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Taso M, Aramendía-Vidaurreta V, Englund EK, Francis S, Franklin S, Madhuranthakam AJ, Martirosian P, Nayak KS, Qin Q, Shao X, Thomas DL, Zun Z, Fernández-Seara MA. Update on state-of-the-art for arterial spin labeling (ASL) human perfusion imaging outside of the brain. Magn Reson Med 2023; 89:1754-1776. [PMID: 36747380 DOI: 10.1002/mrm.29609] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 01/09/2023] [Accepted: 01/16/2023] [Indexed: 02/08/2023]
Abstract
This review article provides an overview of developments for arterial spin labeling (ASL) perfusion imaging in the body (i.e., outside of the brain). It is part of a series of review/recommendation papers from the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group. In this review, we focus on specific challenges and developments tailored for ASL in a variety of body locations. After presenting common challenges, organ-specific reviews of challenges and developments are presented, including kidneys, lungs, heart (myocardium), placenta, eye (retina), liver, pancreas, and muscle, which are regions that have seen the most developments outside of the brain. Summaries and recommendations of acquisition parameters (when appropriate) are provided for each organ. We then explore the possibilities for wider adoption of body ASL based on large standardization efforts, as well as the potential opportunities based on recent advances in high/low-field systems and machine-learning. This review seeks to provide an overview of the current state-of-the-art of ASL for applications in the body, highlighting ongoing challenges and solutions that aim to enable more widespread use of the technique in clinical practice.
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Affiliation(s)
- Manuel Taso
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | | | - Erin K Englund
- Department of Radiology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Susan Francis
- Sir Peter Mansfield Imaging Center, University of Nottingham, Nottingham, UK
| | - Suzanne Franklin
- C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
- Center for Image Sciences, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Ananth J Madhuranthakam
- Department of Radiology, Advanced Imaging Research Center, and Biomedical Engineering, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Petros Martirosian
- Section on Experimental Radiology, Department of Radiology, University Hospital of Tuebingen, Tuebingen, Germany
| | - Krishna S Nayak
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California, USA
| | - Qin Qin
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, Maryland, USA
| | - Xingfeng Shao
- Laboratory of FMRI Technology (LOFT), Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - David L Thomas
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Zungho Zun
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
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Henningsson M, Carlhäll CJ, Ebbers T, Kihlberg J. Non-contrast myocardial perfusion in rest and exercise stress using systolic flow-sensitive alternating inversion recovery. MAGMA (NEW YORK, N.Y.) 2022; 35:711-718. [PMID: 34958438 PMCID: PMC9463284 DOI: 10.1007/s10334-021-00992-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 11/19/2021] [Accepted: 12/13/2021] [Indexed: 06/14/2023]
Abstract
OBJECTIVE To evaluate systolic flow-sensitive alternating inversion recovery (FAIR) during rest and exercise stress using 2RR (two cardiac cycles) or 1RR intervals between inversion pulse and imaging. MATERIALS AND METHODS 1RR and 2RR FAIR was implemented on a 3T scanner. Ten healthy subjects were scanned during rest and stress. Stress was performed using an in-bore ergometer. Heart rate, mean myocardial blood flow (MBF) and temporal signal-to-noise ratio (TSNR) were compared using paired t tests. RESULTS Mean heart rate during stress was higher than rest for 1RR FAIR (85.8 ± 13.7 bpm vs 63.3 ± 11.1 bpm; p < 0.01) and 2RR FAIR (83.8 ± 14.2 bpm vs 63.1 ± 10.6 bpm; p < 0.01). Mean stress MBF was higher than rest for 1RR FAIR (2.97 ± 0.76 ml/g/min vs 1.43 ± 0.6 ml/g/min; p < 0.01) and 2RR FAIR (2.8 ± 0.96 ml/g/min vs 1.22 ± 0.59 ml/g/min; p < 0.01). Resting mean MBF was higher for 1RR FAIR than 2RR FAIR (p < 0.05), but not during stress. TSNR was lower for stress compared to rest for 1RR FAIR (4.52 ± 2.54 vs 10.12 ± 3.69; p < 0.01) and 2RR FAIR (7.36 ± 3.78 vs 12.41 ± 5.12; p < 0.01). 2RR FAIR TSNR was higher than 1RR FAIR for rest (p < 0.05) and stress (p < 0.001). DISCUSSION We have demonstrated feasibility of systolic FAIR in rest and exercise stress. 2RR delay systolic FAIR enables non-contrast perfusion assessment during stress with relatively high TSNR.
