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Demirel OB, Yaman B, Shenoy C, Moeller S, Weingärtner S, Akçakaya M. Signal intensity informed multi-coil encoding operator for physics-guided deep learning reconstruction of highly accelerated myocardial perfusion CMR. Magn Reson Med 2023; 89:308-321. [PMID: 36128896 PMCID: PMC9617789 DOI: 10.1002/mrm.29453] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 07/21/2022] [Accepted: 08/21/2022] [Indexed: 01/11/2023]
Abstract
PURPOSE To develop a physics-guided deep learning (PG-DL) reconstruction strategy based on a signal intensity informed multi-coil (SIIM) encoding operator for highly-accelerated simultaneous multislice (SMS) myocardial perfusion cardiac MRI (CMR). METHODS First-pass perfusion CMR acquires highly-accelerated images with dynamically varying signal intensity/SNR following the administration of a gadolinium-based contrast agent. Thus, using PG-DL reconstruction with a conventional multi-coil encoding operator leads to analogous signal intensity variations across different time-frames at the network output, creating difficulties in generalization for varying SNR levels. We propose to use a SIIM encoding operator to capture the signal intensity/SNR variations across time-frames in a reformulated encoding operator. This leads to a more uniform/flat contrast at the output of the PG-DL network, facilitating generalizability across time-frames. PG-DL reconstruction with the proposed SIIM encoding operator is compared to PG-DL with conventional encoding operator, split slice-GRAPPA, locally low-rank (LLR) regularized reconstruction, low-rank plus sparse (L + S) reconstruction, and regularized ROCK-SPIRiT. RESULTS Results on highly accelerated free-breathing first pass myocardial perfusion CMR at three-fold SMS and four-fold in-plane acceleration show that the proposed method improves upon the reconstruction methods use for comparison. Substantial noise reduction is achieved compared to split slice-GRAPPA, and aliasing artifacts reduction compared to LLR regularized reconstruction, L + S reconstruction and PG-DL with conventional encoding. Furthermore, a qualitative reader study indicated that proposed method outperformed all methods. CONCLUSION PG-DL reconstruction with the proposed SIIM encoding operator improves generalization across different time-frames /SNRs in highly accelerated perfusion CMR.
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Affiliation(s)
- Omer Burak Demirel
- Department of Electrical and Computer EngineeringUniversity of MinnesotaMinneapolisMinnesotaUSA,Center for Magnetic Resonance ResearchUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Burhaneddin Yaman
- Department of Electrical and Computer EngineeringUniversity of MinnesotaMinneapolisMinnesotaUSA,Center for Magnetic Resonance ResearchUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Chetan Shenoy
- Department of Medicine (Cardiology)University of MinnesotaMinneapolisMinnesotaUSA
| | - Steen Moeller
- Center for Magnetic Resonance ResearchUniversity of MinnesotaMinneapolisMinnesotaUSA
| | | | - Mehmet Akçakaya
- Department of Electrical and Computer EngineeringUniversity of MinnesotaMinneapolisMinnesotaUSA,Center for Magnetic Resonance ResearchUniversity of MinnesotaMinneapolisMinnesotaUSA
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2
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Li X, Feng R, Xiao F, Yin Y, Cao D, Wu X, Zhu S, Wang W. Sparse reconstruction of magnetic resonance image combined with two-step iteration and adaptive shrinkage factor. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2022; 19:13214-13226. [PMID: 36654043 DOI: 10.3934/mbe.2022618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
As an advanced technique, compressed sensing has been used for rapid magnetic resonance imaging in recent years, Two-step Iterative Shrinkage Thresholding Algorithm (TwIST) is a popular algorithm based on Iterative Thresholding Shrinkage Algorithm (ISTA) for fast MR image reconstruction. However TwIST algorithms cannot dynamically adjust shrinkage factor according to the degree of convergence. So it is difficult to balance speed and efficiency. In this paper, we proposed an algorithm which can dynamically adjust the shrinkage factor to rebalance the fidelity item and regular item during TwIST iterative process. The shrinkage factor adjusting is judged by the previous reconstructed results throughout the iteration cycle. It can greatly accelerate the iterative convergence while ensuring convergence accuracy. We used MR images with 2 body parts and different sampling rates to simulate, the results proved that the proposed algorithm have a faster convergence rate and better reconstruction performance. We also used 60 MR images of different body parts for further simulation, and the results proved the universal superiority of the proposed algorithm.
