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Anand S, Lustig M. Beat Pilot Tone (BPT): Simultaneous MRI and RF motion sensing at arbitrary frequencies. Magn Reson Med 2024; 92:1768-1787. [PMID: 38872443 PMCID: PMC11429784 DOI: 10.1002/mrm.30150] [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: 09/12/2023] [Revised: 04/13/2024] [Accepted: 04/23/2024] [Indexed: 06/15/2024]
Abstract
PURPOSE To introduce a simple system exploitation with the potential to turn MRI scanners into general-purpose radiofrequency (RF) motion monitoring systems. METHODS Inspired by Pilot Tone (PT), this work proposes Beat Pilot Tone (BPT), in which two or more RF tones at arbitrary frequencies are transmitted continuously during the scan. These tones create motion-modulated standing wave patterns that are sensed by the receiver coil array, incidentally mixed by intermodulation in the receiver chain, and digitized simultaneously with the MRI data. BPT can operate at almost any frequency as long as the intermodulation products lie within the bandwidth of the receivers. BPT's mechanism is explained in electromagnetic simulations and validated experimentally. RESULTS Phantom and volunteer experiments over a range of transmit frequencies suggest that BPT may offer frequency-dependent sensitivity to motion. Using a semi-flexible anterior receiver array, BPT appears to sense cardiac-induced body vibrations at microwave frequencies (≥ $$ \ge $$ 1.2 GHz). At lower frequencies, it exhibits a similar cardiac signal shape to PT, likely due to blood volume changes. Other volunteer experiments with respiratory, bulk, and head motion show that BPT can achieve greater sensitivity to motion than PT and greater separability between motion types. Basic multiple-input multiple-output (4 × 22 $$ 4\times 22 $$ MIMO) operation with simultaneous PT and BPT in head motion is demonstrated using two transmit antennas and a 22-channel head-neck coil. CONCLUSION BPT may offer a rich source of motion information that is frequency-dependent, simultaneous, and complementary to PT and the MRI exam.
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Affiliation(s)
- Suma Anand
- Electrical Engineering and Computer Sciences, University of California, Berkeley, California
| | - Michael Lustig
- Electrical Engineering and Computer Sciences, University of California, Berkeley, California
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Holtackers RJ, Stuber M. Free-Running Cardiac and Respiratory Motion-Resolved Imaging: A Paradigm Shift for Managing Motion in Cardiac MRI? Diagnostics (Basel) 2024; 14:1946. [PMID: 39272732 PMCID: PMC11394669 DOI: 10.3390/diagnostics14171946] [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: 08/16/2024] [Revised: 08/30/2024] [Accepted: 08/30/2024] [Indexed: 09/15/2024] Open
Abstract
Cardiac magnetic resonance imaging (MRI) is widely used for non-invasive assessment of cardiac morphology, function, and tissue characteristics due to its exquisite soft-tissue contrast. However, it remains time-consuming and requires proficiency, making it costly and limiting its widespread use. Traditional cardiac MRI is inefficient as signal acquisition is often limited to specific cardiac phases and requires complex view planning, parameter adjustments, and management of both respiratory and cardiac motion. Recent efforts have aimed to make cardiac MRI more efficient and accessible. Among these innovations, the free-running framework enables 5D whole-heart imaging without the need for an electrocardiogram signal, respiratory breath-holding, or complex planning. It uses a fully self-gated approach to extract cardiac and respiratory signals directly from the acquired image data, allowing for more efficient coverage in time and space without the need for electrocardiogram gating, triggering, navigators, or breath-holds. This review provides a comprehensive overview of the free-running framework, detailing its history, concepts, recent improvements, and clinical applications.
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Affiliation(s)
- Robert J Holtackers
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, 1011 Lausanne, Switzerland
- Department of Radiology & Nuclear Medicine, Maastricht University Medical Center, P. Debyelaan 25, 6229 HX Maastricht, The Netherlands
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Universiteitssingel 50, 6200 MD Maastricht, The Netherlands
| | - Matthias Stuber
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, 1011 Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), EPFL AVP CP CIBM Station 6, 1015 Lausanne, Switzerland
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Tibrewala R, Brantner D, Brown R, Pancoast L, Keerthivasan M, Bruno M, Block KT, Madore B, Sodickson DK, Collins CM. Preliminary Experience with Three Alternative Motion Sensors for 0.55 Tesla MR Imaging. SENSORS (BASEL, SWITZERLAND) 2024; 24:3710. [PMID: 38931494 PMCID: PMC11207459 DOI: 10.3390/s24123710] [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: 04/09/2024] [Revised: 05/27/2024] [Accepted: 06/05/2024] [Indexed: 06/28/2024]
Abstract
Due to limitations in current motion tracking technologies and increasing interest in alternative sensors for motion tracking both inside and outside the MRI system, in this study we share our preliminary experience with three alternative sensors utilizing diverse technologies and interactions with tissue to monitor motion of the body surface, respiratory-related motion of major organs, and non-respiratory motion of deep-seated organs. These consist of (1) a Pilot-Tone RF transmitter combined with deep learning algorithms for tracking liver motion, (2) a single-channel ultrasound transducer with deep learning for monitoring bladder motion, and (3) a 3D Time-of-Flight camera for observing the motion of the anterior torso surface. Additionally, we demonstrate the capability of these sensors to simultaneously capture motion data outside the MRI environment, which is particularly relevant for procedures like radiation therapy, where motion status could be related to previously characterized cyclical anatomical data. Our findings indicate that the ultrasound sensor can track motion in deep-seated organs (bladder) as well as respiratory-related motion. The Time-of-Flight camera offers ease of interpretation and performs well in detecting surface motion (respiration). The Pilot-Tone demonstrates efficacy in tracking bulk respiratory motion and motion of major organs (liver). Simultaneous use of all three sensors could provide complementary motion information outside the MRI bore, providing potential value for motion tracking during position-sensitive treatments such as radiation therapy.