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Affiliation(s)
- Markus Henningsson
- Unit of Cardiovascular Sciences, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
| | - Carl-Johan Carlhäll
- Unit of Cardiovascular Sciences, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
- Department of Clinical Physiology in Linköping, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Tino Ebbers
- Unit of Cardiovascular Sciences, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
| | - Johan Kihlberg
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
- Department of Radiology, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
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Emrich T, Halfmann M, Schoepf UJ, Kreitner KF. CMR for myocardial characterization in ischemic heart disease: state-of-the-art and future developments. Eur Radiol Exp 2021; 5:14. [PMID: 33763757 PMCID: PMC7990980 DOI: 10.1186/s41747-021-00208-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 01/22/2021] [Indexed: 01/25/2023] Open
Abstract
Ischemic heart disease and its sequelae are one of the major contributors to morbidity and mortality worldwide. Over the last decades, technological developments have strengthened the role of noninvasive imaging for detection, risk stratification, and management of patients with ischemic heart disease. Cardiac magnetic resonance (CMR) imaging incorporates both functional and morphological characterization of the heart to determine presence, acuteness, and severity of ischemic heart disease by evaluating myocardial wall motion and function, the presence and extent of myocardial edema, ischemia, and scarring. Currently established clinical protocols have already demonstrated their diagnostic and prognostic value. Nevertheless, there are emerging imaging technologies that provide additional information based on advanced quantification of imaging biomarkers and improved diagnostic accuracy, therefore potentially allowing reduction or avoidance of contrast and/or stressor agents. The aim of this review is to summarize the current state of the art of CMR imaging for ischemic heart disease and to provide insights into promising future developments.
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Affiliation(s)
- Tilman Emrich
- Department of Diagnostic and Interventional Radiology, University Medical Center, Mainz; Langenbeckstraße 1, 55131, Mainz, Germany. .,German Center for Cardiovascular Research (DZHK), Partner Site Rhine Main, Mainz, Langenbeckstraße 1, 55131, Mainz, Germany. .,Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, 29425, USA.
| | - Moritz Halfmann
- Department of Diagnostic and Interventional Radiology, University Medical Center, Mainz; Langenbeckstraße 1, 55131, Mainz, Germany.,German Center for Cardiovascular Research (DZHK), Partner Site Rhine Main, Mainz, Langenbeckstraße 1, 55131, Mainz, Germany
| | - U Joseph Schoepf
- Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, 29425, USA
| | - Karl-Friedrich Kreitner
- Department of Diagnostic and Interventional Radiology, University Medical Center, Mainz; Langenbeckstraße 1, 55131, Mainz, Germany
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Henningsson M, Carlhäll C, Kihlberg J. Myocardial arterial spin labeling in systole and diastole using flow-sensitive alternating inversion recovery with parallel imaging and compressed sensing. NMR IN BIOMEDICINE 2021; 34:e4436. [PMID: 33150707 PMCID: PMC7816237 DOI: 10.1002/nbm.4436] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Revised: 10/08/2020] [Accepted: 10/08/2020] [Indexed: 06/11/2023]
Abstract
Quantitative myocardial perfusion can be achieved without contrast agents using flow-sensitive alternating inversion recovery (FAIR) arterial spin labeling. However, FAIR has an intrinsically low sensitivity, which may be improved by mitigating the effects of physiological noise or by increasing the area of artifact-free myocardium. The aim of this study was to investigate if systolic FAIR may increase the amount of analyzable myocardium compared with diastolic FAIR and its effect on physiological noise. Furthermore, we compare parallel imaging acceleration with a factor of 2 with compressed sensing acceleration with a factor of 3 for systolic FAIR. Twelve healthy subjects were scanned during rest on a 3 T scanner using diastolic FAIR with parallel imaging factor 2 (FAIR-PI2D ), systolic FAIR with the same acceleration (FAIR-PI2S ) and systolic FAIR with compressed sensing factor 3 (FAIR-CS3S ). The number of analyzable pixels in the myocardium, temporal signal-to-noise ratio (TSNR) and mean myocardial blood flow (MBF) were calculated for all methods. The number of analyzable pixels using FAIR-CS3S (663 ± 55) and FAIR-PI2S (671 ± 58) was significantly higher than for FAIR-PI2D (507 ± 82; P = .001 for both), while there was no significant difference between FAIR-PI2S and FAIR-CS3S . The mean TSNR of the midventricular slice for FAIR-PI2D was 11.4 ± 3.9, similar to that of FAIR-CS3S, which was 11.0 ± 3.3, both considerably higher than for FAIR-PI2S, which was 8.4 ± 3.1 (P < .05 for both). Mean MBF was similar for all three methods. The use of compressed sensing accelerated systolic FAIR benefits from an increased number of analyzable myocardial pixels compared with diastolic FAIR without suffering from a TSNR penalty, unlike systolic FAIR with parallel imaging acceleration.