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Affiliation(s)
- Xiuhan Li
- Key Laboratory of Clinical Engineering, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing 211166, China
| | - Rui Feng
- Key Laboratory of Clinical Engineering, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing 211166, China
| | - Funan Xiao
- Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China
| | - Yue Yin
- Department of Medical Engineering, Jiangbei Branch of Zhongda Hospital Affiliated to Southeast University, Nanjing 210044, China
| | - Da Cao
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Xiaoling Wu
- Key Laboratory of Clinical Engineering, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing 211166, China
| | - Songsheng Zhu
- Key Laboratory of Clinical Engineering, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing 211166, China
| | - Wei Wang
- Key Laboratory of Clinical Engineering, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing 211166, China
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3
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Wang J, Weller DS, Kramer CM, Salerno M. DEep learning-based rapid Spiral Image REconstruction (DESIRE) for high-resolution spiral first-pass myocardial perfusion imaging. NMR IN BIOMEDICINE 2022; 35:e4661. [PMID: 34939246 DOI: 10.1002/nbm.4661] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 11/01/2021] [Accepted: 11/16/2021] [Indexed: 06/14/2023]
Abstract
The objective of the current study was to develop and evaluate a DEep learning-based rapid Spiral Image REconstruction (DESIRE) technique for high-resolution spiral first-pass myocardial perfusion imaging with whole-heart coverage, to provide fast and accurate image reconstruction for both single-slice (SS) and simultaneous multislice (SMS) acquisitions. Three-dimensional U-Net-based image enhancement architectures were evaluated for high-resolution spiral perfusion imaging at 3 T. The SS and SMS MB = 2 networks were trained on SS perfusion images from 156 slices from 20 subjects. Structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and normalized root mean square error (NRMSE) were assessed, and prospective images were blindly graded by two experienced cardiologists (5: excellent; 1: poor). Excellent performance was demonstrated for the proposed technique. For SS, SSIM, PSNR, and NRMSE were 0.977 [0.972, 0.982], 42.113 [40.174, 43.493] dB, and 0.102 [0.080, 0.125], respectively, for the best network. For SMS MB = 2 retrospective data, SSIM, PSNR, and NRMSE were 0.961 [0.950, 0.969], 40.834 [39.619, 42.004] dB, and 0.107 [0.086, 0.133], respectively, for the best network. The image quality scores were 4.5 [4.1, 4.8], 4.5 [4.3, 4.6], 3.5 [3.3, 4], and 3.5 [3.3, 3.8] for SS DESIRE, SS L1-SPIRiT, MB = 2 DESIRE, and MB = 2 SMS-slice-L1-SPIRiT, respectively, showing no statistically significant difference (p = 1 and p = 1 for SS and SMS, respectively) between L1-SPIRiT and the proposed DESIRE technique. The network inference time was ~100 ms per dynamic perfusion series with DESIRE, while the reconstruction time of L1-SPIRiT with GPU acceleration was ~ 30 min. It was concluded that DESIRE enabled fast and high-quality image reconstruction for both SS and SMS MB = 2 whole-heart high-resolution spiral perfusion imaging.
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Affiliation(s)
- Junyu Wang
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Daniel S Weller
- Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Christopher M Kramer
- Department of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia, USA
- Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Michael Salerno
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
- Department of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia, USA
- Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
- Departments of Medicine and Radiology, Stanford University Medical Center, Stanford, California, USA
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4
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Zhou R, Wang J, Weller DS, Yang Y, Mugler JP, Salerno M. Free-breathing self-gated continuous-IR spiral T1 mapping: Comparison of dual flip-angle and Bloch-Siegert B1-corrected techniques. Magn Reson Med 2022; 88:1068-1080. [PMID: 35481596 PMCID: PMC9325422 DOI: 10.1002/mrm.29269] [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: 08/31/2021] [Revised: 03/23/2022] [Accepted: 03/25/2022] [Indexed: 11/12/2022]
Abstract
Purpose To develop a B1‐corrrected single flip‐angle continuous acquisition strategy with free‐breathing and cardiac self‐gating for spiral T1 mapping, and compare it to a previous dual flip‐angle technique. Methods Data were continuously acquired using a spiral‐out trajectory, rotated by the golden angle in time. During the first 2 s, off‐resonance Fermi RF pulses were applied to generate a Bloch‐Siegert shift B1 map, and the subsequent data were acquired with an inversion RF pulse applied every 4 s to create a T1* map. The final T1 map was generated from the B1 and the T1* maps by using a look‐up table that accounted for slice profile effects, yielding more accurate T1 values. T1 values were compared to those from inversion recovery (IR) spin echo (phantom only), MOLLI, SAturation‐recovery single‐SHot Acquisition (SASHA), and previously proposed dual flip‐angle results. This strategy was evaluated in a phantom and 25 human subjects. Results The proposed technique showed good agreement with IR spin‐echo results in the phantom experiment. For in‐vivo studies, the proposed technique and the previously proposed dual flip‐angle method were more similar to SASHA results than to MOLLI results. Conclusions B1‐corrected single flip‐angle T1 mapping successfully acquired B1 and T1 maps in a free‐breathing, continuous‐IR spiral acquisition, providing a method with improved accuracy to measure T1 using a continuous Look‐Locker acquisition, as compared to the previously proposed dual excitation flip‐angle technique.