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Affiliation(s)
- Radhika Tibrewala
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Douglas Brantner
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Ryan Brown
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Leanna Pancoast
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | | | - Mary Bruno
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Kai Tobias Block
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Bruno Madore
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Daniel K. Sodickson
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Christopher M. Collins
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, NY 10016, USA
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Falcão MBL, Mackowiak ALC, Rossi GMC, Prša M, Tenisch E, Rumac S, Bacher M, Rutz T, van Heeswijk RB, Speier P, Markl M, Bastiaansen JAM, Stuber M, Roy CW. Combined free-running four-dimensional anatomical and flow magnetic resonance imaging with native contrast using Synchronization of Neighboring Acquisitions by Physiological Signals. J Cardiovasc Magn Reson 2024; 26:101006. [PMID: 38309581 PMCID: PMC11211232 DOI: 10.1016/j.jocmr.2024.101006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 01/25/2024] [Indexed: 02/05/2024] Open
Abstract
BACKGROUND Four-dimensional (4D) flow magnetic resonance imaging (MRI) often relies on the injection of gadolinium- or iron-oxide-based contrast agents to improve vessel delineation. In this work, a novel technique is developed to acquire and reconstruct 4D flow data with excellent dynamic visualization of blood vessels but without the need for contrast injection. Synchronization of Neighboring Acquisitions by Physiological Signals (SyNAPS) uses pilot tone (PT) navigation to retrospectively synchronize the reconstruction of two free-running three-dimensional radial acquisitions, to create co-registered anatomy and flow images. METHODS Thirteen volunteers and two Marfan syndrome patients were scanned without contrast agent using one free-running fast interrupted steady-state (FISS) sequence and one free-running phase-contrast MRI (PC-MRI) sequence. PT signals spanning the two sequences were recorded for retrospective respiratory motion correction and cardiac binning. The magnitude and phase images reconstructed, respectively, from FISS and PC-MRI, were synchronized to create SyNAPS 4D flow datasets. Conventional two-dimensional (2D) flow data were acquired for reference in ascending (AAo) and descending aorta (DAo). The blood-to-myocardium contrast ratio, dynamic vessel area, net volume, and peak flow were used to compare SyNAPS 4D flow with Native 4D flow (without FISS information) and 2D flow. A score of 0-4 was given to each dataset by two blinded experts regarding the feasibility of performing vessel delineation. RESULTS Blood-to-myocardium contrast ratio for SyNAPS 4D flow magnitude images (1.5 ± 0.3) was significantly higher than for Native 4D flow (0.7 ± 0.1, p < 0.01) and was comparable to 2D flow (2.3 ± 0.9, p = 0.02). Image quality scores of SyNAPS 4D flow from the experts (M.P.: 1.9 ± 0.3, E.T.: 2.5 ± 0.5) were overall significantly higher than the scores from Native 4D flow (M.P.: 1.6 ± 0.6, p = 0.03, E.T.: 0.8 ± 0.4, p < 0.01) but still significantly lower than the scores from the reference 2D flow datasets (M.P.: 2.8 ± 0.4, p < 0.01, E.T.: 3.5 ± 0.7, p < 0.01). The Pearson correlation coefficient between the dynamic vessel area measured on SyNAPS 4D flow and that from 2D flow was 0.69 ± 0.24 for the AAo and 0.83 ± 0.10 for the DAo, whereas the Pearson correlation between Native 4D flow and 2D flow measurements was 0.12 ± 0.48 for the AAo and 0.08 ± 0.39 for the DAo. Linear correlations between SyNAPS 4D flow and 2D flow measurements of net volume (r2 = 0.83) and peak flow (r2 = 0.87) were larger than the correlations between Native 4D flow and 2D flow measurements of net volume (r2 = 0.79) and peak flow (r2 = 0.76). CONCLUSION The feasibility and utility of SyNAPS were demonstrated for joint whole-heart anatomical and flow MRI without requiring electrocardiography gating, respiratory navigators, or contrast agents. Using SyNAPS, a high-contrast anatomical imaging sequence can be used to improve 4D flow measurements that often suffer from poor delineation of vessel boundaries in the absence of contrast agents.
