. A survey of GPU-based acceleration techniques in MRI reconstructions. Quant Imaging Med Surg 2018; 8:196-208. [PMID: 29675361 DOI: 10.21037/qims.2018.03.07] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Image reconstruction in magnetic resonance imaging (MRI) clinical applications has become increasingly more complicated. However, diagnostic and treatment require very fast computational procedure. Modern competitive platforms of graphics processing unit (GPU) have been used to make high-performance parallel computations available, and attractive to common consumers for computing massively parallel reconstruction problems at commodity price. GPUs have also become more and more important for reconstruction computations, especially when deep learning starts to be applied into MRI reconstruction. The motivation of this survey is to review the image reconstruction schemes of GPU computing for MRI applications and provide a summary reference for researchers in MRI community.
Collapse
Affiliation(s)
- Haifeng Wang
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | | | - Yuchou Chang
- Computer Science and Engineering Technology Department, University of Houston-Downtown, Houston, Texas, USA
| | - Dong Liang
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| |
Collapse
|
31
|
Campbell-Washburn AE, Tavallaei MA, Pop M, Grant EK, Chubb H, Rhode K, Wright GA. Real-time MRI guidance of cardiac interventions. J Magn Reson Imaging 2017; 46:935-950. [PMID: 28493526 PMCID: PMC5675556 DOI: 10.1002/jmri.25749] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2017] [Accepted: 03/29/2017] [Indexed: 11/09/2022] Open
Abstract
Cardiac magnetic resonance imaging (MRI) is appealing to guide complex cardiac procedures because it is ionizing radiation-free and offers flexible soft-tissue contrast. Interventional cardiac MR promises to improve existing procedures and enable new ones for complex arrhythmias, as well as congenital and structural heart disease. Guiding invasive procedures demands faster image acquisition, reconstruction and analysis, as well as intuitive intraprocedural display of imaging data. Standard cardiac MR techniques such as 3D anatomical imaging, cardiac function and flow, parameter mapping, and late-gadolinium enhancement can be used to gather valuable clinical data at various procedural stages. Rapid intraprocedural image analysis can extract and highlight critical information about interventional targets and outcomes. In some cases, real-time interactive imaging is used to provide a continuous stream of images displayed to interventionalists for dynamic device navigation. Alternatively, devices are navigated relative to a roadmap of major cardiac structures generated through fast segmentation and registration. Interventional devices can be visualized and tracked throughout a procedure with specialized imaging methods. In a clinical setting, advanced imaging must be integrated with other clinical tools and patient data. In order to perform these complex procedures, interventional cardiac MR relies on customized equipment, such as interactive imaging environments, in-room image display, audio communication, hemodynamic monitoring and recording systems, and electroanatomical mapping and ablation systems. Operating in this sophisticated environment requires coordination and planning. This review provides an overview of the imaging technology used in MRI-guided cardiac interventions. Specifically, this review outlines clinical targets, standard image acquisition and analysis tools, and the integration of these tools into clinical workflow. LEVEL OF EVIDENCE 1 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2017;46:935-950.
Collapse
Affiliation(s)
- Adrienne E Campbell-Washburn
- Laboratory of Imaging Technology, Biochemistry and Biophysics Center, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Mohammad A Tavallaei
- Physical Sciences Platform and Schulich Heart Program, Sunnybrook Research Institute, Toronto, Ontario, Canada
- Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Mihaela Pop
- Physical Sciences Platform and Schulich Heart Program, Sunnybrook Research Institute, Toronto, Ontario, Canada
- Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Elena K Grant
- Laboratory of Imaging Technology, Biochemistry and Biophysics Center, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
- Department of Cardiology, Children's National Medical Center, Washington, DC, USA
| | - Henry Chubb
- Division of Imaging Sciences and Biomedical Engineering, King's College London, UK
| | - Kawal Rhode
- Division of Imaging Sciences and Biomedical Engineering, King's College London, UK
| | - Graham A Wright
- Physical Sciences Platform and Schulich Heart Program, Sunnybrook Research Institute, Toronto, Ontario, Canada
- Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| |
Collapse
|
32
|
A review of GPU-based medical image reconstruction. Phys Med 2017; 42:76-92. [PMID: 29173924 DOI: 10.1016/j.ejmp.2017.07.024] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2017] [Revised: 07/06/2017] [Accepted: 07/30/2017] [Indexed: 11/20/2022] Open
Abstract
Tomographic image reconstruction is a computationally demanding task, even more so when advanced models are used to describe a more complete and accurate picture of the image formation process. Such advanced modeling and reconstruction algorithms can lead to better images, often with less dose, but at the price of long calculation times that are hardly compatible with clinical workflows. Fortunately, reconstruction tasks can often be executed advantageously on Graphics Processing Units (GPUs), which are exploited as massively parallel computational engines. This review paper focuses on recent developments made in GPU-based medical image reconstruction, from a CT, PET, SPECT, MRI and US perspective. Strategies and approaches to get the most out of GPUs in image reconstruction are presented as well as innovative applications arising from an increased computing capacity. The future of GPU-based image reconstruction is also envisioned, based on current trends in high-performance computing.
