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Pan J, Huang W, Rueckert D, Kustner T, Hammernik K. Motion-Compensated MR CINE Reconstruction With Reconstruction-Driven Motion Estimation. IEEE TRANSACTIONS ON MEDICAL IMAGING 2024; 43:2420-2433. [PMID: 38354077 DOI: 10.1109/tmi.2024.3364504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/16/2024]
Abstract
In cardiac CINE, motion-compensated MR reconstruction (MCMR) is an effective approach to address highly undersampled acquisitions by incorporating motion information between frames. In this work, we propose a novel perspective for addressing the MCMR problem and a more integrated and efficient solution to the MCMR field. Contrary to state-of-the-art (SOTA) MCMR methods which break the original problem into two sub-optimization problems, i.e. motion estimation and reconstruction, we formulate this problem as a single entity with one single optimization. Our approach is unique in that the motion estimation is directly driven by the ultimate goal, reconstruction, but not by the canonical motion-warping loss (similarity measurement between motion-warped images and target images). We align the objectives of motion estimation and reconstruction, eliminating the drawbacks of artifacts-affected motion estimation and therefore error-propagated reconstruction. Further, we can deliver high-quality reconstruction and realistic motion without applying any regularization/smoothness loss terms, circumventing the non-trivial weighting factor tuning. We evaluate our method on two datasets: 1) an in-house acquired 2D CINE dataset for the retrospective study and 2) the public OCMR cardiac dataset for the prospective study. The conducted experiments indicate that the proposed MCMR framework can deliver artifact-free motion estimation and high-quality MR images even for imaging accelerations up to 20x, outperforming SOTA non-MCMR and MCMR methods in both qualitative and quantitative evaluation across all experiments. The code is available at https://github.com/JZPeterPan/MCMR-Recon-Driven-Motion.
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Goyal A, Crabtree CD, Lee BC, Harfi TT, Rajpal S, Yildiz VO, Simonetti OP, Tong MS. The impact of severe obesity on image quality and ventricular function assessment in echocardiography and cardiac MRI. Int J Cardiovasc Imaging 2024; 40:1081-1094. [PMID: 38625629 PMCID: PMC11147879 DOI: 10.1007/s10554-024-03078-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 03/06/2024] [Indexed: 04/17/2024]
Abstract
This study sought to evaluate the impact of severe obesity on image quality and ventricular function assessment in cardiovascular magnetic resonance (MRI) and trans-thoracic echocardiography (TTE). We studied 100 consecutive patients who underwent clinically indicated cardiac MRI and TTE studies within 12 months between July 2017 and December 2020; 50 (28 females and 22 males; 54.5 ± 18.7 years) with normal body mass index (BMI) (18.5-25 kg/m2) and 50 (21 females and 29 males; 47.2 ± 13.3 years) with severe obesity (BMI ≥ 40 kg/m2). MRI and TTE image quality scores were compared within and across cohorts using a linear mixed model. Categorical left (LVF) and right (RVF) ventricular function were compared using Cohens Kappa statistic. Mean BMI for normal weight and obese cohorts were 22.2 ± 1.7 kg/m2 and 50.3 ± 5.9 kg/m2, respectively. Out of a possible 93 points, mean MRI image quality score was 91.5 ± 2.5 for patients with normal BMI, and 88.4 ± 5.5 for patients with severe obesity; least square (LS) mean difference 3.1, p = 0.460. TTE scores were 64.2 ± 13.6 for patients with normal BMI and 46.0 ± 12.9 for patients with severe obesity, LS mean difference 18.2, p < 0.001. Ventricular function agreement between modalities was worse in the obese cohort for both LVF (72% vs 80% agreement; kappa 0.53 vs 0.70, obese vs. normal BMI), and RVF (58% vs 72% agreement, kappa 0.18 vs 0.34, obese vs. normal BMI). Severe obesity had limited impact on cardiac MRI image quality, while obesity significantly degraded TTE image quality and ventricular function agreement with MRI.
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Affiliation(s)
- Akash Goyal
- Department of Internal Medicine, Division of Cardiovascular Medicine, The Ohio State University, 234 Davis Heart & Lung Research Institute, 473 W. 12th Avenue, Columbus, OH, USA
| | | | - Bryan C Lee
- OhioHealth Systems, Heart and Vascular Institute, Columbus, OH, USA
| | - Thura T Harfi
- Department of Internal Medicine, Division of Cardiovascular Medicine, The Ohio State University, 234 Davis Heart & Lung Research Institute, 473 W. 12th Avenue, Columbus, OH, USA
| | - Saurabh Rajpal
- Department of Internal Medicine, Division of Cardiovascular Medicine, The Ohio State University, 234 Davis Heart & Lung Research Institute, 473 W. 12th Avenue, Columbus, OH, USA
| | - Vedat O Yildiz
- Center for Biostatistics, Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA
| | - Orlando P Simonetti
- Department of Internal Medicine, Division of Cardiovascular Medicine, The Ohio State University, 234 Davis Heart & Lung Research Institute, 473 W. 12th Avenue, Columbus, OH, USA
- Department of Radiology, The Ohio State University, Columbus, OH, USA
- Davis Heart & Lung Research Institute, 473 W. 12th Avenue, Columbus, OH, USA
| | - Matthew S Tong
- Department of Internal Medicine, Division of Cardiovascular Medicine, The Ohio State University, 234 Davis Heart & Lung Research Institute, 473 W. 12th Avenue, Columbus, OH, USA.
- Davis Heart & Lung Research Institute, 473 W. 12th Avenue, Columbus, OH, USA.
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Contijoch F, Rasche V, Seiberlich N, Peters DC. The future of CMR: All-in-one vs. real-time CMR (Part 2). J Cardiovasc Magn Reson 2024; 26:100998. [PMID: 38237901 PMCID: PMC11211235 DOI: 10.1016/j.jocmr.2024.100998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 01/10/2024] [Indexed: 02/20/2024] Open
Abstract
Cardiac Magnetic Resonance (CMR) protocols can be lengthy and complex, which has driven the research community to develop new technologies to make these protocols more efficient and patient-friendly. Two different approaches to improving CMR have been proposed, specifically "all-in-one" CMR, where several contrasts and/or motion states are acquired simultaneously, and "real-time" CMR, in which the examination is accelerated to avoid the need for breathholding and/or cardiac gating. The goal of this two-part manuscript is to describe these two different types of emerging rapid CMR protocols. To this end, the vision of all-in-one and real-time imaging are described, along with techniques which have been devised and tested along the pathway of clinical implementation. The pros and cons of the different methods are presented, and the remaining open needs of each are detailed. Part 1 tackles the "All-in-One" approaches, and Part 2 focuses on the "Real-Time" approaches along with an overall summary of these emerging methods.
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Affiliation(s)
| | - Volker Rasche
- Ulm University Medical Center, Department of Internal Medicine II, Ulm, Germany
| | - Nicole Seiberlich
- Michigan Institute for Imaging Technology and Translation, Department of Radiology, University of Michigan, Ann Arbor, MI, USA
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Demirel OB, Zhang C, Yaman B, Gulle M, Shenoy C, Leiner T, Kellman P, Akcakaya M. High-fidelity Database-free Deep Learning Reconstruction for Real-time Cine Cardiac MRI. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38083374 PMCID: PMC10976294 DOI: 10.1109/embc40787.2023.10340709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Real-time cine cardiac MRI provides an ECG-free free-breathing alternative to clinical gold-standard ECG-gated breath-hold segmented cine MRI for evaluation of heart function. Real-time cine MRI data acquisition during free breathing snapshot imaging enables imaging of patient cohorts that cannot be imaged with segmented or breath-hold acquisitions, but requires rapid imaging to achieve sufficient spatial-temporal resolutions. However, at high acceleration rates, conventional reconstruction techniques suffer from residual aliasing and temporal blurring, including advanced methods such as compressed sensing with radial trajectories. Recently, deep learning (DL) reconstruction has emerged as a powerful tool in MRI. However, its utility for free-breathing real-time cine MRI has been limited, as database-learning of spatio-temporal correlations with varying breathing and cardiac motion patterns across subjects has been challenging. Zero-shot self-supervised physics-guided deep learning (PG-DL) reconstruction has been proposed to overcome such challenges of database training by enabling subject-specific training. In this work, we adapt zero-shot PG-DL for real-time cine MRI with a spatio-temporal regularization. We compare our method to TGRAPPA, locally low-rank (LLR) regularized reconstruction and database-trained PG-DL reconstruction, both for retrospectively and prospectively accelerated datasets. Results on highly accelerated real-time Cartesian cine MRI show that the proposed method outperforms other reconstruction methods, both visibly in terms of noise and aliasing, and quantitatively.
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Hamilton JI, Truesdell W, Galizia M, Burris N, Agarwal P, Seiberlich N. A low-rank deep image prior reconstruction for free-breathing ungated spiral functional CMR at 0.55 T and 1.5 T. MAGMA (NEW YORK, N.Y.) 2023; 36:451-464. [PMID: 37043121 PMCID: PMC11017470 DOI: 10.1007/s10334-023-01088-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 03/02/2023] [Accepted: 04/01/2023] [Indexed: 04/13/2023]
Abstract
OBJECTIVE This study combines a deep image prior with low-rank subspace modeling to enable real-time (free-breathing and ungated) functional cardiac imaging on a commercial 0.55 T scanner. MATERIALS AND METHODS The proposed low-rank deep image prior (LR-DIP) uses two u-nets to generate spatial and temporal basis functions that are combined to yield dynamic images, with no need for additional training data. Simulations and scans in 13 healthy subjects were performed at 0.55 T and 1.5 T using a golden angle spiral bSSFP sequence with images reconstructed using [Formula: see text]-ESPIRiT, low-rank plus sparse (L + S) matrix completion, and LR-DIP. Cartesian breath-held ECG-gated cine images were acquired for reference at 1.5 T. Two cardiothoracic radiologists rated images on a 1-5 scale for various categories, and LV function measurements were compared. RESULTS LR-DIP yielded the lowest errors in simulations, especially at high acceleration factors (R [Formula: see text] 8). LR-DIP ejection fraction measurements agreed with 1.5 T reference values (mean bias - 0.3% at 0.55 T and - 0.2% at 1.5 T). Compared to reference images, LR-DIP images received similar ratings at 1.5 T (all categories above 3.9) and slightly lower at 0.55 T (above 3.4). CONCLUSION Feasibility of real-time functional cardiac imaging using a low-rank deep image prior reconstruction was demonstrated in healthy subjects on a commercial 0.55 T scanner.
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Affiliation(s)
- Jesse I Hamilton
- Department of Radiology, University of Michigan, 1301 Catherine St, Ann Arbor, MI, 48109-1590, USA.