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Affiliation(s)
- Mariana B L Falcão
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Adèle L C Mackowiak
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland; Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland; Translation Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
| | - Giulia M C Rossi
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Milan Prša
- Woman, Mother, Child Department, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Estelle Tenisch
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Simone Rumac
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Mario Bacher
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland; Siemens Healthcare GmbH, Erlangen, Germany
| | - Tobias Rutz
- Service of Cardiology, Centre de Resonance Magnétique Cardiaque (CRMC), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Ruud B van Heeswijk
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | | | - Michael Markl
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA; Department of Biomedical Engineering, Northwestern University, Chicago, Illinois, USA
| | - Jessica A M Bastiaansen
- Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland; Translation Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
| | - Matthias Stuber
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland; Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Christopher W Roy
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
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5
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Pan Y, Varghese J, Tong MS, Yildiz VO, Azzu A, Gatehouse P, Wage R, Nielles-Vallespin S, Pennell DJ, Jin N, Bacher M, Hayes C, Speier P, Simonetti OP. Two-center validation of Pilot Tone based cardiac triggering of a comprehensive cardiovascular magnetic resonance examination. THE INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING 2024; 40:261-273. [PMID: 38082073 DOI: 10.1007/s10554-023-03002-w] [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: 06/28/2023] [Accepted: 10/31/2023] [Indexed: 12/26/2023]
Abstract
The electrocardiogram (ECG) signal is prone to distortions from gradient and radiofrequency interference and the magnetohydrodynamic effect during cardiovascular magnetic resonance imaging (CMR). Although Pilot Tone Cardiac (PTC) triggering has the potential to overcome these limitations, effectiveness across various CMR techniques has yet to be established. To evaluate the performance of PTC triggering in a comprehensive CMR exam. Fifteen volunteers and 20 patients were recruited at two centers. ECG triggered images were collected for comparison in a subset of sequences. The PTC trigger accuracy was evaluated against ECG in cine acquisitions. Two experienced readers scored image quality in PTC-triggered cine, late gadolinium enhancement (LGE), and T1- and T2-weighted dark-blood turbo spin echo (DB-TSE) images. Quantitative cardiac function, flow, and parametric mapping values obtained using PTC and ECG triggered sequences were compared. Breath-held segmented cine used for trigger timing analysis was collected in 15 volunteers and 14 patients. PTC calibration failed in three volunteers and one patient; ECG trigger recording failed in one patient. Out of 1987 total heartbeats, three mismatched trigger PTC-ECG pairs were found. Image quality scores showed no significant difference between PTC and ECG triggering. There was no significant difference found in quantitative measurements in volunteers. In patients, the only significant difference was found in post-contrast T1 (p = 0.04). ICC showed moderate to excellent agreement in all measurements. PTC performance was equivalent to ECG in terms of triggering consistency, image quality, and quantitative image measurements across multiple CMR applications.
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Affiliation(s)
- Yue Pan
- Department of Biomedical Engineering, The Ohio State University, Columbus, OH, USA
- Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Juliet Varghese
- Department of Biomedical Engineering, The Ohio State University, Columbus, OH, USA
- Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Matthew S Tong
- Department of Internal Medicine, Division of Cardiovascular Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Vedat O Yildiz
- Center for Biostatistics, Department of Biomedical Informatics, The Ohio State University College of Medicine, Columbus, OH, USA
| | - Alessia Azzu
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, London, UK
| | - Peter Gatehouse
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, London, UK
| | - Rick Wage
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, London, UK
| | | | - Dudley J Pennell
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, London, UK
| | - Ning Jin
- Cardiovascular MR R&D, Siemens Medical Solutions USA, Malvern, PA, USA
| | - Mario Bacher
- Siemens Healthineers AG, Erlangen, Germany
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | | | | | - Orlando P Simonetti
- Department of Biomedical Engineering, The Ohio State University, Columbus, OH, USA.
- Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
- Department of Internal Medicine, Division of Cardiovascular Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
- Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
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6
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Chen C, Liu Y, Simonetti OP, Tong M, Jin N, Bacher M, Speier P, Ahmad R. Cardiac and respiratory motion extraction for MRI using pilot tone-a patient study. THE INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING 2024; 40:93-105. [PMID: 37874445 PMCID: PMC10842141 DOI: 10.1007/s10554-023-02966-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 09/21/2023] [Indexed: 10/25/2023]
Abstract
This study aims to evaluate the accuracy and reliability of the cardiac and respiratory signals extracted from Pilot Tone (PT) in patients clinically referred for cardiovascular MRI. Twenty-three patients were scanned under free-breathing conditions using a balanced steady-state free-precession real-time (RT) cine sequence on a 1.5T scanner. The PT signal was generated by a built-in PT transmitter integrated within the body array coil, and retrospectively processed to extract respiratory and cardiac signals. For comparison, ECG and BioMatrix (BM) respiratory sensor signals were also synchronously recorded. To assess the performances of PT, ECG, and BM, cardiac and respiratory signals extracted from the RT cine images were used as the ground truth. The respiratory motion extracted from PT correlated positively with the image-derived respiratory signal in all cases and showed a stronger correlation (absolute coefficient: 0.95 ± 0.09) than BM (0.72 ± 0.24). For the cardiac signal, PT trigger jitter (standard deviation of PT trigger locations relative to ECG triggers) ranged from 6.6 to 83.3 ms, with a median of 21.8 ms. The mean absolute difference between the PT and corresponding ECG cardiac cycle duration was less than 5% of the average ECG RR interval for 21 out of 23 patients. We did not observe a significant linear dependence (p > 0.28) of PT delay and PT jitter on the patients' BMI or cardiac cycle duration. This study demonstrates the potential of PT to monitor both respiratory and cardiac motion in patients clinically referred for cardiovascular MRI.
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Affiliation(s)
- Chong Chen
- Department of Biomedical Engineering, The Ohio State University, Columbus, US.