Collapse
|
33
|
Rogers T, Ratnayaka K, Khan JM, Stine A, Schenke WH, Grant LP, Mazal JR, Grant EK, Campbell-Washburn A, Hansen MS, Ramasawmy R, Herzka DA, Xue H, Kellman P, Faranesh AZ, Lederman RJ. CMR fluoroscopy right heart catheterization for cardiac output and pulmonary vascular resistance: results in 102 patients. J Cardiovasc Magn Reson 2017; 19:54. [PMID: 28750642 PMCID: PMC5530573 DOI: 10.1186/s12968-017-0366-2] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2017] [Accepted: 06/21/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Quantification of cardiac output and pulmonary vascular resistance (PVR) are critical components of invasive hemodynamic assessment, and can be measured concurrently with pressures using phase contrast CMR flow during real-time CMR guided cardiac catheterization. METHODS One hundred two consecutive patients underwent CMR fluoroscopy guided right heart catheterization (RHC) with simultaneous measurement of pressure, cardiac output and pulmonary vascular resistance using CMR flow and the Fick principle for comparison. Procedural success, catheterization time and adverse events were prospectively collected. RESULTS RHC was successfully completed in 97/102 (95.1%) patients without complication. Catheterization time was 20 ± 11 min. In patients with and without pulmonary hypertension, baseline mean pulmonary artery pressure was 39 ± 12 mmHg vs. 18 ± 4 mmHg (p < 0.001), right ventricular (RV) end diastolic volume was 104 ± 64 vs. 74 ± 24 (p = 0.02), and RV end-systolic volume was 49 ± 30 vs. 31 ± 13 (p = 0.004) respectively. 103 paired cardiac output and 99 paired PVR calculations across multiple conditions were analyzed. At baseline, the bias between cardiac output by CMR and Fick was 5.9% with limits of agreement -38.3% and 50.2% with r = 0.81 (p < 0.001). The bias between PVR by CMR and Fick was -0.02 WU.m2 with limits of agreement -2.6 and 2.5 WU.m2 with r = 0.98 (p < 0.001). Correlation coefficients were lower and limits of agreement wider during physiological provocation with inhaled 100% oxygen and 40 ppm nitric oxide. CONCLUSIONS CMR fluoroscopy guided cardiac catheterization is safe, with acceptable procedure times and high procedural success rate. Cardiac output and PVR measurements using CMR flow correlated well with the Fick at baseline and are likely more accurate during physiological provocation with supplemental high-concentration inhaled oxygen. TRIAL REGISTRATION Clinicaltrials.gov NCT01287026 , registered January 25, 2011.