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.
| | - William Truesdell
- Department of Radiology, University of Michigan, 1301 Catherine St, Ann Arbor, MI, 48109-1590, USA
| | - Mauricio Galizia
- Department of Radiology, University of Michigan, 1301 Catherine St, Ann Arbor, MI, 48109-1590, USA
| | - Nicholas Burris
- Department of Radiology, University of Michigan, 1301 Catherine St, Ann Arbor, MI, 48109-1590, USA
| | - Prachi Agarwal
- Department of Radiology, University of Michigan, 1301 Catherine St, Ann Arbor, MI, 48109-1590, USA
| | - Nicole Seiberlich
- Department of Radiology, University of Michigan, 1301 Catherine St, Ann Arbor, MI, 48109-1590, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
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Ogier AC, Rapacchi S, Bellemare ME. Four-dimensional reconstruction and characterization of bladder deformations. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2023; 237:107569. [PMID: 37186971 DOI: 10.1016/j.cmpb.2023.107569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 03/31/2023] [Accepted: 04/24/2023] [Indexed: 05/17/2023]
Abstract
BACKGROUND AND OBJECTIVE Pelvic floor disorders are prevalent diseases and patient care remains difficult as the dynamics of the pelvic floor remains poorly understood. So far, only 2D dynamic observations of straining exercises at excretion are available in the clinics and 3D mechanical defects of pelvic organs are not well studied. In this context, we propose a complete methodology for the 3D representation of non-reversible bladder deformations during exercises, combined with a 3D representation of the location of the highest strain areas on the organ surface. METHODS Novel image segmentation and registration approaches have been combined with three geometrical configurations of up-to-date rapid dynamic multi-slice MRI acquisitions for the reconstruction of real-time dynamic bladder volumes. RESULTS For the first time, we proposed real-time 3D deformation fields of the bladder under strain from in-bore forced breathing exercises. The potential of our method was assessed on eight control subjects undergoing forced breathing exercises. We obtained average volume deviations of the reconstructed dynamic volume of bladders around 2.5% and high registration accuracy with mean distance values of 0.4 ± 0.3 mm and Hausdorff distance values of 2.2 ± 1.1 mm. CONCLUSIONS The proposed framework provides proper 3D+t spatial tracking of non-reversible bladder deformations. This has immediate applicability in clinical settings for a better understanding of pelvic organ prolapse pathophysiology. This work can be extended to patients with cavity filling or excretion problems to better characterize the severity of pelvic floor pathologies or to be used for preoperative surgical planning.
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Affiliation(s)
- Augustin C Ogier
- Aix Marseille Univ, Universite de Toulon, CNRS, LIS, Marseille, France.
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Aetesam H, Maji SK. Perceptually Motivated Generative Model for Magnetic Resonance Image Denoising. J Digit Imaging 2023; 36:725-738. [PMID: 36474088 PMCID: PMC10039195 DOI: 10.1007/s10278-022-00744-2] [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: 03/21/2022] [Revised: 11/01/2022] [Accepted: 11/17/2022] [Indexed: 12/12/2022] Open
Abstract
Image denoising is an important preprocessing step in low-level vision problems involving biomedical images. Noise removal techniques can greatly benefit raw corrupted magnetic resonance images (MRI). It has been discovered that the MR data is corrupted by a mixture of Gaussian-impulse noise caused by detector flaws and transmission errors. This paper proposes a deep generative model (GenMRIDenoiser) for dealing with this mixed noise scenario. This work makes four contributions. To begin, Wasserstein generative adversarial network (WGAN) is used in model training to mitigate the problem of vanishing gradient, mode collapse, and convergence issues encountered while training a vanilla GAN. Second, a perceptually motivated loss function is used to guide the training process in order to preserve the low-level details in the form of high-frequency components in the image. Third, batch renormalization is used between the convolutional and activation layers to prevent performance degradation under the assumption of non-independent and identically distributed (non-iid) data. Fourth, global feature attention module (GFAM) is appended at the beginning and end of the parallel ensemble blocks to capture the long-range dependencies that are often lost due to the small receptive field of convolutional filters. The experimental results over synthetic data and MRI stack obtained from real MR scanners indicate the potential utility of the proposed technique across a wide range of degradation scenarios.
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Affiliation(s)
- Hazique Aetesam
- Department of Computer Science and Engineering, Indian Institute of Technology Patna, Patna, 801106 India
| | - Suman Kumar Maji
- Department of Computer Science and Engineering, Indian Institute of Technology Patna, Patna, 801106 India
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Demirel ÖB, Zhang C, Yaman B, Gulle M, Shenoy C, Leiner T, Kellman P, Akçakaya M. High-fidelity Database-free Deep Learning Reconstruction for Real-time Cine Cardiac MRI. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.13.528388. [PMID: 36824797 PMCID: PMC9948950 DOI: 10.1101/2023.02.13.528388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Real-time cine cardiac MRI provides an ECG-free free-breathing alternative to clinical gold-standard ECG-gated breath-hold segmented cine MRI for evaluation of heart function. Real-time cine MRI data acquisition during free breathing snapshot imaging enables imaging of patient cohorts that cannot be imaged with segmented or breath-hold acquisitions, but requires rapid imaging to achieve sufficient spatial-temporal resolutions. However, at high acceleration rates, conventional reconstruction techniques suffer from residual aliasing and temporal blurring, including advanced methods such as compressed sensing with radial trajectories. Recently, deep learning (DL) reconstruction has emerged as a powerful tool in MRI. However, its utility for free-breathing real-time cine MRI has been limited, as database-learning of spatio-temporal correlations with varying breathing and cardiac motion patterns across subjects has been challenging. Zero-shot self-supervised physics-guided deep learning (PG-DL) reconstruction has been proposed to overcome such challenges of database training by enabling subject-specific training. In this work, we adapt zero-shot PG-DL for real-time cine MRI with a spatio-temporal regularization. We compare our method to TGRAPPA, locally low-rank (LLR) regularized reconstruction and database-trained PG-DL reconstruction, both for retrospectively and prospectively accelerated datasets. Results on highly accelerated real-time Cartesian cine MRI show that the proposed method outperforms other reconstruction methods, both visibly in terms of noise and aliasing, and quantitatively.
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Affiliation(s)
- Ömer Burak Demirel
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, USA
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Chi Zhang
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, USA
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Burhaneddin Yaman
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, USA
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Merve Gulle
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, USA
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Chetan Shenoy
- Department of Medicine (Cardiology), University of Minnesota, Minneapolis, MN, USA
| | - Tim Leiner
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Peter Kellman
- National Heart-Lung and Blood Institute, Bethesda, MD, USA
| | - Mehmet Akçakaya
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, USA
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
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Franson D, Ahad J, Liu Y, Fyrdahl A, Truesdell W, Hamilton J, Seiberlich N. Self-calibrated through-time spiral GRAPPA for real-time, free-breathing evaluation of left ventricular function. Magn Reson Med 2023; 89:536-549. [PMID: 36198001 PMCID: PMC10092570 DOI: 10.1002/mrm.29462] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 07/15/2022] [Accepted: 08/26/2022] [Indexed: 12/13/2022]
Abstract
PURPOSE Through-time spiral GRAPPA is a real-time imaging technique that enables ungated, free-breathing evaluation of the left ventricle. However, it requires a separate fully-sampled calibration scan to calculate GRAPPA weights. A self-calibrated through-time spiral GRAPPA method is proposed that uses a specially designed spiral trajectory with interleaved arm ordering such that consecutive undersampled frames can be merged to form calibration data, eliminating the separate fully-sampled acquisition. THEORY AND METHODS The proposed method considers the time needed to acquire data at all points in a GRAPPA calibration kernel when using interleaved arm ordering. Using this metric, simulations were performed to design a spiral trajectory for self-calibrated GRAPPA. Data were acquired in healthy volunteers using the proposed method and a comparison electrocardiogram-gated and breath-held cine scan. Left ventricular functional values and image quality are compared. RESULTS A 12-arm spiral trajectory was designed with a temporal resolution of 32.72 ms/cardiac phase with an acceleration factor of 3. Functional values calculated using the proposed method and the gold-standard method were not statistically significantly different (paired t-test, p < 0.05). Image quality ratings were lower for the proposed method, with statistically significantly different ratings (Wilcoxon signed rank test, p < 0.05) for two of five image quality aspects rated (level of artifact, blood-myocardium contrast). CONCLUSIONS A self-calibrated through-time spiral GRAPPA reconstruction can enable ungated, free-breathing evaluation of the left ventricle in 71 s. Functional values are equivalent to a gold-standard cine technique, although some aspects of image quality may be inferior due to the real-time nature of the data collection.
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Affiliation(s)
- Dominique Franson
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - James Ahad
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Yuchi Liu
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Alexander Fyrdahl
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - William Truesdell
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Jesse Hamilton
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Nicole Seiberlich
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
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Shit S, Zimmermann J, Ezhov I, Paetzold JC, Sanches AF, Pirkl C, Menze BH. SRflow: Deep learning based super-resolution of 4D-flow MRI data. Front Artif Intell 2022; 5:928181. [PMID: 36034591 PMCID: PMC9411720 DOI: 10.3389/frai.2022.928181] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 07/11/2022] [Indexed: 11/13/2022] Open
Abstract
Exploiting 4D-flow magnetic resonance imaging (MRI) data to quantify hemodynamics requires an adequate spatio-temporal vector field resolution at a low noise level. To address this challenge, we provide a learned solution to super-resolve in vivo 4D-flow MRI data at a post-processing level. We propose a deep convolutional neural network (CNN) that learns the inter-scale relationship of the velocity vector map and leverages an efficient residual learning scheme to make it computationally feasible. A novel, direction-sensitive, and robust loss function is crucial to learning vector-field data. We present a detailed comparative study between the proposed super-resolution and the conventional cubic B-spline based vector-field super-resolution. Our method improves the peak-velocity to noise ratio of the flow field by 10 and 30% for in vivo cardiovascular and cerebrovascular data, respectively, for 4 × super-resolution over the state-of-the-art cubic B-spline. Significantly, our method offers 10x faster inference over the cubic B-spline. The proposed approach for super-resolution of 4D-flow data would potentially improve the subsequent calculation of hemodynamic quantities.