| | - Yingmin Liu
- Davis Heart & Lung Research Institute, The Ohio State University, Columbus, US
| | - Orlando P Simonetti
- Davis Heart & Lung Research Institute, The Ohio State University, Columbus, US
| | - Matthew Tong
- Davis Heart & Lung Research Institute, The Ohio State University, Columbus, US
| | - Ning Jin
- Siemens Medical Solutions USA, Inc, Columbus, US
| | | | | | - Rizwan Ahmad
- Department of Biomedical Engineering, The Ohio State University, Columbus, US
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7
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Bissell MM, Raimondi F, Ait Ali L, Allen BD, Barker AJ, Bolger A, Burris N, Carhäll CJ, Collins JD, Ebbers T, Francois CJ, Frydrychowicz A, Garg P, Geiger J, Ha H, Hennemuth A, Hope MD, Hsiao A, Johnson K, Kozerke S, Ma LE, Markl M, Martins D, Messina M, Oechtering TH, van Ooij P, Rigsby C, Rodriguez-Palomares J, Roest AAW, Roldán-Alzate A, Schnell S, Sotelo J, Stuber M, Syed AB, Töger J, van der Geest R, Westenberg J, Zhong L, Zhong Y, Wieben O, Dyverfeldt P. 4D Flow cardiovascular magnetic resonance consensus statement: 2023 update. J Cardiovasc Magn Reson 2023; 25:40. [PMID: 37474977 PMCID: PMC10357639 DOI: 10.1186/s12968-023-00942-z] [Citation(s) in RCA: 54] [Impact Index Per Article: 54.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 05/30/2023] [Indexed: 07/22/2023] Open
Abstract
Hemodynamic assessment is an integral part of the diagnosis and management of cardiovascular disease. Four-dimensional cardiovascular magnetic resonance flow imaging (4D Flow CMR) allows comprehensive and accurate assessment of flow in a single acquisition. This consensus paper is an update from the 2015 '4D Flow CMR Consensus Statement'. We elaborate on 4D Flow CMR sequence options and imaging considerations. The document aims to assist centers starting out with 4D Flow CMR of the heart and great vessels with advice on acquisition parameters, post-processing workflows and integration into clinical practice. Furthermore, we define minimum quality assurance and validation standards for clinical centers. We also address the challenges faced in quality assurance and validation in the research setting. We also include a checklist for recommended publication standards, specifically for 4D Flow CMR. Finally, we discuss the current limitations and the future of 4D Flow CMR. This updated consensus paper will further facilitate widespread adoption of 4D Flow CMR in the clinical workflow across the globe and aid consistently high-quality publication standards.
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Affiliation(s)
- Malenka M Bissell
- Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM), LIGHT Laboratories, Clarendon Way, University of Leeds, Leeds, LS2 9NL, UK.
| | | | - Lamia Ait Ali
- Institute of Clinical Physiology CNR, Massa, Italy
- Foundation CNR Tuscany Region G. Monasterio, Massa, Italy
| | - Bradley D Allen
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Alex J Barker
- Department of Radiology, Children's Hospital Colorado, University of Colorado Anschutz Medical Center, Aurora, USA
| | - Ann Bolger
- Department of Medicine, University of California, San Francisco, CA, USA
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Nicholas Burris
- Department of Radiology, University of Michigan, Ann Arbor, USA
| | - Carl-Johan Carhäll
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
| | | | - Tino Ebbers
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
| | | | - Alex Frydrychowicz
- Department of Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein, Campus Lübeck and Universität Zu Lübeck, Lübeck, Germany
| | - Pankaj Garg
- Norwich Medical School, University of East Anglia, Norwich, UK
| | - Julia Geiger
- Department of Diagnostic Imaging, University Children's Hospital, Zurich, Switzerland
- Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
| | - Hojin Ha
- Department of Mechanical and Biomedical Engineering, Kangwon National University, Chuncheon, South Korea
| | - Anja Hennemuth
- Institute of Computer-Assisted Cardiovascular Medicine, Charité - Universitätsmedizin, Berlin, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site, Berlin, Germany
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Michael D Hope
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Albert Hsiao
- Department of Radiology, University of California, San Diego, CA, USA
| | - Kevin Johnson
- Departments of Radiology and Medical Physics, University of Wisconsin, Madison, WI, USA
| | - Sebastian Kozerke
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Liliana E Ma
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Michael Markl
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Duarte Martins
- Department of Pediatric Cardiology, Hospital de Santa Cruz, Centro Hospitalar Lisboa Ocidental, Lisbon, Portugal
| | - Marci Messina
- Department of Radiology, Northwestern Medicine, Chicago, IL, USA
| | - Thekla H Oechtering
- Department of Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein, Campus Lübeck and Universität Zu Lübeck, Lübeck, Germany
- Departments of Radiology and Medical Physics, University of Wisconsin, Madison, WI, USA
| | - Pim van Ooij
- Department of Radiology & Nuclear Medicine, Amsterdam Cardiovascular Sciences, Amsterdam Movement Sciences, Amsterdam University Medical Centers, Location AMC, Amsterdam, The Netherlands
- Department of Pediatric Cardiology, Division of Pediatrics, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Cynthia Rigsby
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Medical Imaging, Ann & Robert H Lurie Children's Hospital of Chicago, Chicago, IL, USA
| | - Jose Rodriguez-Palomares
- Department of Cardiology, Hospital Universitari Vall d´Hebron,Vall d'Hebron Institut de Recerca (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red-CV, CIBER CV, Madrid, Spain
| | - Arno A W Roest
- Department of Pediatric Cardiology, Willem-Alexander's Children Hospital, Leiden University Medical Center and Center for Congenital Heart Defects Amsterdam-Leiden, Leiden, The Netherlands
| | | | - Susanne Schnell
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Medical Physics, Institute of Physics, University of Greifswald, Greifswald, Germany
| | - Julio Sotelo
- School of Biomedical Engineering, Universidad de Valparaíso, Valparaíso, Chile