Collapse
Affiliation(s)
- Toby Rogers
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD USA
| | - Kanishka Ratnayaka
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD USA
- Department of Cardiology, Rady Children’s Hospital, San Diego, CA USA
| | - Jaffar M. Khan
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD USA
| | - Annette Stine
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD USA
| | - William H. Schenke
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD USA
| | - Laurie P. Grant
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD USA
| | - Jonathan R. Mazal
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD USA
| | - Elena K. Grant
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD USA
- Department of Cardiology, Children’s National Medical Center, Washington, DC USA
| | - Adrienne Campbell-Washburn
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD USA
| | - Michael S. Hansen
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD USA
| | - Rajiv Ramasawmy
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD USA
| | - Daniel A. Herzka
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD USA
| | - Hui Xue
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD USA
| | - Peter Kellman
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD USA
| | - Anthony Z. Faranesh
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD USA
| | - Robert J. Lederman
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD USA
- Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Building 10, Room 2c713, Bethesda, MD 20892-1538 USA
| |
Collapse
|
34
|
Comprehensive Multi-Dimensional MRI for the Simultaneous Assessment of Cardiopulmonary Anatomy and Physiology. Sci Rep 2017; 7:5330. [PMID: 28706270 PMCID: PMC5509743 DOI: 10.1038/s41598-017-04676-8] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2016] [Accepted: 05/18/2017] [Indexed: 01/22/2023] Open
Abstract
Diagnostic testing often assesses the cardiovascular or respiratory systems in isolation, ignoring the major pathophysiologic interactions between the systems in many diseases. When both systems are assessed currently, multiple modalities are utilized in costly fashion with burdensome logistics and decreased accessibility. Thus, we have developed a new acquisition and reconstruction paradigm using the flexibility of MRI to enable a comprehensive exam from a single 5-15 min scan. We constructed a compressive-sensing approach to pseudo-randomly acquire highly subsampled, multi-dimensionally-encoded and time-stamped data from which we reconstruct volumetric cardiac and respiratory motion phases, contrast-agent dynamics, and blood flow velocity fields. The proposed method, named XD flow, is demonstrated for (a) evaluating congenital heart disease, where the impact of bulk motion is reduced in a non-sedated neonatal patient and (b) where the observation of the impact of respiration on flow is necessary for diagnostics; (c) cardiopulmonary imaging, where cardiovascular flow, function, and anatomy information is needed along with pulmonary perfusion quantification; and in (d) renal function imaging, where blood velocities and glomerular filtration rates are simultaneously measured, which highlights the generality of the technique. XD flow has the ability to improve quantification and to provide additional data for patient diagnosis for comprehensive evaluations.
Collapse
|
35
|
Basha TA, Akçakaya M, Liew C, Tsao CW, Delling FN, Addae G, Ngo L, Manning WJ, Nezafat R. Clinical performance of high-resolution late gadolinium enhancement imaging with compressed sensing. J Magn Reson Imaging 2017; 46:1829-1838. [PMID: 28301075 DOI: 10.1002/jmri.25695] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2016] [Accepted: 02/15/2017] [Indexed: 11/08/2022] Open
Abstract
PURPOSE To evaluate diagnostic image quality of 3D late gadolinium enhancement (LGE) with high isotropic spatial resolution (∼1.4 mm3 ) images reconstructed from randomly undersampled k-space using LOw-dimensional-structure Self-learning and Thresholding (LOST). MATERIALS AND METHODS We prospectively enrolled 270 patients (181 men; 55 ± 14 years) referred for myocardial viability assessment. 3D LGE with isotropic spatial resolution of 1.4 ± 0.1 mm3 was acquired at 1.5T using a LOST acceleration rate of 3 to 5. In a subset of 121 patients, 3D LGE or phase-sensitive LGE were acquired with parallel imaging with an acceleration rate of 2 for comparison. Two readers evaluated image quality using a scale of 1 (poor) to 4 (excellent) and assessed for scar presence. The McNemar test statistic was used to compare the proportion of detected scar between the two sequences. We assessed the association between image quality and characteristics (age, gender, torso dimension, weight, heart rate), using generalized linear models. RESULTS Overall, LGE detection proportions for 3D LGE with LOST were similar between readers 1 and 2 (16.30% vs. 18.15%). For image quality, readers gave 85.9% and 80.0%, respectively, for images categorized as good or excellent. Overall proportion of scar presence was not statistically different from conventional 3D LGE (28% vs. 33% [P = 0.17] for reader 1 and 26% vs. 31% [P = 0.37] for reader 2). Increasing subject heart rate was associated with lower image quality (estimated slope = -0.009 (P = 0.001)). CONCLUSION High-resolution 3D LGE with LOST yields good to excellent image quality in >80% of patients and identifies patients with LV scar at the same rate as conventional 3D LGE. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017;46:1829-1838.