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Affiliation(s)
- Suprosanna Shit
- Department of Informatics, Technical University of Munich, Munich, Germany
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
- *Correspondence: Suprosanna Shit
| | - Judith Zimmermann
- Department of Informatics, Technical University of Munich, Munich, Germany
| | - Ivan Ezhov
- Department of Informatics, Technical University of Munich, Munich, Germany
| | | | - Augusto F. Sanches
- Institute of Neuroradiology, University Hospital LMU Munich, Munich, Germany
| | - Carolin Pirkl
- Department of Informatics, Technical University of Munich, Munich, Germany
| | - Bjoern H. Menze
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
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11
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Blind image quality assessment of magnetic resonance images with statistics of local intensity extrema. Inf Sci (N Y) 2022. [DOI: 10.1016/j.ins.2022.05.061] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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12
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McElroy S, Kunze KP, Nazir MS, Speier P, Stäb D, Villa ADM, Yazdani M, Vergani V, Roujol S, Neji R, Chiribiri A. Simultaneous multi-slice steady-state free precession myocardial perfusion with iterative reconstruction and integrated motion compensation. Eur J Radiol 2022; 151:110286. [PMID: 35452953 PMCID: PMC9941714 DOI: 10.1016/j.ejrad.2022.110286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 03/09/2022] [Accepted: 03/23/2022] [Indexed: 11/22/2022]
Abstract
PURPOSE Simultaneous multi-slice (SMS) balanced steady-state free precession (bSSFP) acquisition and iterative reconstruction can provide high spatial resolution and coverage for cardiac magnetic resonance (CMR) perfusion. However, respiratory motion remains a challenge for iterative reconstruction techniques employing temporal regularisation. The aim of this study is to evaluate an iterative reconstruction with integrated motion compensation for SMS-bSSFP first-pass myocardial stress perfusion in the presence of respiratory motion. METHODS Thirty-one patients with suspected coronary artery disease were prospectively recruited and imaged at 1.5 T. A SMS-bSSFP prototype myocardial perfusion sequence was acquired at stress in all patients. All datasets were reconstructed using an iterative reconstruction with temporal regularisation, once with and once without motion compensation (MC and NMC, respectively). Three readers scored each dataset in terms of: image quality (1:poor; 4:excellent), motion/blurring (1:severe motion/blurring; 3:no motion/blurring), and diagnostic confidence (1:poor confidence; 3:high confidence). Quantitative assessment of sharpness was performed. The number of uncorrupted first-pass dynamics was measured on the NMC datasets to classify patients into 'suboptimal breath-hold (BH)' and 'good BH' groups. RESULTS Compared across all cases, MC performed better than NMC in terms of image quality (3.5 ± 0.5 vs. 3.0 ± 0.8, P = 0.002), motion/blurring (2.9 ± 0.1 vs. 2.2 ± 0.8, P < 0.001), diagnostic confidence (2.9 ± 0.1 vs. 2.3 ± 0.7, P < 0.001) and sharpness index (0.34 ± 0.05 vs. 0.31 ± 0.06, P < 0.001). Fourteen patients with a suboptimal BH were identified. For the suboptimal BH group, MC performed better than NMC in terms of image quality (3.8 ± 0.4 vs. 2.6 ± 0.8, P < 0.001), motion/blurring (3.0 ± 0.1 vs. 1.6 ± 0.7, P < 0.001), diagnostic confidence (3.0 ± 0.1 vs. 1.9 ± 0.7, P < 0.001) and sharpness index (0.34 ± 0.05 vs. 0.30 ± 0.06, P = 0.004). For the good BH group, sharpness index was higher for MC than NMC (0.34 ± 0.06 vs 0.31 ± 0.07, P = 0.03), while there were no significant differences observed for the other three metrics assessed (P > 0.11). There were no significant differences between suboptimal BH MC and good BH MC for any of the reported metrics (P > 0.06). CONCLUSIONS Integrated motion compensation significantly reduces motion/blurring and improves image quality, diagnostic confidence and sharpness index of SMS-bSSFP perfusion with iterative reconstruction in the presence of motion.
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Affiliation(s)
- Sarah McElroy
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom.
| | - Karl P Kunze
- MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom
| | - Muhummad Sohaib Nazir
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
| | - Peter Speier
- Cardiovascular Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Daniel Stäb
- MR Research Collaborations, Siemens Healthcare Limited, Melbourne, Australia
| | - Adriana D M Villa
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
| | - Momina Yazdani
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
| | - Vittoria Vergani
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
| | - Sébastien Roujol
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
| | - Radhouene Neji
- MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom
| | - Amedeo Chiribiri
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom.
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13
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Sun C, Robinson A, Wang Y, Bilchick KC, Kramer CM, Weller D, Salerno M, Epstein FH. A Slice-Low-Rank Plus Sparse (slice-L + S) Reconstruction Method for k-t Undersampled Multiband First-Pass Myocardial Perfusion MRI. Magn Reson Med 2022; 88:1140-1155. [PMID: 35608225 PMCID: PMC9325064 DOI: 10.1002/mrm.29281] [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: 07/27/2021] [Revised: 03/14/2022] [Accepted: 04/11/2022] [Indexed: 11/19/2022]
Abstract
Purpose The synergistic use of k‐t undersampling and multiband (MB) imaging has the potential to provide extended slice coverage and high spatial resolution for first‐pass perfusion MRI. The low‐rank plus sparse (L + S) model has shown excellent performance for accelerating single‐band (SB) perfusion MRI. Methods A MB data consistency method employing ESPIRiT maps and through‐plane coil information was developed. This data consistency method was combined with the temporal L + S constraint to form the slice‐L + S method. Slice‐L + S was compared to SB L + S and the sequential operations of split slice‐GRAPPA and SB L + S (seq‐SG‐L + S) using synthetic data formed from multislice SB images. Prospectively k‐t undersampled MB data were also acquired and reconstructed using seq‐SG‐L + S and slice‐L + S. Results Using synthetic data with total acceleration rates of 6–12, slice‐L + S outperformed SB L + S and seq‐SG‐L + S (N = 7 subjects) with respect to normalized RMSE and the structural similarity index (P < 0.05 for both). For the specific case with MB factor = 3 and rate 3 undersampling, or for SB imaging with rate 9 undersampling (N = 7 subjects), the normalized RMSE values were 0.037 ± 0.007, 0.042 ± 0.005, and 0.031 ± 0.004; and the structural similarity index values were 0.88 ± 0.03, 0.85 ± 0.03, and 0.89 ± 0.02 for SB L + S, seq‐SG‐L + S, and slice‐L + S, respectively (P < 0.05 for both). For prospectively undersampled MB data, slice‐L + S provided better image quality than seq‐SG‐L + S for rate 6 (N = 7) and rate 9 acceleration (N = 7) as scored by blinded experts. Conclusion Slice‐L + S outperformed SB‐L + S and seq‐SG‐L + S and provides 9 slice coverage of the left ventricle with a spatial resolution of 1.5 mm × 1.5 mm with good image quality.
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Affiliation(s)
- Changyu Sun
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia.,Department of Biomedical, Biological and Chemical Engineering, University of Missouri, Columbia, Missouri.,Department of Radiology, University of Missouri, Columbia, Missouri
| | - Austin Robinson
- Department of Medicine, University of Virginia Health System, Charlottesville, Virginia
| | - Yu Wang
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia
| | - Kenneth C Bilchick
- Department of Medicine, University of Virginia Health System, Charlottesville, Virginia
| | - Christopher M Kramer
- Department of Medicine, University of Virginia Health System, Charlottesville, Virginia.,Department of Radiology, University of Virginia Health System, Charlottesville, Virginia
| | - Daniel Weller
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia.,Department of Radiology, University of Virginia Health System, Charlottesville, Virginia.,Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, Virginia
| | - Michael Salerno
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia.,Department of Medicine, University of Virginia Health System, Charlottesville, Virginia.,Department of Radiology, University of Virginia Health System, Charlottesville, Virginia
| | - Frederick H Epstein
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia.,Department of Radiology, University of Virginia Health System, Charlottesville, Virginia
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14
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Nita N, Kersten J, Pott A, Weber F, Tesfay T, Benea MT, Metze P, Li H, Rottbauer W, Rasche V, Buckert D. Real-Time Spiral CMR Is Superior to Conventional Segmented Cine-Imaging for Left-Ventricular Functional Assessment in Patients with Arrhythmia. J Clin Med 2022; 11:jcm11082088. [PMID: 35456181 PMCID: PMC9025940 DOI: 10.3390/jcm11082088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 03/29/2022] [Accepted: 04/06/2022] [Indexed: 02/04/2023] Open
Abstract
(1) Background: Segmented Cartesian Cardiovascular magnetic resonance (CMR) often fails to deliver robust assessment of cardiac function in patients with arrhythmia. We aimed to assess the performance of a tiny golden-angle spiral real-time CMR sequence at 1.5 T for left-ventricular (LV) volumetry in patients with irregular heart rhythm; (2) Methods: We validated the real-time sequence against the standard breath-hold segmented Cartesian sequence in 32 patients, of whom 11 presented with arrhythmia. End-diastolic volume (EDV), end-systolic volume (ESV), stroke volume (SV), and ejection fraction (EF) were assessed. In arrhythmic patients, real-time and standard Cartesian acquisitions were compared against a reference echocardiographic modality; (3) Results: In patients with sinus rhythm, good agreements and correlations were found between the segmented and real-time methods, with only minor, non-significant underestimation of EDV for the real-time sequence (135.95 ± 30 mL vs. 137.15 ± 31, p = 0.164). In patients with arrhythmia, spiral real-time CMR yielded superior image quality to the conventional segmented imaging, allowing for excellent agreement with the reference echocardiographic volumetry. In contrast, in this cohort, standard Cartesian CMR showed significant underestimation of LV-ESV (106.72 ± 63.51 mL vs. 125.47 ± 72.41 mL, p = 0.026) and overestimation of LVEF (42.96 ± 10.81% vs. 39.02 ± 11.72%, p = 0.039); (4) Conclusions: Real-time spiral CMR improves image quality in arrhythmic patients, allowing reliable assessment of LV volumetry.
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Affiliation(s)
- Nicoleta Nita
- Department of Internal Medicine II, University Medical Center, 89081 Ulm, Germany; (J.K.); (A.P.); (F.W.); (T.T.); (P.M.); (H.L.); (W.R.); (V.R.); (D.B.)
- Correspondence:
| | - Johannes Kersten
- Department of Internal Medicine II, University Medical Center, 89081 Ulm, Germany; (J.K.); (A.P.); (F.W.); (T.T.); (P.M.); (H.L.); (W.R.); (V.R.); (D.B.)
| | - Alexander Pott
- Department of Internal Medicine II, University Medical Center, 89081 Ulm, Germany; (J.K.); (A.P.); (F.W.); (T.T.); (P.M.); (H.L.); (W.R.); (V.R.); (D.B.)
| | - Fabian Weber
- Department of Internal Medicine II, University Medical Center, 89081 Ulm, Germany; (J.K.); (A.P.); (F.W.); (T.T.); (P.M.); (H.L.); (W.R.); (V.R.); (D.B.)
| | - Temsgen Tesfay
- Department of Internal Medicine II, University Medical Center, 89081 Ulm, Germany; (J.K.); (A.P.); (F.W.); (T.T.); (P.M.); (H.L.); (W.R.); (V.R.); (D.B.)
| | | | - Patrick Metze
- Department of Internal Medicine II, University Medical Center, 89081 Ulm, Germany; (J.K.); (A.P.); (F.W.); (T.T.); (P.M.); (H.L.); (W.R.); (V.R.); (D.B.)
| | - Hao Li
- Department of Internal Medicine II, University Medical Center, 89081 Ulm, Germany; (J.K.); (A.P.); (F.W.); (T.T.); (P.M.); (H.L.); (W.R.); (V.R.); (D.B.)
| | - Wolfgang Rottbauer
- Department of Internal Medicine II, University Medical Center, 89081 Ulm, Germany; (J.K.); (A.P.); (F.W.); (T.T.); (P.M.); (H.L.); (W.R.); (V.R.); (D.B.)
| | - Volker Rasche
- Department of Internal Medicine II, University Medical Center, 89081 Ulm, Germany; (J.K.); (A.P.); (F.W.); (T.T.); (P.M.); (H.L.); (W.R.); (V.R.); (D.B.)
| | - Dominik Buckert
- Department of Internal Medicine II, University Medical Center, 89081 Ulm, Germany; (J.K.); (A.P.); (F.W.); (T.T.); (P.M.); (H.L.); (W.R.); (V.R.); (D.B.)