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Millennium Institute for Intelligent Healthcare Engineering - iHEALTH, Santiago, Chile
| | - Matthias Stuber
- Département de Radiologie Médicale, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
| | - Ali B Syed
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Johannes Töger
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden
| | - Rob van der Geest
- Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Jos Westenberg
- CardioVascular Imaging Group (CVIG), Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Liang Zhong
- National Heart Centre Singapore, Duke-NUS Medical School, National University of Singapore, Singapore, Singapore
| | - Yumin Zhong
- Department of Radiology, School of Medicine, Shanghai Children's Medical Center Affiliated With Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Oliver Wieben
- Departments of Radiology and Medical Physics, University of Wisconsin, Madison, WI, USA
| | - Petter Dyverfeldt
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
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8
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Pan Y, Varghese J, Tong MS, Yildiz VO, Azzu A, Gatehouse P, Wage R, Nielles-Vallespin S, Pennell D, Jin N, Bacher M, Hayes C, Speier P, Simonetti OP. Two-center validation of Pilot Tone Based Cardiac Triggering of a Comprehensive Cardiovascular Magnetic Resonance Examination. RESEARCH SQUARE 2023:rs.3.rs-3121723. [PMID: 37461505 PMCID: PMC10350216 DOI: 10.21203/rs.3.rs-3121723/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/28/2023]
Abstract
Background The electrocardiogram (ECG) signal is prone to distortions from gradient and radiofrequency interference and the magnetohydrodynamic effect during cardiovascular magnetic resonance imaging (CMR). Although Pilot Tone Cardiac (PTC) triggering has the potential to overcome these limitations, effectiveness across various CMR techniques has yet to be established. Purpose To evaluate the performance of PTC triggering in a comprehensive CMR exam. Methods Fifteen volunteers and twenty patients were recruited at two centers. ECG triggered images were collected for comparison in a subset of sequences. The PTC trigger accuracy was evaluated against ECG in cine acquisitions. Two experienced readers scored image quality in PTC-triggered cine, late gadolinium enhancement (LGE), and T1- and T2-weighted dark-blood turbo spin echo (DB-TSE) images. Quantitative cardiac function, flow, and parametric mapping values obtained using PTC and ECG triggered sequences were compared. Results Breath-held segmented cine used for trigger timing analysis was collected in 15 volunteers and 14 patients. PTC calibration failed in three volunteers and one patient; ECG trigger recording failed in one patient. Out of 1987 total heartbeats, three mismatched trigger PTC-ECG pairs were found. Image quality scores showed no significant difference between PTC and ECG triggering. There was no significant difference found in quantitative measurements in volunteers. In patients, the only significant difference was found in post-contrast T1 (p = 0.04). ICC showed moderate to excellent agreement in all measurements. Conclusion PTC performance was equivalent to ECG in terms of triggering consistency, image quality, and quantitative image measurements across multiple CMR applications.
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Falcão MBL, Rossi GMC, Rutz T, Prša M, Tenisch E, Ma L, Weiss EK, Baraboo JJ, Yerly J, Markl M, Stuber M, Roy CW. Focused navigation for respiratory-motion-corrected free-running radial 4D flow MRI. Magn Reson Med 2023; 90:117-132. [PMID: 36877140 PMCID: PMC10149606 DOI: 10.1002/mrm.29634] [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: 08/25/2022] [Revised: 02/21/2023] [Accepted: 02/21/2023] [Indexed: 03/07/2023]
Abstract
PURPOSE To validate a respiratory motion correction method called focused navigation (fNAV) for free-running radial whole-heart 4D flow MRI. METHODS Using fNAV, respiratory signals derived from radial readouts are converted into three orthogonal displacements, which are then used to correct respiratory motion in 4D flow datasets. Hundred 4D flow acquisitions were simulated with non-rigid respiratory motion and used for validation. The difference between generated and fNAV displacement coefficients was calculated. Vessel area and flow measurements from 4D flow reconstructions with (fNAV) and without (uncorrected) motion correction were compared to the motion-free ground-truth. In 25 patients, the same measurements were compared between fNAV 4D flow, 2D flow, navigator-gated Cartesian 4D flow, and uncorrected 4D flow datasets. RESULTS For simulated data, the average difference between generated and fNAV displacement coefficients was 0.04± $$ \pm $$ 0.32 mm and 0.31± $$ \pm $$ 0.35 mm in the x and y directions, respectively. In the z direction, this difference was region-dependent (0.02± $$ \pm $$ 0.51 mm up to 5.85± $$ \pm $$ 3.41 mm). For all measurements (vessel area, net volume, and peak flow), the average difference from ground truth was higher for uncorrected 4D flow datasets (0.32± $$ \pm $$ 0.11 cm2 , 11.1± $$ \pm $$ 3.5 mL, and 22.3± $$ \pm $$ 6.0 mL/s) than for fNAV 4D flow datasets (0.10± $$ \pm $$ 0.03 cm2 , 2.6± $$ \pm $$ 0.7 mL, and 5.1± 0 $$ \pm 0 $$ .9 mL/s, p < 0.05). In vivo, average vessel area measurements were 4.92± $$ \pm $$ 2.95 cm2 , 5.06± $$ \pm $$ 2.64 cm2 , 4.87± $$ \pm $$ 2.57 cm2 , 4.87± $$ \pm $$ 2.69 cm2 , for 2D flow and fNAV, navigator-gated and uncorrected 4D flow datasets, respectively. In the ascending aorta, all 4D flow datasets except for the fNAV reconstruction had significantly different vessel area measurements from 2D flow. Overall, 2D flow datasets demonstrated the strongest correlation to fNAV 4D flow for both net volume (r2 = 0.92) and peak flow (r2 = 0.94), followed by navigator-gated 4D flow (r2 = 0.83 and r2 = 0.86, respectively), and uncorrected 4D flow (r2 = 0.69 and r2 = 0.86, respectively). CONCLUSION fNAV corrected respiratory motion in vitro and in vivo, resulting in fNAV 4D flow measurements that are comparable to those derived from 2D flow and navigator-gated Cartesian 4D flow datasets, with improvements over those from uncorrected 4D flow.