Collapse
Affiliation(s)
- Tamer A Basha
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.,Systems and Biomedical Engineering Department, University of Cairo, Cairo, Egypt
| | - Mehmet Akçakaya
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, Minnesota, USA.,Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Charlene Liew
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Connie W Tsao
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Francesca N Delling
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Gifty Addae
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Long Ngo
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Warren J Manning
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.,Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Reza Nezafat
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| |
Collapse
|
36
|
Kantasis G, Xanthis CG, Haris K, Heiberg E, Aletras AH. Cloud GPU-based simulations for SQUAREMR. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2017; 274:80-88. [PMID: 27889652 DOI: 10.1016/j.jmr.2016.11.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2016] [Revised: 11/10/2016] [Accepted: 11/16/2016] [Indexed: 06/06/2023]
Abstract
Quantitative Magnetic Resonance Imaging (MRI) is a research tool, used more and more in clinical practice, as it provides objective information with respect to the tissues being imaged. Pixel-wise T1 quantification (T1 mapping) of the myocardium is one such application with diagnostic significance. A number of mapping sequences have been developed for myocardial T1 mapping with a wide range in terms of measurement accuracy and precision. Furthermore, measurement results obtained with these pulse sequences are affected by errors introduced by the particular acquisition parameters used. SQUAREMR is a new method which has the potential of improving the accuracy of these mapping sequences through the use of massively parallel simulations on Graphical Processing Units (GPUs) by taking into account different acquisition parameter sets. This method has been shown to be effective in myocardial T1 mapping; however, execution times may exceed 30min which is prohibitively long for clinical applications. The purpose of this study was to accelerate the construction of SQUAREMR's multi-parametric database to more clinically acceptable levels. The aim of this study was to develop a cloud-based cluster in order to distribute the computational load to several GPU-enabled nodes and accelerate SQUAREMR. This would accommodate high demands for computational resources without the need for major upfront equipment investment. Moreover, the parameter space explored by the simulations was optimized in order to reduce the computational load without compromising the T1 estimates compared to a non-optimized parameter space approach. A cloud-based cluster with 16 nodes resulted in a speedup of up to 13.5 times compared to a single-node execution. Finally, the optimized parameter set approach allowed for an execution time of 28s using the 16-node cluster, without compromising the T1 estimates by more than 10ms. The developed cloud-based cluster and optimization of the parameter set reduced the execution time of the simulations involved in constructing the SQUAREMR multi-parametric database thus bringing SQUAREMR's applicability within time frames that would be likely acceptable in the clinic.
Collapse
Affiliation(s)
- George Kantasis
- Laboratory of Computing and Medical Informatics, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Christos G Xanthis
- Lund Cardiac MR Group, Department of Clinical Physiology and Nuclear Medicine, Lund University, Skåne University Hospital in Lund, Lund, Sweden; Laboratory of Computing and Medical Informatics, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Kostas Haris
- Laboratory of Computing and Medical Informatics, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Einar Heiberg
- Lund Cardiac MR Group, Department of Clinical Physiology and Nuclear Medicine, Lund University, Skåne University Hospital in Lund, Lund, Sweden; Department of Biomedical Engineering, Faculty of Engineering, Lund University, Lund, Sweden
| | - Anthony H Aletras
- Laboratory of Computing and Medical Informatics, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece; Lund Cardiac MR Group, Department of Clinical Physiology and Nuclear Medicine, Lund University, Skåne University Hospital in Lund, Lund, Sweden.
| |
Collapse
|
37
|
Yang ACY, Kretzler M, Sudarski S, Gulani V, Seiberlich N. Sparse Reconstruction Techniques in Magnetic Resonance Imaging: Methods, Applications, and Challenges to Clinical Adoption. Invest Radiol 2016; 51:349-64. [PMID: 27003227 PMCID: PMC4948115 DOI: 10.1097/rli.0000000000000274] [Citation(s) in RCA: 67] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
The family of sparse reconstruction techniques, including the recently introduced compressed sensing framework, has been extensively explored to reduce scan times in magnetic resonance imaging (MRI). While there are many different methods that fall under the general umbrella of sparse reconstructions, they all rely on the idea that a priori information about the sparsity of MR images can be used to reconstruct full images from undersampled data. This review describes the basic ideas behind sparse reconstruction techniques, how they could be applied to improve MRI, and the open challenges to their general adoption in a clinical setting. The fundamental principles underlying different classes of sparse reconstructions techniques are examined, and the requirements that each make on the undersampled data outlined. Applications that could potentially benefit from the accelerations that sparse reconstructions could provide are described, and clinical studies using sparse reconstructions reviewed. Lastly, technical and clinical challenges to widespread implementation of sparse reconstruction techniques, including optimization, reconstruction times, artifact appearance, and comparison with current gold standards, are discussed.