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Affiliation(s)
- Ruixi Zhou
- Department of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China.,Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Junyu Wang
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia, USA
| | | | - Yang Yang
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - John P Mugler
- Radiology & Medical Imaging, Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Michael Salerno
- Department of Medicine, Cardiovascular Medicine and Department of Radiology, Cardiovascular Imaging, Stanford University, Palo Alto, California, USA.,Department of Medicine, Cardiology Division, Radiology and Medical Imaging, and Biomedical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
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5
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Zhou R, Weller DS, Yang Y, Wang J, Jeelani H, Mugler JP, Salerno M. Dual-excitation flip-angle simultaneous cine and T 1 mapping using spiral acquisition with respiratory and cardiac self-gating. Magn Reson Med 2021; 86:82-96. [PMID: 33590591 PMCID: PMC8849625 DOI: 10.1002/mrm.28675] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 12/18/2020] [Accepted: 12/19/2020] [Indexed: 12/26/2022]
Abstract
PURPOSE To develop a free-breathing cardiac self-gated technique that provides cine images and B1+ slice profile-corrected T1 maps from a single acquisition. METHODS Without breath-holding or electrocardiogram gating, data were acquired continuously on a 3T scanner using a golden-angle gradient-echo spiral pulse sequence, with an inversion RF pulse applied every 4 seconds. Flip angles of 3° and 15° were used for readouts after the first four and second four inversions. Self-gating cardiac triggers were extracted from heart image navigators, and respiratory motion was corrected by rigid registration on each heartbeat. Cine images were reconstructed from the steady-state portion of 15° readouts using a low-rank plus sparse reconstruction. The T1 maps were fit using a projection onto convex sets approach from images reconstructed using slice profile-corrected dictionary learning. This strategy was evaluated in a phantom and 14 human subjects. RESULTS The self-gated signal demonstrated close agreement with the acquired electrocardiogram signal. The image quality for the proposed cine images and standard clinical balanced SSFP images were 4.31 (±0.50) and 4.65 (±0.30), respectively. The slice profile-corrected T1 values were similar to those of the inversion-recovery spin-echo technique in phantom, and had a higher global T1 value than that of MOLLI in human subjects. CONCLUSIONS Cine and T1 mapping using spiral acquisition with respiratory and cardiac self-gating successfully acquired T1 maps and cine images in a single acquisition without the need for electrocardiogram gating or breath-holding. This dual-excitation flip-angle approach provides a novel approach for measuring T1 while accounting for B1+ and slice profile effect on the apparent T1∗ .
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Affiliation(s)
- Ruixi Zhou
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, VA, United States
| | - Daniel S. Weller
- Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, United States
| | - Yang Yang
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Junyu Wang
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, VA, United States
| | - Haris Jeelani
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - John P. Mugler
- Radiology & Medical Imaging, Biomedical Engineering, University of Virginia Health System, Charlottesville, VA, United States
| | - Michael Salerno
- Cardiology, Radiology & Medical Imaging, Biomedical Engineering, University of Virginia Health System, Charlottesville, VA, United States
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6
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Hays AG. Editorial for "Diagnostic Accuracy of Spiral Whole-Heart Quantitative Adenosine Stress Cardiac Magnetic Resonance With Motion Compensated L1-SPIRIT". J Magn Reson Imaging 2021; 54:1280-1281. [PMID: 33955105 DOI: 10.1002/jmri.27658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 04/14/2021] [Indexed: 11/10/2022] Open
Affiliation(s)
- Allison G Hays
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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7
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Pan JA, Robinson AA, Yang Y, Lozano PR, McHugh S, Holland EM, Meyer CH, Taylor AM, Kramer CM, Salerno M. Diagnostic Accuracy of Spiral Whole-Heart Quantitative Adenosine Stress Cardiovascular Magnetic Resonance With Motion Compensated L1-SPIRIT. J Magn Reson Imaging 2021; 54:1268-1279. [PMID: 33822426 DOI: 10.1002/jmri.27620] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Revised: 03/16/2021] [Accepted: 03/18/2021] [Indexed: 01/24/2023] Open
Abstract
BACKGROUND Variable density spiral (VDS) pulse sequences with motion compensated compressed sensing (MCCS) reconstruction allow for whole-heart quantitative assessment of myocardial perfusion but are not clinically validated. PURPOSE Assess performance of whole-heart VDS quantitative stress perfusion with MCCS to detect obstructive coronary artery disease (CAD). STUDY TYPE Prospective cross sectional. POPULATION Twenty-five patients with chest pain and known or suspected CAD and nine normal subjects. FIELD STRENGTH/SEQUENCE Segmented steady-state free precession (SSFP) sequence, segmented phase sensitive inversion recovery sequence for late gadolinium enhancement (LGE) imaging and VDS sequence at 1.5 T for rest and stress quantitative perfusion at eight short-axis locations. ASSESSMENT Stenosis was defined as ≥50% by quantitative coronary angiography (QCA). Visual and quantitative analysis of MRI data was compared to QCA. Quantitative analysis assessed average myocardial perfusion reserve (MPR), average stress myocardial blood flow (MBF), and lowest stress MBF of two contiguous myocardial segments. Ischemic burden was measured visually and quantitatively. STATISTICAL TESTS Student's t-test, McNemar's test, chi-square statistic, linear mixed-effects model, and area under receiver-operating characteristic curve (ROC). RESULTS Per-patient visual analysis demonstrated a sensitivity of 84% (95% confidence interval [CI], 60%-97%) and specificity of 83% [95% CI, 36%-100%]. There was no significant difference between per-vessel visual and quantitative analysis for sensitivity (69% [95% CI, 51%-84%] vs. 77% [95% CI, 60%-90%], P = 0.39) and specificity (88% [95% CI, 73%-96%] vs. 80% [95% CI, 64%-91%], P = 0.75). Per-vessel quantitative analysis ROC showed no significant difference (P = 0.06) between average MPR (0.68 [95% CI, 0.56-0.81]), average stress MBF (0.74 [95% CI, 0.63-0.86]), and lowest stress MBF (0.79 [95% CI, 0.69-0.90]). Visual and quantitative ischemic burden measurements were comparable (P = 0.85). DATA CONCLUSION Whole-heart VDS stress perfusion demonstrated good diagnostic accuracy and ischemic burden evaluation. No significant difference was seen between visual and quantitative diagnostic performance and ischemic burden measurements. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Jonathan A Pan