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Affiliation(s)
- Mariana B. L. Falcão
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Giulia M. C. Rossi
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Tobias Rutz
- Service of Cardiology, Centre de Resonance Magnétique Cardiaque (CRMC), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Milan Prša
- Woman-Mother-Child Department, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Estelle Tenisch
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Liliana Ma
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois USA
- Department of Biomedical Engineering, Northwestern University, Chicago, Illinois USA
| | - Elizabeth K. Weiss
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois USA
- Department of Biomedical Engineering, Northwestern University, Chicago, Illinois USA
| | - Justin J. Baraboo
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois USA
- Department of Biomedical Engineering, Northwestern University, Chicago, Illinois USA
| | - Jérôme Yerly
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Michael Markl
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois USA
- Department of Biomedical Engineering, Northwestern University, Chicago, Illinois USA
| | - Matthias Stuber
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Christopher W. Roy
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
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10
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Madore B, Hess AT, van Niekerk AMJ, Hoinkiss DC, Hucker P, Zaitsev M, Afacan O, Günther M. External Hardware and Sensors, for Improved MRI. J Magn Reson Imaging 2023; 57:690-705. [PMID: 36326548 PMCID: PMC9957809 DOI: 10.1002/jmri.28472] [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: 07/27/2022] [Revised: 09/26/2022] [Accepted: 09/27/2022] [Indexed: 11/06/2022] Open
Abstract
Complex engineered systems are often equipped with suites of sensors and ancillary devices that monitor their performance and maintenance needs. MRI scanners are no different in this regard. Some of the ancillary devices available to support MRI equipment, the ones of particular interest here, have the distinction of actually participating in the image acquisition process itself. Most commonly, such devices are used to monitor physiological motion or variations in the scanner's imaging fields, allowing the imaging and/or reconstruction process to adapt as imaging conditions change. "Classic" examples include electrocardiography (ECG) leads and respiratory bellows to monitor cardiac and respiratory motion, which have been standard equipment in scan rooms since the early days of MRI. Since then, many additional sensors and devices have been proposed to support MRI acquisitions. The main physical properties that they measure may be primarily "mechanical" (eg acceleration, speed, and torque), "acoustic" (sound and ultrasound), "optical" (light and infrared), or "electromagnetic" in nature. A review of these ancillary devices, as currently available in clinical and research settings, is presented here. In our opinion, these devices are not in competition with each other: as long as they provide useful and unique information, do not interfere with each other and are not prohibitively cumbersome to use, they might find their proper place in future suites of sensors. In time, MRI acquisitions will likely include a plurality of complementary signals. A little like the microbiome that provides genetic diversity to organisms, these devices can provide signal diversity to MRI acquisitions and enrich measurements. Machine-learning (ML) algorithms are well suited at combining diverse input signals toward coherent outputs, and they could make use of all such information toward improved MRI capabilities. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Bruno Madore
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Aaron T Hess
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Adam MJ van Niekerk
- Karolinska Institutet, Solna, Sweden
- Norwegian University of Science and Technology, Trondheim, Norway
| | | | - Patrick Hucker
- Division of Medical Physics, Department of Diagnostic and Interventional Radiology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Maxim Zaitsev
- Division of Medical Physics, Department of Diagnostic and Interventional Radiology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Onur Afacan
- Computational Radiology Laboratory, Department of Radiology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Matthias Günther
- Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany
- University Bremen, Bremen, Germany
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11
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Lin K, Sarnari R, Speier P, Hayes C, Davids R, Carr JC, Markl M. Pilot Tone-Triggered MRI for Quantitative Assessment of Cardiac Function, Motion, and Structure. Invest Radiol 2023; 58:239-243. [PMID: 36070525 PMCID: PMC10016086 DOI: 10.1097/rli.0000000000000922] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE The aim of this study was to test the hypothesis that there are good agreements between cardiac functional and structural indices derived from magnetic resonance imaging (MRI) sequences triggered with pilot tone (PT) and electrocardiogram (ECG). MATERIALS AND METHODS Sixteen healthy volunteers (11 male, age 21-76 years) underwent a cardiac MRI scan. Cine MRI, T1, and T2 mapping were acquired by using PT and ECG triggering. Quantitative measurements, including left and right ventricular end-diastolic volume, end-systolic volume, stroke volume, ejection fraction, longitudinal strain, left ventricular T1 and T2 values, left and right atrial longitudinal strain, and maximal/minimal volumes, were measured. The interclass correlation coefficient, coefficient of variation, and Bland-Altman plots were used to evaluate the agreements between measurements derived by MRI sequences triggered with 2 methods. RESULTS There were no significant differences among end-diastolic volume, end-systolic volume, stroke volume, ejection fraction, left ventricle mass, T1 and T2 values, or longitudinal strains acquired using PT and ECG. There were good agreements and low variations between the levels of these indices acquired with PT and ECG. Interclass correlation coefficients mainly ranged from 0.73 to 0.98. The coefficients of variation ranged from 1.4% to 22.6%. CONCLUSIONS Pilot tone-triggered MRI provides comparable measurements of cardiac function, motion, and structure as ECG-triggered MRI. Pilot tone has the potential to become a backup of ECG gating in cardiovascular imaging.