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15
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Feng L, Ma D, Liu F. Rapid MR relaxometry using deep learning: An overview of current techniques and emerging trends. NMR IN BIOMEDICINE 2022; 35:e4416. [PMID: 33063400 PMCID: PMC8046845 DOI: 10.1002/nbm.4416] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 08/25/2020] [Accepted: 09/09/2020] [Indexed: 05/08/2023]
Abstract
Quantitative mapping of MR tissue parameters such as the spin-lattice relaxation time (T1 ), the spin-spin relaxation time (T2 ), and the spin-lattice relaxation in the rotating frame (T1ρ ), referred to as MR relaxometry in general, has demonstrated improved assessment in a wide range of clinical applications. Compared with conventional contrast-weighted (eg T1 -, T2 -, or T1ρ -weighted) MRI, MR relaxometry provides increased sensitivity to pathologies and delivers important information that can be more specific to tissue composition and microenvironment. The rise of deep learning in the past several years has been revolutionizing many aspects of MRI research, including image reconstruction, image analysis, and disease diagnosis and prognosis. Although deep learning has also shown great potential for MR relaxometry and quantitative MRI in general, this research direction has been much less explored to date. The goal of this paper is to discuss the applications of deep learning for rapid MR relaxometry and to review emerging deep-learning-based techniques that can be applied to improve MR relaxometry in terms of imaging speed, image quality, and quantification robustness. The paper is comprised of an introduction and four more sections. Section 2 describes a summary of the imaging models of quantitative MR relaxometry. In Section 3, we review existing "classical" methods for accelerating MR relaxometry, including state-of-the-art spatiotemporal acceleration techniques, model-based reconstruction methods, and efficient parameter generation approaches. Section 4 then presents how deep learning can be used to improve MR relaxometry and how it is linked to conventional techniques. The final section concludes the review by discussing the promise and existing challenges of deep learning for rapid MR relaxometry and potential solutions to address these challenges.
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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
| | - Dan Ma
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Fang Liu
- Department of Radiology, Massachusetts General Hospital, Harvard University, Boston, Massachusetts
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16
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Srinivas SA, Cauley SF, Stockmann JP, Sappo CR, Vaughn CE, Wald LL, Grissom WA, Cooley CZ. External Dynamic InTerference Estimation and Removal (EDITER) for low field MRI. Magn Reson Med 2022; 87:614-628. [PMID: 34480778 PMCID: PMC8920578 DOI: 10.1002/mrm.28992] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 07/25/2021] [Accepted: 08/10/2021] [Indexed: 02/03/2023]
Abstract
PURPOSE Point-of-care MRI requires operation outside of Faraday shielded rooms normally used to block image-degrading electromagnetic interference (EMI). To address this, we introduce the EDITER method (External Dynamic InTerference Estimation and Removal), an external sensor-based method to retrospectively remove image artifacts from time-varying external interference sources. THEORY AND METHODS The method acquires data from multiple EMI detectors (tuned receive coils as well as untuned electrodes placed on the body) simultaneously with the primary MR coil during and between image data acquisition. We calculate impulse response functions dynamically that map the data from the detectors to the time varying artifacts then remove the transformed detected EMI from the MR data. Performance of the EDITER algorithm was assessed in phantom and in vivo imaging experiments in an 80 mT portable brain MRI in a controlled EMI environment and with an open 47.5 mT MRI scanner in an uncontrolled EMI setting. RESULTS In the controlled setting, the effectiveness of the EDITER technique was demonstrated for specific types of introduced EMI sources with up to a 97% reduction of structured EMI and up to 76% reduction of broadband EMI in phantom experiments. In the uncontrolled EMI experiments, we demonstrate EMI reductions of up to 99% using an electrode and pick-up coil in vivo. We demonstrate up to a nine-fold improvement in image SNR with the method. CONCLUSION The EDITER technique is a flexible and robust method to improve image quality in portable MRI systems with minimal passive shielding and could reduce the reliance of MRI on shielded rooms and allow for truly portable MRI.
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Affiliation(s)
- Sai Abitha Srinivas
- Vanderbilt University Institute of imaging science, Nashville, TN, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
| | - Stephen F Cauley
- Harvard Medical School, Boston, MA, United States
- Dept. of Radiology, Massachusetts General Hospital, Athinoula A Martinos Center for Biomedical Imaging, Boston, MA, United States
| | - Jason P Stockmann
- Harvard Medical School, Boston, MA, United States
- Dept. of Radiology, Massachusetts General Hospital, Athinoula A Martinos Center for Biomedical Imaging, Boston, MA, United States
| | - Charlotte R Sappo
- Vanderbilt University Institute of imaging science, Nashville, TN, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
| | - Christopher E Vaughn
- Vanderbilt University Institute of imaging science, Nashville, TN, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
| | - Lawrence L Wald
- Harvard Medical School, Boston, MA, United States
- Dept. of Radiology, Massachusetts General Hospital, Athinoula A Martinos Center for Biomedical Imaging, Boston, MA, United States
- Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, United States
| | - William A Grissom
- Vanderbilt University Institute of imaging science, Nashville, TN, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
- Department of Electrical Engineering, Vanderbilt University, Nashville, TN, United States
- Department of Radiology, Vanderbilt University, Nashville, TN, United States
| | - Clarissa Z Cooley
- Harvard Medical School, Boston, MA, United States
- Dept. of Radiology, Massachusetts General Hospital, Athinoula A Martinos Center for Biomedical Imaging, Boston, MA, United States
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17
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Svecic A, Mansour R, Tang A, Kadoury S. Prediction of post transarterial chemoembolization MR images of hepatocellular carcinoma using spatio-temporal graph convolutional networks. PLoS One 2021; 16:e0259692. [PMID: 34874934 PMCID: PMC8651128 DOI: 10.1371/journal.pone.0259692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 10/24/2021] [Indexed: 11/25/2022] Open
Abstract
Magnetic resonance imaging (MRI) plays a critical role in the planning and monitoring of hepatocellular carcinomas (HCC) treated with locoregional therapies, in order to assess disease progression or recurrence. Dynamic contrast-enhanced (DCE)-MRI sequences offer temporal data on tumor enhancement characteristics which has strong prognostic value. Yet, predicting follow-up DCE-MR images from which tumor enhancement and viability can be measured, before treatment of HCC actually begins, remains an unsolved problem given the complexity of spatial and temporal information. We propose an approach to predict future DCE-MRI examinations following transarterial chemoembolization (TACE) by learning the spatio-temporal features related to HCC response from pre-TACE images. A novel Spatial-Temporal Discriminant Graph Neural Network (STDGNN) based on graph convolutional networks is presented. First, embeddings of viable, equivocal and non-viable HCCs are separated within a joint low-dimensional latent space, which is created using a discriminant neural network representing tumor-specific features. Spatial tumoral features from independent MRI volumes are then extracted with a structural branch, while dynamic features are extracted from the multi-phase sequence with a separate temporal branch. The model extracts spatio-temporal features by a joint minimization of the network branches. At testing, a pre-TACE diagnostic DCE-MRI is embedded on the discriminant spatio-temporal latent space, which is then translated to the follow-up domain space, thus allowing to predict the post-TACE DCE-MRI describing HCC treatment response. A dataset of 366 HCC’s from liver cancer patients was used to train and test the model using DCE-MRI examinations with associated pathological outcomes, with the spatio-temporal framework yielding 93.5% classification accuracy in response identification, and generating follow-up images yielding insignificant differences in perfusion parameters compared to ground-truth post-TACE examinations.
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Affiliation(s)
- Andrei Svecic
- Department of Computer Engineering, MedICAL, Polytechnique Montréal, Montréal, Québec, Canada
| | | | - An Tang
- CHUM Research Center, Montréal, Québec, Canada
- Department of Radiology, CHUM, Montréal, Québec, Canada
| | - Samuel Kadoury
- Department of Computer Engineering, MedICAL, Polytechnique Montréal, Montréal, Québec, Canada
- CHUM Research Center, Montréal, Québec, Canada
- * E-mail:
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18
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Yoo J, Jin KH, Gupta H, Yerly J, Stuber M, Unser M. Time-Dependent Deep Image Prior for Dynamic MRI. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:3337-3348. [PMID: 34043506 DOI: 10.1109/tmi.2021.3084288] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
We propose a novel unsupervised deep-learning-based algorithm for dynamic magnetic resonance imaging (MRI) reconstruction. Dynamic MRI requires rapid data acquisition for the study of moving organs such as the heart. We introduce a generalized version of the deep-image-prior approach, which optimizes the weights of a reconstruction network to fit a sequence of sparsely acquired dynamic MRI measurements. Our method needs neither prior training nor additional data. In particular, for cardiac images, it does not require the marking of heartbeats or the reordering of spokes. The key ingredients of our method are threefold: 1) a fixed low-dimensional manifold that encodes the temporal variations of images; 2) a network that maps the manifold into a more expressive latent space; and 3) a convolutional neural network that generates a dynamic series of MRI images from the latent variables and that favors their consistency with the measurements in k -space. Our method outperforms the state-of-the-art methods quantitatively and qualitatively in both retrospective and real fetal cardiac datasets. To the best of our knowledge, this is the first unsupervised deep-learning-based method that can reconstruct the continuous variation of dynamic MRI sequences with high spatial resolution.
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19
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Xue H, Artico J, Fontana M, Moon JC, Davies RH, Kellman P. Landmark Detection in Cardiac MRI by Using a Convolutional Neural Network. Radiol Artif Intell 2021; 3:e200197. [PMID: 34617022 PMCID: PMC8489464 DOI: 10.1148/ryai.2021200197] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 04/28/2021] [Accepted: 06/15/2021] [Indexed: 12/03/2022]
Abstract
PURPOSE To develop a convolutional neural network (CNN) solution for landmark detection in cardiac MRI (CMR). MATERIALS AND METHODS This retrospective study included cine, late gadolinium enhancement (LGE), and T1 mapping examinations from two hospitals. The training set included 2329 patients (34 089 images; mean age, 54.1 years; 1471 men; December 2017 to March 2020). A hold-out test set included 531 patients (7723 images; mean age, 51.5 years; 323 men; May 2020 to July 2020). CNN models were developed to detect two mitral valve plane and apical points on long-axis images. On short-axis images, anterior and posterior right ventricular (RV) insertion points and left ventricular (LV) center points were detected. Model outputs were compared with manual labels assigned by two readers. The trained model was deployed to MRI scanners. RESULTS For the long-axis images, successful detection of cardiac landmarks ranged from 99.7% to 100% for cine images and from 99.2% to 99.5% for LGE images. For the short-axis images, detection rates were 96.6% for cine, 97.6% for LGE, and 98.7% for T1 mapping. The Euclidean distances between model-assigned and manually assigned labels ranged from 2 to 3.5 mm for different landmarks, indicating close agreement between model-derived landmarks and manually assigned labels. For all views and imaging sequences, no differences between the models' assessment of images and the readers' assessment of images were found for the anterior RV insertion angle or LV length. Model inference for a typical cardiac cine series took 610 msec with the graphics processing unit and 5.6 seconds with central processing unit. CONCLUSION A CNN was developed for landmark detection on both long- and short-axis CMR images acquired with cine, LGE, and T1 mapping sequences, and the accuracy of the CNN was comparable with the interreader variation.Keywords: Cardiac, Heart, Convolutional Neural Network (CNN), Deep Learning Algorithms, Machine Learning Algorithms, Feature Detection, Quantification, Supervised Learning, MR Imaging Supplemental material is available for this article. Published under a CC BY 4.0 license.