Collapse
Affiliation(s)
- Alice Chieh-Yu Yang
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, USA
| | - Madison Kretzler
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, USA
| | - Sonja Sudarski
- Institute for Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim - Heidelberg University, Heidelberg, Germany
| | - Vikas Gulani
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, USA
- Department of Radiology, University Hospitals of Cleveland, Cleveland, USA
| | - Nicole Seiberlich
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, USA
- Department of Radiology, University Hospitals of Cleveland, Cleveland, USA
| |
Collapse
|
38
|
Ting ST, Ahmad R, Jin N, Craft J, Serafim da Silveira J, Xue H, Simonetti OP. Fast implementation for compressive recovery of highly accelerated cardiac cine MRI using the balanced sparse model. Magn Reson Med 2016; 77:1505-1515. [DOI: 10.1002/mrm.26224] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2015] [Revised: 02/08/2016] [Accepted: 02/29/2016] [Indexed: 12/29/2022]
Affiliation(s)
- Samuel T Ting
- Department of Biomedical Engineering, The Ohio State University, Columbus, Ohio, USA.,Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University, Columbus, Ohio, USA
| | - Rizwan Ahmad
- Department of Electrical and Computer Engineering, The Ohio State University, Columbus, Ohio, USA.,Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University, Columbus, Ohio, USA
| | - Ning Jin
- Siemens Medical Solutions, Columbus, Ohio, USA
| | - Jason Craft
- Division of Cardiology, Advocate Christ Medical Center, Oak Lawn, Illinois, USA
| | - Juliana Serafim da Silveira
- Department of Internal Medicine, Division of Cardiovascular Medicine, The Ohio State University, Columbus, Ohio, USA
| | - Hui Xue
- The National Heart, Lung and Blood Institute, The National Institutes of Health, Bethesda, Maryland, USA
| | - Orlando P Simonetti
- Department of Biomedical Engineering, The Ohio State University, Columbus, Ohio, USA.,Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University, Columbus, Ohio, USA.,Department of Internal Medicine, Division of Cardiovascular Medicine, The Ohio State University, Columbus, Ohio, USA.,Department of Radiology, The Ohio State University, Columbus, Ohio, USA
| |
Collapse
|
39
|
Cross R, Olivieri L, O'Brien K, Kellman P, Xue H, Hansen M. Improved workflow for quantification of left ventricular volumes and mass using free-breathing motion corrected cine imaging. J Cardiovasc Magn Reson 2016; 18:10. [PMID: 26915830 PMCID: PMC4768329 DOI: 10.1186/s12968-016-0231-8] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2016] [Accepted: 02/22/2016] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND Traditional cine imaging for cardiac functional assessment requires breath-holding, which can be problematic in some situations. Free-breathing techniques have relied on multiple averages or real-time imaging, producing images that can be spatially and/or temporally blurred. To overcome this, methods have been developed to acquire real-time images over multiple cardiac cycles, which are subsequently motion corrected and reformatted to yield a single image series displaying one cardiac cycle with high temporal and spatial resolution. Application of these algorithms has required significant additional reconstruction time. The use of distributed computing was recently proposed as a way to improve clinical workflow with such algorithms. In this study, we have deployed a distributed computing version of motion corrected re-binning reconstruction for free-breathing evaluation of cardiac function. METHODS Twenty five patients and 25 volunteers underwent cardiovascular magnetic resonance (CMR) for evaluation of left ventricular end-systolic volume (ESV), end-diastolic volume (EDV), and end-diastolic mass. Measurements using motion corrected re-binning were compared to those using breath-held SSFP and to free-breathing SSFP with multiple averages, and were performed by two independent observers. Pearson correlation coefficients and Bland-Altman plots tested agreement across techniques. Concordance correlation coefficient and Bland-Altman analysis tested inter-observer variability. Total scan plus reconstruction times were tested for significant differences using paired t-test. RESULTS Measured volumes and mass obtained by motion corrected re-binning and by averaged free-breathing SSFP compared favorably to those obtained by breath-held SSFP (r = 0.9863/0.9813 for EDV, 0.9550/0.9685 for ESV, 0.9952/0.9771 for mass). Inter-observer variability was good with concordance correlation coefficients between observers across all acquisition types suggesting substantial agreement. Both motion corrected re-binning and averaged free-breathing SSFP acquisition and reconstruction times were shorter than breath-held SSFP techniques (p < 0.0001). On average, motion corrected re-binning required 3 min less than breath-held SSFP imaging, a 37% reduction in acquisition and reconstruction time. CONCLUSIONS The motion corrected re-binning image reconstruction technique provides robust cardiac imaging that can be used for quantification that compares favorably to breath-held SSFP as well as multiple average free-breathing SSFP, but can be obtained in a fraction of the time when using cloud-based distributed computing reconstruction.