- Cardiovascular Division, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Austin A Robinson
- Division of Cardiovascular Diseases, Division of Radiology, Scripps Clinic, La Jolla, California, USA
| | - Yang Yang
- Cardiovascular Division, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia, USA.,Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Patricia Rodriguez Lozano
- Cardiovascular Division, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Stephen McHugh
- Department of Internal Medicine, Lewis Katz School of Medicine at Temple University, Philadelphia, Pennsylvania, USA
| | - Eric M Holland
- Division of Cardiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Craig H Meyer
- Department of Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA.,Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Angela M Taylor
- Cardiovascular Division, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Christopher M Kramer
- Cardiovascular Division, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia, USA.,Department of Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Michael Salerno
- Cardiovascular Division, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia, USA.,Department of Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA.,Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
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8
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Wang J, Yang Y, Weller DS, Zhou R, Van Houten M, Sun C, Epstein FH, Meyer CH, Kramer CM, Salerno M. High spatial resolution spiral first-pass myocardial perfusion imaging with whole-heart coverage at 3 T. Magn Reson Med 2021; 86:648-662. [PMID: 33709415 DOI: 10.1002/mrm.28701] [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: 08/21/2020] [Revised: 11/16/2020] [Accepted: 01/04/2021] [Indexed: 11/10/2022]
Abstract
PURPOSE To develop and evaluate a high spatial resolution (1.25 × 1.25 mm2 ) spiral first-pass myocardial perfusion imaging technique with whole-heart coverage at 3T, to better assess transmural differences in perfusion between the endocardium and epicardium, to quantify the myocardial ischemic burden, and to improve the detection of obstructive coronary artery disease. METHODS Whole-heart high-resolution spiral perfusion pulse sequences and corresponding motion-compensated reconstruction techniques for both interleaved single-slice (SS) and simultaneous multi-slice (SMS) acquisition with or without outer-volume suppression (OVS) were developed. The proposed techniques were evaluated in 34 healthy volunteers and 8 patients (55 data sets). SS and SMS images were reconstructed using motion-compensated L1-SPIRiT and SMS-Slice-L1-SPIRiT, respectively. Images were blindly graded by 2 experienced cardiologists on a 5-point scale (5, excellent; 1, poor). RESULTS High-quality perfusion imaging was achieved for both SS and SMS acquisitions with or without OVS. The SS technique without OVS had the highest scores (4.5 [4, 5]), which were greater than scores for SS with OVS (3.5 [3.25, 3.75], P < .05), MB = 2 without OVS (3.75 [3.25, 4], P < .05), and MB = 2 with OVS (3.75 [2.75, 4], P < .05), but significantly higher than those for MB = 3 without OVS (4 [4, 4], P = .95). SMS image quality was improved using SMS-Slice-L1-SPIRiT as compared to SMS-L1-SPIRiT (P < .05 for both reviewers). CONCLUSION We demonstrated the successful implementation of whole-heart spiral perfusion imaging with high resolution at 3T. Good image quality was achieved, and the SS without OVS showed the best image quality. Evaluation in patients with expected ischemic heart disease is warranted.
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Affiliation(s)
- Junyu Wang
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Yang Yang
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Daniel S Weller
- Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Ruixi Zhou
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Matthew Van Houten
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Changyu Sun
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Frederick H Epstein
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.,Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Craig H Meyer
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.,Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Christopher M Kramer
- Department of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia, USA.,Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Michael Salerno
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.,Department of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia, USA.,Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
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9
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Fan L, Shen D, Haji-Valizadeh H, Naresh NK, Carr JC, Freed BH, Lee DC, Kim D. Rapid dealiasing of undersampled, non-Cartesian cardiac perfusion images using U-net. NMR IN BIOMEDICINE 2020; 33:e4239. [PMID: 31943431 PMCID: PMC7165063 DOI: 10.1002/nbm.4239] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2019] [Revised: 11/15/2019] [Accepted: 11/18/2019] [Indexed: 05/25/2023]
Abstract
Compressed sensing (CS) is a promising method for accelerating cardiac perfusion MRI to achieve clinically acceptable image quality with high spatial resolution (1.6 × 1.6 × 8 mm3 ) and extensive myocardial coverage (6-8 slices per heartbeat). A major disadvantage of CS is its relatively lengthy processing time (~8 min per slice with 64 frames using a graphics processing unit), thereby making it impractical for clinical translation. The purpose of this study was to implement and test whether an image reconstruction pipeline including a neural network is capable of reconstructing 6.4-fold accelerated, non-Cartesian (radial) cardiac perfusion k-space data at least 10 times faster than CS, without significant loss in image quality. We implemented a 3D (2D + time) U-Net and trained it with 132 2D + time datasets (coil combined, zero filled as input; CS reconstruction as reference) with 64 time frames from 28 patients (8448 2D images in total). For testing, we used 56 2D + time coil-combined, zero-filled datasets (3584 2D images in total) from 12 different patients as input to our trained U-Net, and compared the resulting images with CS reconstructed images using quantitative metrics of image quality and visual scores (conspicuity of wall enhancement, noise, artifacts; each score ranging from 1 (worst) to 5 (best), with 3 defined as clinically acceptable) evaluated by readers. Including pre- and post-processing steps, compared with CS, U-Net significantly reduced the reconstruction time by 14.4-fold (32.1 ± 1.4 s for U-Net versus 461.3 ± 16.9 s for CS, p < 0.001), while maintaining high data fidelity (structural similarity index = 0.914 ± 0.023, normalized root mean square error = 1.7 ± 0.3%, identical mean edge sharpness of 1.2 mm). The median visual summed score was not significantly different (p = 0.053) between CS (14; interquartile range (IQR) = 0.5) and U-Net (12; IQR = 0.5). This study shows that the proposed pipeline with a U-Net is capable of reconstructing 6.4-fold accelerated, non-Cartesian cardiac perfusion k-space data 14.4 times faster than CS, without significant loss in data fidelity or image quality.