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Affiliation(s)
- Kai Lin
- Department of Radiology, Northwestern University, Chicago, IL
| | - Roberto Sarnari
- Department of Radiology, Northwestern University, Chicago, IL
| | | | | | | | - James C. Carr
- Department of Radiology, Northwestern University, Chicago, IL
| | - Michael Markl
- Department of Radiology, Northwestern University, Chicago, IL
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12
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Ludwig J, Kerkering KM, Speier P, Schaeffter T, Kolbitsch C. Pilot tone-based prospective correction of respiratory motion for free-breathing myocardial T1 mapping. MAGMA (NEW YORK, N.Y.) 2023; 36:135-150. [PMID: 35921020 PMCID: PMC9992053 DOI: 10.1007/s10334-022-01032-4] [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: 04/19/2022] [Revised: 06/22/2022] [Accepted: 07/10/2022] [Indexed: 11/24/2022]
Abstract
OBJECTIVE To provide respiratory motion correction for free-breathing myocardial T1 mapping using a pilot tone (PT) and a continuous golden-angle radial acquisition. MATERIALS AND METHODS During a 45 s prescan the PT is acquired together with a dynamic sagittal image covering multiple respiratory cycles. From these images, the respiratory heart motion in head-feet and anterior-posterior direction is estimated and two linear models are derived between the PT and heart motion. In the following scan through-plane motion is corrected prospectively with slice tracking based on the PT. In-plane motion is corrected for retrospectively. Our method was evaluated on a motion phantom and 11 healthy subjects. RESULTS Non-motion corrected measurements using a moving phantom showed T1 errors of 14 ± 4% (p < 0.05) compared to a reference measurement. The proposed motion correction approach reduced this error to 3 ± 4% (p < 0.05). In vivo the respiratory motion led to an overestimation of T1 values by 26 ± 31% compared to breathhold T1 maps, which was successfully corrected to an average difference of 3 ± 2% (p < 0.05) between our free-breathing approach and breathhold data. DISCUSSION Our proposed PT-based motion correction approach allows for T1 mapping during free-breathing with the same accuracy as a corresponding breathhold T1 mapping scan.
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Affiliation(s)
- Juliane Ludwig
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Abbestr. 2-12, 10587, Berlin, Germany.
| | - Kirsten Miriam Kerkering
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Abbestr. 2-12, 10587, Berlin, Germany
| | | | - Tobias Schaeffter
- Department of Biomedical Engineering, Technische Universität Berlin, Berlin, Germany
| | - Christoph Kolbitsch
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Abbestr. 2-12, 10587, Berlin, Germany
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13
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Feng L. 4D Golden-Angle Radial MRI at Subsecond Temporal Resolution. NMR IN BIOMEDICINE 2023; 36:e4844. [PMID: 36259951 PMCID: PMC9845193 DOI: 10.1002/nbm.4844] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 09/29/2022] [Accepted: 10/13/2022] [Indexed: 05/14/2023]
Abstract
Intraframe motion blurring, as a major challenge in free-breathing dynamic MRI, can be reduced if high temporal resolution can be achieved. To address this challenge, this work proposes a highly accelerated 4D (3D + time) dynamic MRI framework with subsecond temporal resolution that does not require explicit motion compensation. The method combines standard stack-of-stars golden-angle radial sampling and tailored GRASP-Pro (Golden-angle RAdial Sparse Parallel imaging with imProved performance) reconstruction. Specifically, 4D dynamic MRI acquisition is performed continuously without motion gating or sorting. The k-space centers in stack-of-stars radial data are organized to guide estimation of a temporal basis, with which GRASP-Pro reconstruction is employed to enforce joint low-rank subspace and sparsity constraints. This new basis estimation strategy is the new feature proposed for subspace-based reconstruction in this work to achieve high temporal resolution (e.g., subsecond/3D volume). It does not require sequence modification to acquire additional navigation data, it is compatible with commercially available stack-of-stars sequences, and it does not need an intermediate reconstruction step. The proposed 4D dynamic MRI approach was tested in abdominal motion phantom, free-breathing abdominal MRI, and dynamic contrast-enhanced MRI (DCE-MRI). Our results have shown that GRASP-Pro reconstruction with the new basis estimation strategy enables highly-accelerated 4D dynamic imaging at subsecond temporal resolution (with five spokes or less for each dynamic frame per image slice) for both free-breathing non-DCE-MRI and DCE-MRI. In the abdominal phantom, better image quality with lower root mean square error and higher structural similarity index was achieved using GRASP-Pro compared with standard GRASP. With the ability to acquire each 3D image in less than 1 s, intraframe respiratory blurring can be intrinsically reduced for body applications with our approach, which eliminates the need for explicit motion detection and motion compensation.