Collapse
Affiliation(s)
- Russell Cross
- Division of Cardiology, Children's National Health System, 111 Michigan Avenue, NW, Washington, DC, 20010, USA.
| | - Laura Olivieri
- Division of Cardiology, Children's National Health System, 111 Michigan Avenue, NW, Washington, DC, 20010, USA.
| | - Kendall O'Brien
- Division of Cardiology, Children's National Health System, 111 Michigan Avenue, NW, Washington, DC, 20010, USA.
| | - Peter Kellman
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
| | - Hui Xue
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
| | - Michael Hansen
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
| |
Collapse
|
40
|
Mazal JR, Rogers T, Schenke WH, Faranesh AZ, Hansen M, O'Brien K, Ratnayaka K, Lederman RJ. Interventional-Cardiovascular MR: Role of the Interventional MR Technologist. Radiol Technol 2016; 87:261-70. [PMID: 26721838 PMCID: PMC4724808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
BACKGROUND Interventional-cardiovascular magnetic resonance (iCMR) is a promising clinical tool for adults and children who need a comprehensive hemodynamic catheterization of the heart. Magnetic resonance (MR) imaging-guided cardiac catheterization offers radiation-free examination with increased soft tissue contrast and unconstrained imaging planes for catheter guidance. The interventional MR technologist plays an important role in the care of patients undergoing such procedures. It is therefore helpful for technologists to understand the unique iCMR preprocedural preparation, procedural and imaging workflows, and management of emergencies. The authors report their team's experience from the National Institutes of Health Clinical Center and a collaborating pediatric site.
Collapse
|
41
|
Cheng JY, Hanneman K, Zhang T, Alley MT, Lai P, Tamir JI, Uecker M, Pauly JM, Lustig M, Vasanawala SS. Comprehensive motion-compensated highly accelerated 4D flow MRI with ferumoxytol enhancement for pediatric congenital heart disease. J Magn Reson Imaging 2015; 43:1355-68. [PMID: 26646061 DOI: 10.1002/jmri.25106] [Citation(s) in RCA: 74] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2015] [Accepted: 11/14/2015] [Indexed: 11/06/2022] Open
Abstract
PURPOSE To develop and evaluate motion-compensation and compressed-sensing techniques in 4D flow MRI for anatomical assessment in a comprehensive ferumoxytol-enhanced congenital heart disease (CHD) exam. MATERIALS AND METHODS A Cartesian 4D flow sequence was developed to enable intrinsic navigation and two variable-density sampling schemes: VDPoisson and VDRad. Four compressed-sensing methods were developed: A) VDPoisson scan reconstructed using spatial wavelets; B) added temporal total variation to A; C) VDRad scan using the same reconstruction as in B; and D) added motion compensation to C. With Institutional Review Board (IRB) approval and Health Insurance Portability and Accountability Act (HIPAA) compliance, 23 consecutive patients (eight females, mean 6.3 years) referred for ferumoxytol-enhanced CHD 3T MRI were recruited. Images were acquired and reconstructed using methods A-D. Two cardiovascular radiologists independently scored the images on a 5-point scale. These readers performed a paired wall motion and functional assessment between method D and 2D balanced steady-state free precession (bSSFP) CINE for 16 cases. RESULTS Method D had higher diagnostic image quality for most anatomical features (mean 3.8-4.8) compared to A (2.0-3.6), B (2.2-3.7), and C (2.9-3.9) with P < 0.05 with good interobserver agreement (κ ≥ 0.49). Method D had similar or better assessment of myocardial borders and cardiac motion compared to 2D bSSFP (P < 0.05, κ ≥ 0.77). All methods had good internal agreement in comparing aortic with pulmonic flow (BA mean < 0.02%, r > 0.85) and compared to method A (BA mean < 0.13%, r > 0.84) with P < 0.01. CONCLUSION Flow, functional, and anatomical assessment in CHD with ferumoxytol-enhanced 4D flow is feasible and can be significantly improved using motion compensation and compressed sensing. J. Magn. Reson. Imaging 2016;43:1355-1368.