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Affiliation(s)
- Lexiaozi Fan
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL
- Department of Biomedical Engineering, Northwestern University, Evanston, IL
| | - Daming Shen
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL
- Department of Biomedical Engineering, Northwestern University, Evanston, IL
| | - Hassan Haji-Valizadeh
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL
- Department of Biomedical Engineering, Northwestern University, Evanston, IL
| | | | - James C. Carr
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Benjamin H. Freed
- Division of Cardiology, Internal Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Daniel C. Lee
- Division of Cardiology, Internal Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Daniel Kim
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL
- Department of Biomedical Engineering, Northwestern University, Evanston, IL
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10
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Kowalik GT, Knight D, Steeden JA, Muthurangu V. Perturbed spiral real-time phase-contrast MR with compressive sensing reconstruction for assessment of flow in children. Magn Reson Med 2019; 83:2077-2091. [PMID: 31703158 DOI: 10.1002/mrm.28065] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Revised: 10/04/2019] [Accepted: 10/14/2019] [Indexed: 11/10/2022]
Abstract
PURPOSE we implemented a golden-angle spiral phase contrast sequence. A commonly used uniform density spiral and a new 'perturbed' spiral that produces more incoherent aliases were assessed. The aim was to ascertain whether greater incoherence enabled more accurate Compressive Sensing reconstruction and superior measurement of flow and velocity. METHODS A range of 'perturbed' spiral trajectories based on a uniform spiral trajectory were formulated. The trajectory that produced the most noise-like aliases was selected for further testing. For in-silico and in-vivo experiments, data was reconstructed using total Variation L1 regularisation in the spatial and temporal domains. In-silico, the reconstruction accuracy of the 'perturbed' golden spiral was compared to uniform density golden-angle spiral. For the in-vivo experiment, stroke volume and peak mean velocity were measured in 20 children using 'perturbed' and uniform density golden-angle spiral sequences. These were compared to a reference standard gated Cartesian sequence. RESULTS In-silico, the perturbed spiral acquisition produced more accurate reconstructions with less temporal blurring (NRMSE ranging from 0.03 to 0.05) than the uniform density acquisition (NRMSE ranging from 0.06 to 0.12). This translated in more accurate results in-vivo with no significant bias in the peak mean velocity (bias: -0.1, limits: -4.4 to 4.1 cm/s; P = 0.98) or stroke volume (bias: -1.8, limits: -9.4 to 5.8 ml, P = 0.19). CONCLUSION We showed that a 'perturbed' golden-angle spiral approach is better suited to Compressive Sensing reconstruction due to more incoherent aliases. This enabled accurate real-time measurement of flow and peak velocity in children.
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Affiliation(s)
- Grzegorz Tomasz Kowalik
- Centre for Cardiovascular Imaging, University College London Institute of Cardiovascular Science, London, United Kingdom
| | - Daniel Knight
- Centre for Cardiovascular Imaging, University College London Institute of Cardiovascular Science, London, United Kingdom.,Department of Cardiology, Royal Free London NHS Foundation Trust, London, United Kingdom
| | - Jennifer Anne Steeden
- Centre for Cardiovascular Imaging, University College London Institute of Cardiovascular Science, London, United Kingdom
| | - Vivek Muthurangu
- Centre for Cardiovascular Imaging, University College London Institute of Cardiovascular Science, London, United Kingdom.,Great Ormond Street Hospital for Children, London, United Kingdom
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11
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Zhou R, Yang Y, Mathew RC, Mugler JP, Weller DS, Kramer CM, Ahmed AH, Jacob M, Salerno M. Free-breathing cine imaging with motion-corrected reconstruction at 3T using SPiral Acquisition with Respiratory correction and Cardiac Self-gating (SPARCS). Magn Reson Med 2019; 82:706-720. [PMID: 31006916 DOI: 10.1002/mrm.27763] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Revised: 03/12/2019] [Accepted: 03/15/2019] [Indexed: 12/28/2022]
Abstract
PURPOSE To develop a continuous-acquisition cardiac self-gated spiral pulse sequence and a respiratory motion-compensated reconstruction strategy for free-breathing cine imaging. METHODS Cine data were acquired continuously on a 3T scanner for 8 seconds per slice without ECG gating or breath-holding, using a golden-angle gradient echo spiral pulse sequence. Cardiac motion information was extracted by applying principal component analysis on the gridded 8 × 8 k-space center data. Respiratory motion was corrected by rigid registration on each heartbeat. Images were reconstructed using a low-rank and sparse (L+S) technique. This strategy was evaluated in 37 healthy subjects and 8 subjects undergoing clinical cardiac MR studies. Image quality was scored (1-5 scale) in a blinded fashion by 2 experienced cardiologists. In 13 subjects with whole-heart coverage, left ventricular ejection fraction (LVEF) from SPiral Acquisition with Respiratory correction and Cardiac Self-gating (SPARCS) was compared to that from a standard ECG-gated breath-hold balanced steady-state free precession (bSSFP) cine sequence. RESULTS The self-gated signal was successfully extracted in all cases and demonstrated close agreement with the acquired ECG signal (mean bias, -0.22 ms). The mean image score across all subjects was 4.0 for reconstruction using the L+S model. There was good agreement between the LVEF derived from SPARCS and the gold-standard bSSFP technique. CONCLUSION SPARCS successfully images cardiac function without the need for ECG gating or breath-holding. With an 8-second data acquisition per slice, whole-heart cine images with clinically acceptable spatial and temporal resolution and image quality can be acquired in <90 seconds of free-breathing acquisition.