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Affiliation(s)
- Hui Xue
- From the National Heart, Lung, and Blood Institute, National
Institutes of Health, 10 Center Dr, Bethesda, MD 20892 (H.X., P.K.); Barts Heart
Centre, National Health Service, London, England (J.A., J.C.M., R.H.D.); and
National Amyloidosis Centre, Royal Free Hospital, London, England (M.F.)
| | - Jessica Artico
- From the National Heart, Lung, and Blood Institute, National
Institutes of Health, 10 Center Dr, Bethesda, MD 20892 (H.X., P.K.); Barts Heart
Centre, National Health Service, London, England (J.A., J.C.M., R.H.D.); and
National Amyloidosis Centre, Royal Free Hospital, London, England (M.F.)
| | - Marianna Fontana
- From the National Heart, Lung, and Blood Institute, National
Institutes of Health, 10 Center Dr, Bethesda, MD 20892 (H.X., P.K.); Barts Heart
Centre, National Health Service, London, England (J.A., J.C.M., R.H.D.); and
National Amyloidosis Centre, Royal Free Hospital, London, England (M.F.)
| | - James C. Moon
- From the National Heart, Lung, and Blood Institute, National
Institutes of Health, 10 Center Dr, Bethesda, MD 20892 (H.X., P.K.); Barts Heart
Centre, National Health Service, London, England (J.A., J.C.M., R.H.D.); and
National Amyloidosis Centre, Royal Free Hospital, London, England (M.F.)
| | - Rhodri H. Davies
- From the National Heart, Lung, and Blood Institute, National
Institutes of Health, 10 Center Dr, Bethesda, MD 20892 (H.X., P.K.); Barts Heart
Centre, National Health Service, London, England (J.A., J.C.M., R.H.D.); and
National Amyloidosis Centre, Royal Free Hospital, London, England (M.F.)
| | - Peter Kellman
- From the National Heart, Lung, and Blood Institute, National
Institutes of Health, 10 Center Dr, Bethesda, MD 20892 (H.X., P.K.); Barts Heart
Centre, National Health Service, London, England (J.A., J.C.M., R.H.D.); and
National Amyloidosis Centre, Royal Free Hospital, London, England (M.F.)
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20
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Ferrazzi G, McElroy S, Neji R, Kunze KP, Nazir MS, Speier P, Stäb D, Forman C, Razavi R, Chiribiri A, Roujol S. All-systolic first-pass myocardial rest perfusion at a long saturation time using simultaneous multi-slice imaging and compressed sensing acceleration. Magn Reson Med 2021; 86:663-676. [PMID: 33749026 PMCID: PMC7611406 DOI: 10.1002/mrm.28712] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2020] [Revised: 12/17/2020] [Accepted: 01/11/2021] [Indexed: 12/14/2022]
Abstract
PURPOSE To enable all-systolic first-pass rest myocardial perfusion with long saturation times. To investigate the change in perfusion contrast and dark rim artefacts through simulations and surrogate measurements. METHODS Simulations were employed to investigate optimal saturation time for myocardium-perfusion defect contrast and blood-to-myocardium signal ratios. Two saturation recovery blocks with long/short saturation times (LTS/STS) were employed to image 3 slices at end-systole and diastole. Simultaneous multi-slice balanced steady state free precession imaging and compressed sensing acceleration were combined. The sequence was compared to a 3 slice-by-slice clinical protocol in 10 patients. Quantitative assessment of myocardium-peak pre contrast and blood-to-myocardium signal ratios, as well as qualitative assessment of perceived SNR, image quality, blurring, and dark rim artefacts, were performed. RESULTS Simulations showed that with a bolus of 0.075 mmol/kg, a LTS of 240-470 ms led to a relative increase in myocardium-perfusion defect contrast of 34% ± 9%-28% ± 27% than a STS = 120 ms, while reducing blood-to-myocardium signal ratio by 18% ± 10%-32% ± 14% at peak myocardium. With a bolus of 0.05 mmol/kg, LTS was 320-570 ms with an increase in myocardium-perfusion defect contrast of 63% ± 13%-62% ± 29%. Across patients, LTS led to an average increase in myocardium-peak pre contrast of 59% (P < .001) at peak myocardium and a lower blood-to-myocardium signal ratio of 47% (P < .001) and 15% (P < .001) at peak blood/myocardium. LTS had improved motion robustness (P = .002), image quality (P < .001), and decreased dark rim artefacts (P = .008) than the clinical protocol. CONCLUSION All-systolic rest perfusion can be achieved by combining simultaneous multi-slice and compressed sensing acceleration, enabling 3-slice cardiac coverage with reduced motion and dark rim artefacts. Numerical simulations indicate that myocardium-perfusion defect contrast increases at LTS.
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Affiliation(s)
- Giulio Ferrazzi
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
- IRCCS San Camillo Hospital, Venice, Italy
| | - Sarah McElroy
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Radhouene Neji
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
- MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom
| | - Karl P. Kunze
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
- MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom
| | - Muhummad Sohaib Nazir
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Peter Speier
- Cardiovascular MR predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Daniel Stäb
- MR Research Collaborations, Siemens Healthcare Limited, Melbourne, Australia
| | - Christoph Forman
- Cardiovascular MR predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Reza Razavi
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Amedeo Chiribiri
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Sébastien Roujol
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
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Ryu K, Lee JH, Nam Y, Gho SM, Kim HS, Kim DH. Accelerated multicontrast reconstruction for synthetic MRI using joint parallel imaging and variable splitting networks. Med Phys 2021; 48:2939-2950. [PMID: 33733464 DOI: 10.1002/mp.14848] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2020] [Revised: 03/12/2021] [Accepted: 03/12/2021] [Indexed: 11/10/2022] Open
Abstract
PURPOSE Synthetic magnetic resonance imaging (MRI) requires the acquisition of multicontrast images to estimate quantitative parameter maps, such as T1 , T2 , and proton density (PD). The study aims to develop a multicontrast reconstruction method based on joint parallel imaging (JPI) and joint deep learning (JDL) to enable further acceleration of synthetic MRI. METHODS The JPI and JDL methods are extended and combined to improve reconstruction for better-quality, synthesized images. JPI is performed as a first step to estimate the missing k-space lines, and JDL is then performed to correct and refine the previous estimate with a trained neural network. For the JDL architecture, the original variable splitting network (VS-Net) is modified and extended to form a joint variable splitting network (JVS-Net) to apply to multicontrast reconstructions. The proposed method is designed and tested for multidynamic multiecho (MDME) images with Cartesian uniform under-sampling using acceleration factors between 4 and 8. RESULTS It is demonstrated that the normalized root-mean-square error (nRMSE) is lower and the structural similarity index measure (SSIM) values are higher with the proposed method compared to both the JPI and JDL methods individually. The method also demonstrates the potential to produce a set of synthesized contrast-weighted images that closely resemble those from the fully sampled acquisition without erroneous artifacts. CONCLUSION Combining JPI and JDL enables the reconstruction of highly accelerated synthetic MRIs.
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Affiliation(s)
- Kanghyun Ryu
- Department of Radiology, Stanford University, Stanford, CA, USA.,Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Jae-Hun Lee
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Yoonho Nam
- Department of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea
| | - Sung-Min Gho
- MR Collaboration and Development, GE Healthcare, Seoul, Republic of Korea
| | - Ho-Sung Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Dong-Hyun Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
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22
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Stępień I, Obuchowicz R, Piórkowski A, Oszust M. Fusion of Deep Convolutional Neural Networks for No-Reference Magnetic Resonance Image Quality Assessment. SENSORS 2021; 21:s21041043. [PMID: 33546412 PMCID: PMC7913522 DOI: 10.3390/s21041043] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 01/28/2021] [Accepted: 01/29/2021] [Indexed: 12/02/2022]
Abstract
The quality of magnetic resonance images may influence the diagnosis and subsequent treatment. Therefore, in this paper, a novel no-reference (NR) magnetic resonance image quality assessment (MRIQA) method is proposed. In the approach, deep convolutional neural network architectures are fused and jointly trained to better capture the characteristics of MR images. Then, to improve the quality prediction performance, the support vector machine regression (SVR) technique is employed on the features generated by fused networks. In the paper, several promising network architectures are introduced, investigated, and experimentally compared with state-of-the-art NR-IQA methods on two representative MRIQA benchmark datasets. One of the datasets is introduced in this work. As the experimental validation reveals, the proposed fusion of networks outperforms related approaches in terms of correlation with subjective opinions of a large number of experienced radiologists.
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Affiliation(s)
- Igor Stępień
- Doctoral School of Engineering and Technical Sciences at the Rzeszow University of Technology, al. Powstancow Warszawy 12, 35-959 Rzeszow, Poland;
| | - Rafał Obuchowicz
- Department of Diagnostic Imaging, Jagiellonian University Medical College, 19 Kopernika Street, 31-501 Cracow, Poland;
| | - Adam Piórkowski
- Department of Biocybernetics and Biomedical Engineering, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Cracow, Poland;
| | - Mariusz Oszust
- Department of Computer and Control Engineering, Rzeszow University of Technology, W. Pola 2, 35-959 Rzeszow, Poland
- Correspondence:
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23
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Sandino CM, Lai P, Vasanawala SS, Cheng JY. Accelerating cardiac cine MRI using a deep learning-based ESPIRiT reconstruction. Magn Reson Med 2021; 85:152-167. [PMID: 32697891 PMCID: PMC7722220 DOI: 10.1002/mrm.28420] [Citation(s) in RCA: 73] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Revised: 06/17/2020] [Accepted: 06/18/2020] [Indexed: 12/29/2022]
Abstract
PURPOSE To propose a novel combined parallel imaging and deep learning-based reconstruction framework for robust reconstruction of highly accelerated 2D cardiac cine MRI data. METHODS We propose DL-ESPIRiT, an unrolled neural network architecture that utilizes an extended coil sensitivity model to address SENSE-related field-of-view (FOV) limitations in previously proposed deep learning-based reconstruction frameworks. Additionally, we propose a novel neural network design based on (2+1)D spatiotemporal convolutions to produce more accurate dynamic MRI reconstructions than conventional 3D convolutions. The network is trained on fully sampled 2D cardiac cine datasets collected from 11 healthy volunteers with IRB approval. DL-ESPIRiT is compared against a state-of-the-art parallel imaging and compressed sensing method known as l 1 -ESPIRiT. The reconstruction accuracy of both methods is evaluated on retrospectively undersampled datasets (R = 12) with respect to standard image quality metrics as well as automatic deep learning-based segmentations of left ventricular volumes. Feasibility of DL-ESPIRiT is demonstrated on two prospectively undersampled datasets acquired in a single heartbeat per slice. RESULTS The (2+1)D DL-ESPIRiT method produces higher fidelity image reconstructions when compared to l 1 -ESPIRiT reconstructions with respect to standard image quality metrics (P < .001). As a result of improved image quality, segmentations made from (2+1)D DL-ESPIRiT images are also more accurate than segmentations from l 1 -ESPIRiT images. CONCLUSIONS DL-ESPIRiT synergistically combines a robust parallel imaging model and deep learning-based priors to produce high-fidelity reconstructions of retrospectively undersampled 2D cardiac cine data acquired with reduced FOV. Although a proof-of-concept is shown, further experiments are necessary to determine the efficacy of DL-ESPIRiT in prospectively undersampled data.