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Affiliation(s)
- Markus Henningsson
- Unit for Cardiovascular Sciences, Department of Health, Medicine and Caring SciencesLinköping UniversityLinköpingSweden
- Center for Medical Image Science and Visualization (CMIV)Linköping UniversityLinköpingSweden
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Carl‐Johan Carlhäll
- Unit for Cardiovascular Sciences, Department of Health, Medicine and Caring SciencesLinköping UniversityLinköpingSweden
- Center for Medical Image Science and Visualization (CMIV)Linköping UniversityLinköpingSweden
- Department of Clinical Physiology in Linköping, Department of Health, Medicine and Caring SciencesLinköping UniversityLinköpingSweden
| | - Johan Kihlberg
- Center for Medical Image Science and Visualization (CMIV)Linköping UniversityLinköpingSweden
- Department of Radiology, Department of Health, Medicine and Caring SciencesLinköping UniversityLinköpingSweden
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Lobos RA, Hoge WS, Javed A, Liao C, Setsompop K, Nayak KS, Haldar JP. Robust autocalibrated structured low-rank EPI ghost correction. Magn Reson Med 2020; 85:3403-3419. [PMID: 33332652 DOI: 10.1002/mrm.28638] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 11/12/2020] [Accepted: 11/16/2020] [Indexed: 12/16/2022]
Abstract
PURPOSE We propose and evaluate a new structured low-rank method for echo-planar imaging (EPI) ghost correction called Robust Autocalibrated LORAKS (RAC-LORAKS). The method can be used to suppress EPI ghosts arising from the differences between different readout gradient polarities and/or the differences between different shots. It does not require conventional EPI navigator signals, and is robust to imperfect autocalibration data. METHODS Autocalibrated LORAKS is a previous structured low-rank method for EPI ghost correction that uses GRAPPA-type autocalibration data to enable high-quality ghost correction. This method works well when the autocalibration data are pristine, but performance degrades substantially when the autocalibration information is imperfect. RAC-LORAKS generalizes Autocalibrated LORAKS in two ways. First, it does not completely trust the information from autocalibration data, and instead considers the autocalibration and EPI data simultaneously when estimating low-rank matrix structure. Second, it uses complementary information from the autocalibration data to improve EPI reconstruction in a multi-contrast joint reconstruction framework. RAC-LORAKS is evaluated using simulations and in vivo data, including comparisons to state-of-the-art methods. RESULTS RAC-LORAKS is demonstrated to have good ghost elimination performance compared to state-of-the-art methods in several complicated EPI acquisition scenarios (including gradient-echo brain imaging, diffusion-encoded brain imaging, and cardiac imaging). CONCLUSIONS RAC-LORAKS provides effective suppression of EPI ghosts and is robust to imperfect autocalibration data.
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Affiliation(s)
- Rodrigo A Lobos
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA.,Signal and Image Processing Institute, University of Southern California, Los Angeles, CA, USA
| | - W Scott Hoge
- Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Ahsan Javed
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA.,Signal and Image Processing Institute, University of Southern California, Los Angeles, CA, USA
| | - Congyu Liao
- Department of Radiology, Harvard Medical School, Boston, MA, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Kawin Setsompop
- Department of Radiology, Harvard Medical School, Boston, MA, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Krishna S Nayak
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA.,Signal and Image Processing Institute, University of Southern California, Los Angeles, CA, USA.,Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA
| | - Justin P Haldar
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA.,Signal and Image Processing Institute, University of Southern California, Los Angeles, CA, USA.,Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA
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