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Affiliation(s)
- Ruixi Zhou
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia
| | - Yang Yang
- Department of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia.,Translational and Molecular Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Roshin C Mathew
- Department of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia.,Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia
| | - John P Mugler
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia.,Department of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia.,Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia
| | - Daniel S Weller
- Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, Virginia
| | - Christopher M Kramer
- Department of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia.,Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia
| | - Abdul Haseeb Ahmed
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa
| | - Mathews Jacob
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa
| | - Michael Salerno
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia.,Department of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia.,Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia
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12
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Contemporary Issues in Quantitative Myocardial Perfusion CMR Imaging. CURRENT CARDIOVASCULAR IMAGING REPORTS 2019. [DOI: 10.1007/s12410-019-9484-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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13
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Yang Y, Meyer CH, Epstein FH, Kramer CM, Salerno M. Whole-heart spiral simultaneous multi-slice first-pass myocardial perfusion imaging. Magn Reson Med 2019; 81:852-862. [PMID: 30311689 PMCID: PMC6289615 DOI: 10.1002/mrm.27412] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Revised: 05/23/2018] [Accepted: 05/30/2018] [Indexed: 11/11/2022]
Abstract
PURPOSE To develop and evaluate a simultaneous multislice (SMS) spiral perfusion pulse sequence with whole-heart coverage. METHODS An orthogonal set of phase cycling angles following a Hadamard pattern was incorporated into a golden-angle (GA) variable density spiral perfusion sequence to perform SMS imaging at different multiband (MB) factors. Images were reconstructed using an SMS extension of L1-SPIRiT that we have termed SMS-L1-SPIRiT. The proposed sequence was evaluated in 40 subjects (10 each for MB factors of 1, 2, 3, and 4). Images were blindly graded by 2 cardiologists on a 5-point scale (5, excellent). To quantitatively evaluate the reconstruction performance against images acquired without SMS, the MB =1 data were used to retrospectively simulate data acquired at MB factors of 2 to 4. RESULTS Analysis of the SMS point-spread function for the desired slice showed that the proposed sampling strategy significantly canceled the main-lobe energy of the other slices and has low side-lobe energy resulting in an incoherent temporal aliasing pattern when rotated by the GA. Retrospective experiments demonstrated the SMS-L1-SPIRiT method removed aliasing from the interfering slices and showed excellent agreement with the ground-truth MB =1 images. Clinical evaluation demonstrated high-quality perfusion images with average image-quality scores of 4.3 ± 0.5 (MB =2), 4.2 ± 0.5 (MB =3), and 4.4 ± 0.4 (MB =4) with no significant quality difference in image quality between MB factors (P = 0.38). CONCLUSION SMS spiral perfusion at MB factors 2, 3, and 4 produces high-quality perfusion images with whole-heart coverage in a clinical setting with high sampling efficiency.
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Affiliation(s)
- Yang Yang
- Departments of Medicine, Cardiovascular Division, University of Virginia Health System
| | - Craig H. Meyer
- Radiology and Medical Imaging, University of Virginia Health System
- Department of Biomedical Engineering, University of Virginia
| | - Frederick H. Epstein
- Radiology and Medical Imaging, University of Virginia Health System
- Department of Biomedical Engineering, University of Virginia
| | - Christopher M. Kramer
- Departments of Medicine, Cardiovascular Division, University of Virginia Health System
- Radiology and Medical Imaging, University of Virginia Health System
| | - Michael Salerno
- Departments of Medicine, Cardiovascular Division, University of Virginia Health System
- Radiology and Medical Imaging, University of Virginia Health System
- Department of Biomedical Engineering, University of Virginia
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14
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Salerno M, Sharif B, Arheden H, Kumar A, Axel L, Li D, Neubauer S. Recent Advances in Cardiovascular Magnetic Resonance: Techniques and Applications. Circ Cardiovasc Imaging 2017; 10:CIRCIMAGING.116.003951. [PMID: 28611116 DOI: 10.1161/circimaging.116.003951] [Citation(s) in RCA: 99] [Impact Index Per Article: 14.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Cardiovascular magnetic resonance imaging has become the gold standard for evaluating myocardial function, volumes, and scarring. Additionally, cardiovascular magnetic resonance imaging is unique in its comprehensive tissue characterization, including assessment of myocardial edema, myocardial siderosis, myocardial perfusion, and diffuse myocardial fibrosis. Cardiovascular magnetic resonance imaging has become an indispensable tool in the evaluation of congenital heart disease, heart failure, cardiac masses, pericardial disease, and coronary artery disease. This review will highlight some recent novel cardiovascular magnetic resonance imaging techniques, concepts, and applications.