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Affiliation(s)
| | - Peng Lai
- Applied Sciences Laboratory, GE Healthcare, Menlo Park, CA, USA
| | | | - Joseph Y Cheng
- Department of Radiology, Stanford University, Stanford, CA, USA
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24
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Ke Z, Cheng J, Ying L, Zheng H, Zhu Y, Liang D. An unsupervised deep learning method for multi-coil cine MRI. ACTA ACUST UNITED AC 2020; 65:235041. [DOI: 10.1088/1361-6560/abaffa] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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25
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Abstract
Classification of heart failure is based on the left ventricular ejection fraction (EF): preserved EF, midrange EF, and reduced EF. There remains an unmet need for further heart failure phenotyping of ventricular structure-function relationships. Because of high spatiotemporal resolution, cardiac magnetic resonance (CMR) remains the reference modality for quantification of ventricular contractile function. The authors aim to highlight novel frameworks, including theranostic use of ferumoxytol, to enable more efficient evaluation of ventricular function in heart failure patients who are also frequently anemic, and to discuss emerging quantitative CMR approaches for evaluation of ventricular structure-function relationships in heart failure.
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26
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Liu Y, Yi Z, Zhao Y, Chen F, Feng Y, Guo H, Leong ATL, Wu EX. Calibrationless parallel imaging reconstruction for multislice MR data using low-rank tensor completion. Magn Reson Med 2020; 85:897-911. [PMID: 32966651 DOI: 10.1002/mrm.28480] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Revised: 07/26/2020] [Accepted: 07/27/2020] [Indexed: 12/16/2022]
Abstract
PURPOSE To provide joint calibrationless parallel imaging reconstruction of highly accelerated multislice 2D MR k-space data. METHODS Adjacent image slices in multislice MR data have similar coil sensitivity maps, spatial support, and image content. Such similarities can be utilized to improve image quality by reconstructing multiple slices jointly with low-rank tensor completion. Specifically, the multichannel k-space data from multiple slices are constructed into a block-wise Hankel tensor and iteratively updated by promoting tensor low-rankness through higher-order SVD. This multislice block-wise Hankel tensor completion was implemented for 2D spiral and Cartesian k-space undersampling where sampling patterns vary between adjacent slices. The approach was evaluated with human brain MR data and compared to the traditional single-slice simultaneous autocalibrating and k-space estimation reconstruction. RESULTS The proposed multislice block-wise Hankel tensor completion approach robustly reconstructed highly undersampled multislice 2D spiral and Cartesian data. It produced substantially lower level of artifacts compared to the traditional single-slice simultaneous autocalibrating and k-space estimation reconstruction. Quantitative evaluation using error maps and root mean square error demonstrated its significantly improved performance in terms of residual artifacts and root mean square error. CONCLUSION Our proposed multislice block-wise Hankel tensor completion method exploits the similar coil sensitivity and image content within multislice MR data through a tensor completion framework. It offers a new and effective approach to acquire and reconstruct highly undersampled multislice MR data in a calibrationless manner.
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Affiliation(s)
- Yilong Liu
- Laboratory of Biomedical Imaging and Signal Processing, the University of Hong Kong, Hong Kong SAR, People's Republic of China.,Department of Electrical and Electronic Engineering, the University of Hong Kong, Hong Kong SAR, People's Republic of China
| | - Zheyuan Yi
- Laboratory of Biomedical Imaging and Signal Processing, the University of Hong Kong, Hong Kong SAR, People's Republic of China.,Department of Electrical and Electronic Engineering, the University of Hong Kong, Hong Kong SAR, People's Republic of China.,Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, People's Republic of China
| | - Yujiao Zhao
- Laboratory of Biomedical Imaging and Signal Processing, the University of Hong Kong, Hong Kong SAR, People's Republic of China.,Department of Electrical and Electronic Engineering, the University of Hong Kong, Hong Kong SAR, People's Republic of China
| | - Fei Chen
- Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, People's Republic of China
| | - Yanqiu Feng
- School of Biomedical Engineering, Southern Medical University, Guangzhou, People's Republic of China
| | - Hua Guo
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, People's Republic of China
| | - Alex T L Leong
- Laboratory of Biomedical Imaging and Signal Processing, the University of Hong Kong, Hong Kong SAR, People's Republic of China.,Department of Electrical and Electronic Engineering, the University of Hong Kong, Hong Kong SAR, People's Republic of China
| | - Ed X Wu
- Laboratory of Biomedical Imaging and Signal Processing, the University of Hong Kong, Hong Kong SAR, People's Republic of China.,Department of Electrical and Electronic Engineering, the University of Hong Kong, Hong Kong SAR, People's Republic of China
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27
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Li H, Metze P, Abaei A, Rottbauer W, Just S, Lu Q, Rasche V. Feasibility of real-time cardiac MRI in mice using tiny golden angle radial sparse. NMR IN BIOMEDICINE 2020; 33:e4300. [PMID: 32227427 DOI: 10.1002/nbm.4300] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Revised: 03/02/2020] [Accepted: 03/05/2020] [Indexed: 06/10/2023]
Abstract
Cardiovascular magnetic resonance imaging has proven valuable for the assessment of structural and functional cardiac abnormalities. Even although it is an established imaging method in small animals, the long acquisition times of gated or self-gated techniques still limit its widespread application. In this study, the application of tiny golden angle radial sparse MRI (tyGRASP) for real-time cardiac imaging was tested in 12 constitutive nexilin (Nexn) knock-out (KO) mice, both heterozygous (Het, N = 6) and wild-type (WT, N = 6), and the resulting functional parameters were compared with a well-established self-gating approach. Real-time images were reconstructed for different temporal resolutions of between 16.8 and 79.8 ms per image. The suggested approach was additionally tested for dobutamine stress and qualitative first-pass perfusion imaging. Measurements were repeated twice within 2 weeks for reproducibility assessment. In direct comparison with the high-quality, self-gated technique, the real-time approach did not show any significant differences in global function parameters for acquisition times below 50 ms (rest) and 31.5 ms (stress). Compared with WT, the end-diastolic volume (EDV) and end-systolic volume (ESV) were markedly higher (P < 0.05) and the ejection fraction (EF) was significantly lower in the Het Nexn-KO mice at rest (P < 0.001). For the stress investigation, a clear decrease of EDV and ESV, and an increase in EF, but maintained stroke volume, could be observed in both groups. Combined with ECG-triggering, tyGRASP provided first-pass perfusion data with a temporal resolution of one image per heartbeat, allowing the quantitative assessment of upslope curves in the blood-pool and myocardium. Excellent inter-study reproducibility was achieved in all the functional parameters. The tyGRASP is a valuable real-time MRI technique for mice, which significantly reduces the scan time in preclinical cardiac functional imaging, providing sufficient image quality for deriving accurate functional parameters, and has the potential to investigate real-time and beat-to-beat changes.
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Affiliation(s)
- Hao Li
- Core Facility Small Animal Imaging, Ulm University, Ulm, Germany
- Department of Cardiology, The Second Hospital of Shandong University, Jinan, China
| | - Patrick Metze
- Department of Internal Medicine II, Ulm University Medical Center, Ulm, Germany
| | - Alireza Abaei
- Core Facility Small Animal Imaging, Ulm University, Ulm, Germany
| | - Wolfgang Rottbauer
- Department of Internal Medicine II, Ulm University Medical Center, Ulm, Germany
| | - Steffen Just
- Department of Internal Medicine II, Ulm University Medical Center, Ulm, Germany
| | - Qinghua Lu
- Department of Cardiology, The Second Hospital of Shandong University, Jinan, China
| | - Volker Rasche
- Core Facility Small Animal Imaging, Ulm University, Ulm, Germany
- Department of Internal Medicine II, Ulm University Medical Center, Ulm, Germany
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28
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Chen H, Xie RM, Zhao L, Zhang XY, Zhao YK, Wang Z, Xie GX, Ma XH. Evaluation of left ventricular strain in patients with arrhythmia based on the 3T MR temporal parallel acquisition technique. Sci Rep 2020; 10:9342. [PMID: 32518330 PMCID: PMC7283215 DOI: 10.1038/s41598-020-66315-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Accepted: 05/14/2020] [Indexed: 11/09/2022] Open
Abstract
Most of the current studies on myocardial strain are mainly applied in patients with sinus rhythm because the image quality of arrhythmias obtained with conventional scanning sequences does not meet diagnostic needs. Here, we intend to assess left ventricular (LV) global myocardial strain in patients with arrhythmias with 3 Tesla magnetic resonance (MR) and a new cine sequence. Thirty-three patients with arrhythmia and forty-eight subjects with sinus rhythm were enrolled in the study. LV myocardial thickness, cardiac function, myocardial strain and the apparent contrast-to-noise ratio (CNR) were all measured and compared using images generated by the real-time temporal parallel acquisition technique (TPAT) and the conventional cine sequence. In the arrhythmia group, the image quality of real-time TPAT was significantly better than that of the conventional cine sequence. In the arrhythmia group, the LV global peak radial strain and global peak circumferential strain values of real-time TPAT were significantly different from those of the conventional technique (radial strain, conventional: 20.27 ± 15.39 vs. TPAT: 24.14 ± 15.85, p = 0.007; circumferential strain, conventional:-12.06 ± 6.60 vs. TPAT: -13.71 ± 6.31, p = 0.015). There was no significant difference in global peak longitudinal strain between real-time TPAT and the conventional technique (-10.94 ± 4.66 vs. -10.70 ± 5.96, p = 0.771). There was no significant difference in the cardiac function parameters between the two techniques (p > 0.05), but there was a significant difference in 12 segments of the LV wall thickness between the two sequences (p < 0.05). In the sinus rhythm group, image quality using real-time TPAT was comparable to that using the conventional technique, and there was no significant difference in any of the indices (p > 0.05). Real-time TPAT is an effective method for detection of left ventricular myocardial deformation in patients with arrhythmia.
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Affiliation(s)
- Hui Chen
- Department of Radiology, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, China.,Department of Interventional Diagnosis and Treatment, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, China
| | - Ru-Ming Xie
- Department of Radiology, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, China
| | - Lei Zhao
- Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, Chaoyang District, Beijing, 100029, China
| | - Xiao-Yong Zhang
- MR Collaborations NE Asia, Siemens Healthcare, Shenzhen, 518000, China
| | - Yi-Ke Zhao
- Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, Chaoyang District, Beijing, 100029, China
| | - Zheng Wang
- Department of Interventional Diagnosis and Treatment, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, China
| | - Guo-Xi Xie
- Department of Biomedical Engineering, School of Basic Medical Science, Guangzhou Medical University, Guangzhou, 511416, China.
| | - Xiao-Hai Ma
- Department of Interventional Diagnosis and Treatment, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, China.