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Affiliation(s)
- Li Feng
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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14
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Roy CW, Di Sopra L, Whitehead KK, Piccini D, Yerly J, Heerfordt J, Ghosh RM, Fogel MA, Stuber M. Free-running cardiac and respiratory motion-resolved 5D whole-heart coronary cardiovascular magnetic resonance angiography in pediatric cardiac patients using ferumoxytol. J Cardiovasc Magn Reson 2022; 24:39. [PMID: 35754040 PMCID: PMC9235103 DOI: 10.1186/s12968-022-00871-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 06/10/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Coronary cardiovascular magnetic resonance angiography (CCMRA) of congenital heart disease (CHD) in pediatric patients requires accurate planning, adequate sequence parameter adjustments, lengthy scanning sessions, and significant involvement from highly trained personnel. Anesthesia and intubation are commonplace to minimize movements and control respiration in younger subjects. To address the above concerns and provide a single-click imaging solution, we applied our free-running framework for fully self-gated (SG) free-breathing 5D whole-heart CCMRA to CHD patients after ferumoxytol injection. We tested the hypothesis that spatial and motion resolution suffice to visualize coronary artery ostia in a cohort of CHD subjects, both for intubated and free-breathing acquisitions. METHODS In 18 pediatric CHD patients, non-electrocardiogram (ECG) triggered 5D free-running gradient echo CCMRA with whole-heart 1 mm3 isotropic spatial resolution was performed in seven minutes on a 1.5T CMR scanner. Eleven patients were anesthetized and intubated, while seven were breathing freely without anesthesia. All patients were slowly injected with ferumoxytol (4 mg/kg) over 15 minutes. Cardiac and respiratory motion-resolved 5D images were reconstructed with a fully SG approach. To evaluate the performance of motion resolution, visibility of coronary artery origins was assessed. Intubated and free-breathing patient sub-groups were compared for image quality using coronary artery length and conspicuity as well as lung-liver interface sharpness. RESULTS Data collection using the free-running framework was successful in all patients in less than 8 min; scan planning was very simple without the need for parameter adjustments, while no ECG lead placement and triggering was required. From the resulting SG 5D motion-resolved reconstructed images, coronary artery origins could be retrospectively extracted in 90% of the cases. These general findings applied to both intubated and free-breathing pediatric patients (no difference in terms of lung-liver interface sharpness), while image quality and coronary conspicuity between both cohorts was very similar. CONCLUSIONS A simple-to-use push-button framework for 5D whole-heart CCMRA was successfully employed in pediatric CHD patients with ferumoxytol injection. This approach, working without any external gating and for a wide range of heart rates and body sizes provided excellent definition of cardiac anatomy for both intubated and free-breathing patients.
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Affiliation(s)
- Christopher W. Roy
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-8-84, 1011 Lausanne, Switzerland
| | - Lorenzo Di Sopra
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-8-84, 1011 Lausanne, Switzerland
| | - Kevin K. Whitehead
- Division of Cardiology, Department of Pediatrics, The Children’s Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, USA
| | - Davide Piccini
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-8-84, 1011 Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Jérôme Yerly
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-8-84, 1011 Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - John Heerfordt
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-8-84, 1011 Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Reena M. Ghosh
- Division of Cardiology, Department of Pediatrics, The Children’s Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, USA
| | - Mark A. Fogel
- Division of Cardiology, Department of Pediatrics, The Children’s Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, USA
| | - Matthias Stuber
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-8-84, 1011 Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
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15
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Feng L. Golden-Angle Radial MRI: Basics, Advances, and Applications. J Magn Reson Imaging 2022; 56:45-62. [PMID: 35396897 PMCID: PMC9189059 DOI: 10.1002/jmri.28187] [Citation(s) in RCA: 48] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 03/23/2022] [Accepted: 03/24/2022] [Indexed: 12/21/2022] Open
Abstract
In recent years, golden‐angle radial sampling has received substantial attention and interest in the magnetic resonance imaging (MRI) community, and it has become a popular sampling trajectory for both research and clinical use. However, although the number of relevant techniques and publications has grown rapidly, there is still a lack of a review paper that provides a comprehensive overview and summary of the basics of golden‐angle rotation, the advantages and challenges/limitations of golden‐angle radial sampling, and recommendations in using different types of golden‐angle radial trajectories for MRI applications. Such a review paper is expected to be helpful both for clinicians who are interested in learning the potential benefits of golden‐angle radial sampling and for MRI physicists who are interested in exploring this research direction. The main purpose of this review paper is thus to present an overview and summary about golden‐angle radial MRI sampling. The review consists of three sections. The first section aims to answer basic questions such as: what is a golden angle; how is the golden angle calculated; why is golden‐angle radial sampling useful, and what are its limitations. The second section aims to review more advanced trajectories of golden‐angle radial sampling, including tiny golden‐angle rotation, stack‐of‐stars golden‐angle radial sampling, and three‐dimensional (3D) kooshball golden‐angle radial sampling. Their respective advantages and limitations and potential solutions to address these limitations are also discussed. Finally, the third section reviews MRI applications that can benefit from golden‐angle radial sampling and provides recommendations to readers who are interested in implementing golden‐angle radial trajectories in their MRI studies.
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Affiliation(s)
- Li Feng
- BioMedical Engineering and Imaging Institute (BMEII) and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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16
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Abstract
This special issue of Magnetic Resonance in Medical Sciences features the most recent reviews on 4D Flow MRI. These reviews deal with the current status of the emerging technique of 4D Flow MRI facilitated in various areas that are difficult to obtain with conventional flowmetry. MR signals inherently contain flow velocity information. In previous decades, in vivo blood flow measurement was traditionally performed by 2D methods, such as Doppler ultrasonography and 2D phase-contrast MRI, which have long been regarded as mature techniques in hemodynamic flowmetry. Although 2D velocimetries have many advantages over 4D Flow MRI in terms of cost and accessibility, and provide excellent temporal and in-plane spatial resolutions, they also have some disadvantages. The emerging technology of 4D Flow MRI can overcome the shortcomings of conventional 2D imaging. In recent years, hemodynamic analysis has witnessed significant progress that is primarily attributable to advances in 4D Flow MRI.
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Affiliation(s)
- Yasuo Takehara
- Department of Fundamental Development for Low Invasive Diagnostic Imaging, Nagoya University Graduate School of Medicine
| | - Tetsuro Sekine
- Department of Radiology, Nippon Medical School Musashi Kosugi Hospital
| | - Takayuki Obata
- Applied MRI Research, Department of Molecular Imaging and Theranostics, National Institutes for Quantum Science and Technology
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