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Affiliation(s)
- Michael Salerno
- From the Cardiovascular Division, Department of Medicine, Department of Radiology and Medical Imaging, and Department of Biomedical Engineering, University of Virginia Health System, Charlottesville (M.S.); Biomedical Imaging Research Institute, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA (B.S., D.L.); Department of Clinical Sciences, Clinical Physiology, Lund University, Skane University Hospital, Sweden (H.A.); Cardiology Division, Department of Medicine, Northern Ontario School of Medicine, Sudbury, Canada (A.K.); Department of Radiology and Department of Medicine, New York University, New York (L.A.); and Division of Cardiovascular Medicine, Oxford Center for Clinical Magnetic Resonance Research, University of Oxford, London, United Kingdom (S.N.).
| | - Behzad Sharif
- From the Cardiovascular Division, Department of Medicine, Department of Radiology and Medical Imaging, and Department of Biomedical Engineering, University of Virginia Health System, Charlottesville (M.S.); Biomedical Imaging Research Institute, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA (B.S., D.L.); Department of Clinical Sciences, Clinical Physiology, Lund University, Skane University Hospital, Sweden (H.A.); Cardiology Division, Department of Medicine, Northern Ontario School of Medicine, Sudbury, Canada (A.K.); Department of Radiology and Department of Medicine, New York University, New York (L.A.); and Division of Cardiovascular Medicine, Oxford Center for Clinical Magnetic Resonance Research, University of Oxford, London, United Kingdom (S.N.)
| | - Håkan Arheden
- From the Cardiovascular Division, Department of Medicine, Department of Radiology and Medical Imaging, and Department of Biomedical Engineering, University of Virginia Health System, Charlottesville (M.S.); Biomedical Imaging Research Institute, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA (B.S., D.L.); Department of Clinical Sciences, Clinical Physiology, Lund University, Skane University Hospital, Sweden (H.A.); Cardiology Division, Department of Medicine, Northern Ontario School of Medicine, Sudbury, Canada (A.K.); Department of Radiology and Department of Medicine, New York University, New York (L.A.); and Division of Cardiovascular Medicine, Oxford Center for Clinical Magnetic Resonance Research, University of Oxford, London, United Kingdom (S.N.)
| | - Andreas Kumar
- From the Cardiovascular Division, Department of Medicine, Department of Radiology and Medical Imaging, and Department of Biomedical Engineering, University of Virginia Health System, Charlottesville (M.S.); Biomedical Imaging Research Institute, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA (B.S., D.L.); Department of Clinical Sciences, Clinical Physiology, Lund University, Skane University Hospital, Sweden (H.A.); Cardiology Division, Department of Medicine, Northern Ontario School of Medicine, Sudbury, Canada (A.K.); Department of Radiology and Department of Medicine, New York University, New York (L.A.); and Division of Cardiovascular Medicine, Oxford Center for Clinical Magnetic Resonance Research, University of Oxford, London, United Kingdom (S.N.)
| | - Leon Axel
- From the Cardiovascular Division, Department of Medicine, Department of Radiology and Medical Imaging, and Department of Biomedical Engineering, University of Virginia Health System, Charlottesville (M.S.); Biomedical Imaging Research Institute, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA (B.S., D.L.); Department of Clinical Sciences, Clinical Physiology, Lund University, Skane University Hospital, Sweden (H.A.); Cardiology Division, Department of Medicine, Northern Ontario School of Medicine, Sudbury, Canada (A.K.); Department of Radiology and Department of Medicine, New York University, New York (L.A.); and Division of Cardiovascular Medicine, Oxford Center for Clinical Magnetic Resonance Research, University of Oxford, London, United Kingdom (S.N.)
| | - Debiao Li
- From the Cardiovascular Division, Department of Medicine, Department of Radiology and Medical Imaging, and Department of Biomedical Engineering, University of Virginia Health System, Charlottesville (M.S.); Biomedical Imaging Research Institute, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA (B.S., D.L.); Department of Clinical Sciences, Clinical Physiology, Lund University, Skane University Hospital, Sweden (H.A.); Cardiology Division, Department of Medicine, Northern Ontario School of Medicine, Sudbury, Canada (A.K.); Department of Radiology and Department of Medicine, New York University, New York (L.A.); and Division of Cardiovascular Medicine, Oxford Center for Clinical Magnetic Resonance Research, University of Oxford, London, United Kingdom (S.N.)
| | - Stefan Neubauer
- From the Cardiovascular Division, Department of Medicine, Department of Radiology and Medical Imaging, and Department of Biomedical Engineering, University of Virginia Health System, Charlottesville (M.S.); Biomedical Imaging Research Institute, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA (B.S., D.L.); Department of Clinical Sciences, Clinical Physiology, Lund University, Skane University Hospital, Sweden (H.A.); Cardiology Division, Department of Medicine, Northern Ontario School of Medicine, Sudbury, Canada (A.K.); Department of Radiology and Department of Medicine, New York University, New York (L.A.); and Division of Cardiovascular Medicine, Oxford Center for Clinical Magnetic Resonance Research, University of Oxford, London, United Kingdom (S.N.)