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29
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Najeeb F, Usman M, Aslam I, Qazi SA, Omer H. Respiratory motion-corrected, compressively sampled dynamic MR image reconstruction by exploiting multiple sparsity constraints and phase correlation-based data binning. MAGMA (NEW YORK, N.Y.) 2020; 33:411-419. [PMID: 31754909 DOI: 10.1007/s10334-019-00794-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Revised: 10/10/2019] [Accepted: 10/30/2019] [Indexed: 06/10/2023]
Abstract
INTRODUCTION Cardiac magnetic resonance imaging (cMRI) is a standard method that is clinically used to evaluate the function of the human heart. Respiratory motion during a cMRI scan causes blurring artefacts in the reconstructed images. In conventional MRI, breath holding is used to avoid respiratory motion artefacts, which may be difficult for cardiac patients. MATERIALS AND METHODS This paper proposes a method in which phase correlation-based binning, followed by image registration-based sparsity along with spatio-temporal sparsity, is incorporated into the standard low rank + sparse (L+S) reconstruction for free-breathing cardiac cine MRI. The proposed method is validated on clinical data and simulated free-breathing cardiac cine data for different acceleration factors (AFs). The reconstructed images are analysed using visual assessment, artefact power (AP) and root-mean-square error (RMSE). The results of the proposed method are compared with the contemporary motion-corrected compressed sensing (MC-CS) method given in the literature. RESULTS Our results show that the proposed method successfully reconstructs the motion-corrected images from respiratory motion-corrupted, compressively sampled cardiac cine MR data, e.g., there is 26% and 24% improvement in terms of AP and RMSE values, respectively, at AF = 4 and 20% and 16.04% improvement in terms of AP and RMSE values, respectively, at AF = 8 in the reconstruction results from the proposed method for the cardiac phantom cine data. CONCLUSION The proposed method achieves significant improvement in the AP and RMSE values at different AFs for both the phantom and in vivo data.
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Affiliation(s)
- Faisal Najeeb
- Department of Electrical and Computer Engineering, COMSATS University Islamabad, Islamabad, Pakistan.
| | - Muhammad Usman
- Department of Computer Science, University College London, London, UK
| | - Ibtisam Aslam
- Department of Electrical and Computer Engineering, COMSATS University Islamabad, Islamabad, Pakistan
| | - Sohaib A Qazi
- Department of Electrical and Computer Engineering, COMSATS University Islamabad, Islamabad, Pakistan
| | - Hammad Omer
- Department of Electrical and Computer Engineering, COMSATS University Islamabad, Islamabad, Pakistan
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30
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Mansour R, Thibodeau Antonacci A, Bilodeau L, Vazquez Romaguera L, Cerny M, Huet C, Gilbert G, Tang A, Kadoury S. Impact of temporal resolution and motion correction for dynamic contrast-enhanced MRI of the liver using an accelerated golden-angle radial sequence. Phys Med Biol 2020; 65:085004. [PMID: 32084661 DOI: 10.1088/1361-6560/ab78be] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
This paper presents a prospective study evaluating the impact on image quality and quantitative dynamic contrast-enhanced (DCE)-MRI perfusion parameters when varying the number of respiratory motion states when using an eXtra-Dimensional Golden-Angle Radial Sparse Parallel (XD-GRASP) MRI sequence. DCE acquisition was performed using a 3D stack-of-stars gradient-echo golden-angle radial acquisition in free-breathing with 100 spokes per motion state and temporal resolution of 6 s/volume, and using a non-rigid motion compensation to align different motion states. Parametric analysis was conducted using a dual-input single-compartment model. Nonparametric analysis was performed on the time-intensity curves. A total of 22 hepatocellular carcinomas (size: 11-52 mm) were evaluated. XD-GRASP reconstructed with increasing number of spokes for each motion state increased the signal-to-noise ratio (SNR) (p < 0.05) but decreased temporal resolution (0.04 volume/s vs 0.17 volume/s for one motion state) (p < 0.05). A visual scoring by an experienced radiologist show no change between increasing number of motion states with same number of spokes using the Likert score. The normalized maximum intensity time ratio, peak enhancement ratio and tumor arterial fraction increased with decreasing number of motion states (p < 0.05) while the transfer constant from the portal venous plasma to the surrounding tissue significantly decreased (p < 0.05). These same perfusion parameters show a significant difference in case of tumor displacement more than 1 cm (p < 0.05) whereas in the opposite case there was no significant variation. While a higher number of motion states and higher number of spokes improves SNR, the resulting lower temporal resolution can influence quantitative parameters that capture rapid signal changes. Finally, fewer displacement compensation is advantageous with lower number of motion state due to the higher temporal resolution. XD-GRASP can be used to perform quantitative perfusion measures in the liver, but the number of motion states may significantly alter some quantitative parameters.
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Affiliation(s)
- Rihab Mansour
- Centre hospitalier de l'Université de Montréal (CHUM) Research center, Montréal, QC, Canada
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31
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Obuchowicz R, Oszust M, Bielecka M, Bielecki A, Piórkowski A. Magnetic Resonance Image Quality Assessment by Using Non-Maximum Suppression and Entropy Analysis. ENTROPY 2020; 22:e22020220. [PMID: 33285994 PMCID: PMC7516651 DOI: 10.3390/e22020220] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/05/2020] [Revised: 02/04/2020] [Accepted: 02/13/2020] [Indexed: 12/17/2022]
Abstract
An investigation of diseases using magnetic resonance (MR) imaging requires automatic image quality assessment methods able to exclude low-quality scans. Such methods can be also employed for an optimization of parameters of imaging systems or evaluation of image processing algorithms. Therefore, in this paper, a novel blind image quality assessment (BIQA) method for the evaluation of MR images is introduced. It is observed that the result of filtering using non-maximum suppression (NMS) strongly depends on the perceptual quality of an input image. Hence, in the method, the image is first processed by the NMS with various levels of acceptable local intensity difference. Then, the quality is efficiently expressed by the entropy of a sequence of extrema numbers obtained with the thresholded NMS. The proposed BIQA approach is compared with ten state-of-the-art techniques on a dataset containing MR images and subjective scores provided by 31 experienced radiologists. The Pearson, Spearman, Kendall correlation coefficients and root mean square error for the method assessing images in the dataset were 0.6741, 0.3540, 0.2428, and 0.5375, respectively. The extensive experimental evaluation of the BIQA methods reveals that the introduced measure outperforms related techniques by a large margin as it correlates better with human scores.
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Affiliation(s)
- Rafał Obuchowicz
- Department of Diagnostic Imaging, Jagiellonian University Medical College, 19 Kopernika Street, 31-501 Cracow, Poland;
| | - Mariusz Oszust
- Department of Computer and Control Engineering, Rzeszow University of Technology, W. Pola 2, 35-959 Rzeszow, Poland;
| | - Marzena Bielecka
- Faculty of Geology, Geophysics and Environmental Protection, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Cracow, Poland
- Correspondence:
| | - Andrzej Bielecki
- Faculty of Electrical Engineering, Automation, Computer Science and Biomedical Engineering, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Cracow, Poland;
| | - Adam Piórkowski
- Department of Biocybernetics and Biomedical Engineering, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Cracow, Poland;
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32
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Oszust M, Piórkowski A, Obuchowicz R. No‐reference image quality assessment of magnetic resonance images with high‐boost filtering and local features. Magn Reson Med 2020; 84:1648-1660. [DOI: 10.1002/mrm.28201] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Revised: 01/14/2020] [Accepted: 01/16/2020] [Indexed: 12/31/2022]
Affiliation(s)
- Mariusz Oszust
- Department of Computer and Control Engineering Rzeszów University of Technology Rzeszów Poland
| | - Adam Piórkowski
- Department of Biocybernetics and Biomedical Engineering AGH University of Science and Technology Kraków Poland
| | - Rafał Obuchowicz
- Department of Diagnostic Imaging Jagiellonian University Medical College Kraków Poland
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33
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Xue H, Brown LA, Nielles-Vallespin S, Plein S, Kellman P. Automatic in-line quantitative myocardial perfusion mapping: Processing algorithm and implementation. Magn Reson Med 2020; 83:712-730. [PMID: 31441550 PMCID: PMC8400845 DOI: 10.1002/mrm.27954] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Revised: 06/27/2019] [Accepted: 07/27/2019] [Indexed: 02/03/2023]
Abstract
PURPOSE Quantitative myocardial perfusion mapping has advantages over qualitative assessment, including the ability to detect global flow reduction. However, it is not clinically available and remains a research tool. Building upon the previously described imaging sequence, this study presents algorithm and implementation of an automated solution for inline perfusion flow mapping with step by step performance characterization. METHODS Proposed workflow consists of motion correction (MOCO), arterial input function blood detection, intensity to gadolinium concentration conversion, and pixel-wise mapping. A distributed kinetics model, blood-tissue exchange model, is implemented, computing pixel-wise maps of myocardial blood flow (mL/min/g), permeability-surface-area product (mL/min/g), blood volume (mL/g), and interstitial volume (mL/g). RESULTS Thirty healthy subjects (11 men; 26.4 ± 10.4 years) were recruited and underwent adenosine stress perfusion cardiovascular MR. Mean MOCO quality score was 3.6 ± 0.4 for stress and 3.7 ± 0.4 for rest. Myocardial Dice similarity coefficients after MOCO were significantly improved (P < 1e-6), 0.87 ± 0.05 for stress and 0.86 ± 0.06 for rest. Arterial input function peak gadolinium concentration was 4.4 ± 1.3 mmol/L at stress and 5.2 ± 1.5 mmol/L at rest. Mean myocardial blood flow at stress and rest were 2.82 ± 0.47 mL/min/g and 0.68 ± 0.16 mL/min/g, respectively. The permeability-surface-area product was 1.32 ± 0.26 mL/min/g at stress and 1.09 ± 0.21 mL/min/g at rest (P < 1e-3). Blood volume was 12.0 ± 0.8 mL/100 g at stress and 9.7 ± 1.0 mL/100 g at rest (P < 1e-9), indicating good adenosine vasodilation response. Interstitial volume was 20.8 ± 2.5 mL/100 g at stress and 20.3 ± 2.9 mL/100 g at rest (P = 0.50). CONCLUSIONS An inline perfusion flow mapping workflow is proposed and demonstrated on normal volunteers. Initial evaluation demonstrates this fully automated solution for the respiratory MOCO, arterial input function left ventricle mask detection, and pixel-wise mapping, from free-breathing myocardial perfusion imaging.
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Affiliation(s)
- Hui Xue
- National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | - Louise A.E. Brown
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | | | - Sven Plein
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Peter Kellman
- National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland
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Everaars H, van Diemen PA, Bom MJ, Schumacher SP, de Winter RW, van de Ven PM, Raijmakers PG, Lammertsma AA, Hofman MBM, van der Geest RJ, Götte MJ, van Rossum AC, Nijveldt R, Danad I, Driessen RS, Knaapen P. Comparison between quantitative cardiac magnetic resonance perfusion imaging and [ 15O]H 2O positron emission tomography. Eur J Nucl Med Mol Imaging 2019; 47:1688-1697. [PMID: 31822958 PMCID: PMC7248026 DOI: 10.1007/s00259-019-04641-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Accepted: 11/26/2019] [Indexed: 12/20/2022]
Abstract
Purpose To compare cardiac magnetic resonance imaging (CMR) with [15O]H2O positron emission tomography (PET) for quantification of absolute myocardial blood flow (MBF) and myocardial flow reserve (MFR) in patients with coronary artery disease (CAD). Methods Fifty-nine patients with stable CAD underwent CMR and [15O]H2O PET. The CMR imaging protocol included late gadolinium enhancement to rule out presence of scar tissue and perfusion imaging using a dual sequence, single bolus technique. Absolute MBF was determined for the three main vascular territories at rest and during vasodilator stress. Results CMR measurements of regional stress MBF and MFR showed only moderate correlation to those obtained using PET (r = 0.39; P < 0.001 for stress MBF and r = 0.36; P < 0.001 for MFR). Bland-Altman analysis revealed a significant bias of 0.2 ± 1.0 mL/min/g for stress MBF and − 0.5 ± 1.2 for MFR. CMR-derived stress MBF and MFR demonstrated area under the curves of respectively 0.72 (95% CI: 0.65 to 0.79) and 0.76 (95% CI: 0.69 to 0.83) and had optimal cutoff values of 2.35 mL/min/g and 2.25 for detecting abnormal myocardial perfusion, defined as [15O]H2O PET-derived stress MBF ≤ 2.3 mL/min/g and MFR ≤ 2.5. Using these cutoff values, CMR and PET were concordant in 137 (77%) vascular territories for stress MBF and 135 (80%) vascular territories for MFR. Conclusion CMR measurements of stress MBF and MFR showed modest agreement to those obtained with [15O]H2O PET. Nevertheless, stress MBF and MFR were concordant between CMR and [15O]H2O PET in 77% and 80% of vascular territories, respectively.