Collapse
Affiliation(s)
- Joseph Y Cheng
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Kate Hanneman
- Department of Radiology, Stanford University, Stanford, California, USA.,University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Tao Zhang
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Marcus T Alley
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Peng Lai
- Global Applied Science Laboratory, GE Healthcare, Menlo Park, California, USA
| | - Jonathan I Tamir
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA
| | - Martin Uecker
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA
| | - John M Pauly
- Magnetic Resonance Systems Research Laboratory, Department of Electrical Engineering, Stanford University, Stanford, California, USA
| | - Michael Lustig
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA
| | | |
Collapse
|
42
|
Campbell-Washburn AE, Faranesh AZ, Lederman RJ, Hansen MS. Magnetic Resonance Sequences and Rapid Acquisition for MR-Guided Interventions. Magn Reson Imaging Clin N Am 2015; 23:669-79. [PMID: 26499283 DOI: 10.1016/j.mric.2015.05.006] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Interventional MR uses rapid imaging to guide diagnostic and therapeutic procedures. One of the attractions of MR-guidance is the abundance of inherent contrast mechanisms available. Dynamic procedural guidance with real-time imaging has pushed the limits of MR technology, demanding rapid acquisition and reconstruction paired with interactive control and device visualization. This article reviews the technical aspects of real-time MR sequences that enable MR-guided interventions.
Collapse
Affiliation(s)
- Adrienne E Campbell-Washburn
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 9000 Rockville Pike, Building 10, Room B1D416, Bethesda, MD 20892, USA.
| | - Anthony Z Faranesh
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 9000 Rockville Pike, Building 10, Room 2C713, Bethesda, MD 20892, USA
| | - Robert J Lederman
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 9000 Rockville Pike, Building 10, Room 2C713, Bethesda, MD 20892, USA
| | - Michael S Hansen
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 9000 Rockville Pike, Building 10, Room B1D416, Bethesda, MD 20892, USA
| |
Collapse
|
43
|
Longo MG, Vairo F, Souza CF, Giugliani R, Vedolin LM. Brain imaging and genetic risk in the pediatric population, part 1: inherited metabolic diseases. Neuroimaging Clin N Am 2015; 25:31-51. [PMID: 25476511 DOI: 10.1016/j.nic.2014.09.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
In this article, the genotype-MR phenotype correlation of the most common or clinically important inherited metabolic diseases (IMD) in the pediatric population is reviewed. A nonsystematic search of the PubMed/Medline database of relevant studies about "genotype-phenotype correlation" in IMD was performed. Some MR phenotypes related to specific gene mutations were found, such as bilateral hypertrophy of inferior olives in patients harboring POLG and SURF1 mutations, and central lesions in the cervical spinal cord in patients with nonketotic hyperglycinemia harboring GLRX5 gene mutation.
Collapse
Affiliation(s)
- Maria Gabriela Longo
- Radiology Service, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil
| | - Filippo Vairo
- Medical Genetics Service, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Post Graduation Program on Genetics and Molecular Biology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Carolina Fischinger Souza
- Medical Genetics Service, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil
| | - Roberto Giugliani
- Medical Genetics Service, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Department of Genetics, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Leonardo Modesti Vedolin
- Radiology Service, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Post Graduation Program on Medical Sciences: Medicine, Department of Internal Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
| |
Collapse
|