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15
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Yang Y, Zhao L, Chen X, Shaw PW, Gonzalez JA, Epstein FH, Meyer CH, Kramer CM, Salerno M. Reduced field of view single-shot spiral perfusion imaging. Magn Reson Med 2017; 79:208-216. [PMID: 28321908 DOI: 10.1002/mrm.26664] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2016] [Revised: 02/10/2017] [Accepted: 02/11/2017] [Indexed: 12/21/2022]
Abstract
PURPOSE To develop a single-shot spiral perfusion pulse sequence with outer-volume suppression (OVS) to achieve whole-heart coverage with a short temporal footprint of 10 ms per slice location. METHODS A highly accelerated single-shot variable density spiral pulse sequence with an integrated OVS module for reduced field of view (rFOV) perfusion imaging with 2 mm spatial resolution was developed and evaluated in simulations, phantom experiments and in clinical patients with (n = 8) or without (n = 8) OVS. Images were reconstructed by block low-rank sparsity with motion guidance (BLOSM) and graded by two cardiologists on a 5-point scale (1, excellent; 5, poor). RESULTS Simulation and phantom results showed that OVS effectively suppressed the signal outside the desired field of view (FOV). Clinical patient data demonstrated high quality perfusion images with rFOV. The average image quality scores of full FOV cases and rFOV cases were 3.1 ± 0.64 and 2.3 ± 0.46, respectively, (P = 0.02) from cardiologist 1 and 2.5 ± 0.54 and 1.8 ± 0.47, respectively, (P = 0.04) from cardiologist 2, showing superior image quality for the rFOV images compared with the full FOV images. CONCLUSION A single-shot spiral perfusion sequence that uses OVS and BLOSM performs perfusion imaging with a very short temporal footprint per image supporting whole-heart coverage with good image quality. Magn Reson Med 79:208-216, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Yang Yang
- Departments of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Li Zhao
- Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Xiao Chen
- Medical Imaging Technologies, Siemens Medical Solutions USA, Inc
| | - Peter W Shaw
- Cardiology Professional Services, Berkshire Medical Center, Pittsfield, Massachusetts, USA
| | - Jorge A Gonzalez
- Division of Cardiovascular Disease, Scripps Clinic, John R. Anderson V Medical Pavilion, La Jolla, California, USA
| | - Frederick H Epstein
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.,Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Craig H Meyer
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.,Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Christopher M Kramer
- Departments of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia, USA.,Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Michael Salerno
- Departments of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia, USA.,Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.,Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
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16
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Wang H, Adluru G, Chen L, Kholmovski EG, Bangerter NK, DiBella EVR. Radial simultaneous multi-slice CAIPI for ungated myocardial perfusion. Magn Reson Imaging 2016; 34:1329-1336. [PMID: 27502698 DOI: 10.1016/j.mri.2016.07.015] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2016] [Accepted: 07/30/2016] [Indexed: 11/17/2022]
Abstract
OBJECTIVE Simultaneous multi-slice (SMS) imaging is a slice acceleration technique that acquires multiple slices in the same time as a single slice. Radial controlled aliasing in parallel imaging results in higher acceleration (radial CAIPIRINHA or CAIPI) is a promising SMS method with less severe slice aliasing artifacts as compared to its Cartesian counterpart. Here we use radial CAIPI with data undersampling and constrained reconstruction to improve the utility of ungated cardiac perfusion acquisitions. We test the proposed framework with a traditional saturation recovery fast low-angle shot (turboFLASH) sequence and also without saturation recovery as a steady-state spoiled gradient echo (SPGR) sequence on animal and human studies. METHODS Simulations and phantom studies were performed for both the turboFLASH and the SPGR radial CAIPI methods. Ungated undersampled golden ratio radial CAIPI data with saturation recovery were acquired in 8 dogs and 2 human subjects. The CAIPI data without saturation pulses were acquired in 4 human subjects. For both methods, slice acceleration factors of two and three were used. A new spatio-temporal reconstruction using total variation and patch-based low rank constraints was used to jointly reconstruct the multi-slice multi-coil images. RESULTS Phantom scans and computer simulations showed that ungated SPGR generally provides better contrast to noise ratio (CNR) than the saturation recovery sequence if the saturation recovery time is less than 100ms. Both of the ungated radial CAIPI methods demonstrated promising image quality in terms of preserving dynamics of the contrast agent and maintaining anatomical structures, even with three slices acquired simultaneously. CONCLUSION Ungated simultaneous multi-slice acquisitions with either a saturation recovery turboFLASH sequence or a steady-state gradient echo SPGR sequence are feasible and provide increased slice coverage without loss of temporal resolution. Compared with a sensitivity encoding (SENSE) SMS reconstruction, the constrained reconstruction method provides better image quality for undersampled radial CAIPI data.
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Affiliation(s)
- Haonan Wang
- Department of Electrical & Computer Engineering, Brigham Young University, Provo, UT, USA
| | - Ganesh Adluru
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA.
| | - Liyong Chen
- Advanced MRI Technologies, Sebastopol, CA, United States
| | - Eugene G Kholmovski
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA
| | - Neal K Bangerter
- Department of Electrical & Computer Engineering, Brigham Young University, Provo, UT, USA; Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA
| | - Edward V R DiBella
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA
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