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Affiliation(s)
- Henk Everaars
- Department of Cardiology, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, the Netherlands
| | - Pepijn A van Diemen
- Department of Cardiology, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, the Netherlands
| | - Michiel J Bom
- Department of Cardiology, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, the Netherlands
| | - Stefan P Schumacher
- Department of Cardiology, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, the Netherlands
| | - Ruben W de Winter
- Department of Cardiology, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, the Netherlands
| | - Peter M van de Ven
- Department of Epidemiology and Biostatistics, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, the Netherlands
| | - Pieter G Raijmakers
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, the Netherlands
| | - Adriaan A Lammertsma
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, the Netherlands
| | - Mark B M Hofman
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, the Netherlands
| | - Rob J van der Geest
- Department of Radiology, Leiden University Medical Centers, Leiden, the Netherlands
| | - Marco J Götte
- Department of Cardiology, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, the Netherlands
| | - Albert C van Rossum
- Department of Cardiology, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, the Netherlands
| | - Robin Nijveldt
- Department of Cardiology, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Ibrahim Danad
- Department of Cardiology, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, the Netherlands
| | - Roel S Driessen
- Department of Cardiology, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, the Netherlands
| | - Paul Knaapen
- Department of Cardiology, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, the Netherlands.
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Chieh SW, Kaveh M, Akçakaya M, Moeller S. Self-calibrated interpolation of non-Cartesian data with GRAPPA in parallel imaging. Magn Reson Med 2019; 83:1837-1850. [PMID: 31722128 DOI: 10.1002/mrm.28033] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 08/20/2019] [Accepted: 09/17/2019] [Indexed: 12/22/2022]
Abstract
PURPOSE To develop a non-Cartesian k-space reconstruction method using self-calibrated region-specific interpolation kernels for highly accelerated acquisitions. METHODS In conventional non-Cartesian GRAPPA with through-time GRAPPA (TT-GRAPPA), the use of region-specific interpolation kernels has demonstrated improved reconstruction quality in dynamic imaging for highly accelerated acquisitions. However, TT-GRAPPA requires the acquisition of a large number of separate calibration scans. To reduce the overall imaging time, we propose Self-calibrated Interpolation of Non-Cartesian data with GRAPPA (SING) to self-calibrate region-specific interpolation kernels from dynamic undersampled measurements. The SING method synthesizes calibration data to adapt to the distinct shape of each region-specific interpolation kernel geometry, and uses a novel local k-space regularization through an extension of TT-GRAPPA. This calibration approach is used to reconstruct non-Cartesian images at high acceleration rates while mitigating noise amplification. The reconstruction quality of SING is compared with conjugate-gradient SENSE and TT-GRAPPA in numerical phantoms and in vivo cine data sets. RESULTS In both numerical phantom and in vivo cine data sets, SING offers visually and quantitatively similar reconstruction quality to TT-GRAPPA, and provides improved reconstruction quality over conjugate-gradient SENSE. Furthermore, temporal fidelity in SING and TT-GRAPPA is similar for the same acceleration rates. G-factor evaluation over the heart shows that SING and TT-GRAPPA provide similar noise amplification at moderate and high rates. CONCLUSION The proposed SING reconstruction enables significant improvement of acquisition efficiency for calibration data, while matching the reconstruction performance of TT-GRAPPA.
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Affiliation(s)
- Seng-Wei Chieh
- Electrical and Computer Engineering, University of Minnesota, Minneapolis, Minnesota
| | - Mostafa Kaveh
- Electrical and Computer Engineering, University of Minnesota, Minneapolis, Minnesota
| | - Mehmet Akçakaya
- Electrical and Computer Engineering, University of Minnesota, Minneapolis, Minnesota.,Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota
| | - Steen Moeller
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota
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36
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Moser P, Bogner W, Hingerl L, Heckova E, Hangel G, Motyka S, Trattnig S, Strasser B. Non-Cartesian GRAPPA and coil combination using interleaved calibration data - application to concentric-ring MRSI of the human brain at 7T. Magn Reson Med 2019; 82:1587-1603. [PMID: 31183893 PMCID: PMC6772100 DOI: 10.1002/mrm.27822] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Revised: 04/29/2019] [Accepted: 05/01/2019] [Indexed: 12/12/2022]
Abstract
PURPOSE Proton MR spectroscopic imaging (MRSI) benefits from B0 ≥ 7T and multichannel receive coils, promising substantial resolution improvements. However, MRSI acquisition with high spatial resolution requires efficient acceleration and coil combination. To speed up the already-fast sampling via concentric rings, we implemented additional, non-Cartesian, hybrid through-time/through-k-space (tt/tk)-generalized autocalibrating partially parallel acquisition (GRAPPA). A new multipurpose interleaved calibration scan (interleaved MUSICAL) acquires reference data for both coil combination and PI. This renders the reconstruction process (especially PI) less sensitive to instabilities. METHODS Six healthy volunteers were scanned at 7T. Three calibration datasets for coil combination and PI were recorded: a) iMUSICAL, b) static MUSICAL as prescan, c) moved MUSICAL as prescan with misaligned head position. The coil combination performance, including motion sensitivity, of iMUSICAL was compared to MUSICAL for single-slice free induction decay (FID)-MRSI. Through-time/through-k-space-GRAPPA with constant/variable-density undersampling was evaluated on the same data, comparing the three calibration datasets. Additionally, the proposed method was successfully applied to 3D whole-brain FID-MRSI. RESULTS Using iMUSICAL for coil combination yielded the highest signal-to-noise ratio (SNR) (+9%) and lowest Cramer-Rao lower bounds (CRLBs) (-6%) compared to both MUSICAL approaches, with similar metabolic map quality. Also, excellent mean g-factors of 1.07 and low residual lipid aliasing were obtained when using iMUSICAL as calibration data for two-fold, variable-density undersampling, while significantly degraded metabolic maps were obtained using the misaligned MUSICAL calibration data. CONCLUSION Through-time/through-k-space-GRAPPA can accelerate already time-efficient non-Cartesian spatial-spectral 2D/3D-MRSI encoding even further. Particularly promising results have been achieved using iMUSICAL as a robust, interleaved multipurpose calibration for MRSI reconstruction, without extra calibration prescan.
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Affiliation(s)
- Philipp Moser
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Lukas Hingerl
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Eva Heckova
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Gilbert Hangel
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Stanislav Motyka
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Siegfried Trattnig
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria.,Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria
| | - Bernhard Strasser
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria.,Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
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37
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Wang H, Jia S, Chang Y, Zhu Y, Zou C, Li Y, Liu X, Zheng H, Liang D. Improving GRAPPA reconstruction using joint nonlinear kernel mapped and phase conjugated virtual coils. Phys Med Biol 2019; 64:14NT01. [PMID: 31167169 DOI: 10.1088/1361-6560/ab274d] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
To improve the reconstruction condition and alleviate the noise amplification of GRAPPA reconstruction by aggregating the phase conjugated and nonlinear kernel mapped coils with the original physical coil. Nonlinear GRAPPA (NL-GRAPPA) is a kernel-based non-iterative approach which can reduce noise-induced error in GRAPPA reconstruction. And virtual conjugate coil (VCC) embeds the conjugate symmetric property of k-space into GRAPPA data synthesis to improve reconstruction condition. This work proposed NL-VCC-GRAPPA to jointly utilize the nonlinear mapped virtual coil and phase conjugated virtual coil to further reduce noise amplification in parallel imaging. In vivo static and dynamic 2D imaging accelerated by uniform undersampling schemes were performed to evaluate the proposed method in terms of visual image quality, root-mean-square-error (RMSE), and geometry factor (g-factor). The effects of acceleration factors, calibration data size and kernel shape on the proposed model were also separately analyzed and discussed. The proposed method illustrated improved visual image quality evidenced by reduced retrospective RMSE and prospective g-factor comparing with conventional GRAPPA and the recently proposed iterative SENSE-LORAKS reconstructions. Although a larger amount of calibration data and smaller kernel size were required to stabilize the calibration of fourfold extended kernel for the proposed method, it was non-iterative and relatively insensitive to parameter adjustment in the applications. The proposed NL-VCC-extension to conventional GRAPPA brings visible improvements for imaging scenarios accelerated by the widely available uniform undersampling schemes in a practically efficient manner without iteration.
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Affiliation(s)
- Haifeng Wang
- Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, People's Republic of China. Co-First/Equal Authorship
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38
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Wech T, Kunze KP, Rischpler C, Stäb D, Speier P, Köstler H, Nekolla SG. A compressed sensing accelerated radial MS-CAIPIRINHA technique for extended anatomical coverage in myocardial perfusion studies on PET/MR systems. Phys Med 2019; 64:157-165. [PMID: 31515014 DOI: 10.1016/j.ejmp.2019.06.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Revised: 06/05/2019] [Accepted: 06/17/2019] [Indexed: 10/26/2022] Open
Abstract
PURPOSE Simultaneous acquisition of myocardial first-pass perfusion MRI and 18F-FDG PET viability imaging on integrated whole-body PET/MR hybrid systems synergistically delivers both functional and metabolic information on the tissue state. While PET viability scans are inherently three-dimensional, conventional MR myocardial perfusion imaging is typically performed using only three short-axis slices with a temporal resolution of one RR-interval. To improve the integrated diagnostics, an acquisition and image reconstruction method based on "Multi-Slice Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration (MS-CAIPIRINHA)" was developed extending anatomical coverage for MR perfusion imaging to six short-axis slices per RR-interval. METHODS An ECG-gated radial TurboFLASH MR pulse sequence with dual band excitation was implemented on an integrated whole-body PET/MR system and a model-based reconstruction technique was developed to fully reconstruct the undersampled CAIPIRINHA acquisitions. An 18F-FDG viability PET scan was performed simultaneously to the MR protocol, additionally complemented by a late enhancement MRI acquisition (LGE). RESULTS AND CONCLUSION The developed imaging technique was tested in five patients with known collateralized coronary total occlusions, resulting in improved characterization of perfusion across areas of decreased tissue viability as indicated by the simultaneously determined 18F-FDG uptake. While conventional MR perfusion with only three slice positions was occasionally missing substantial parts of the viable area, the new approach achieved LV coverage only slightly inferior to LGE imaging and therefore better comparable to PET results. The quality of first-pass enhancement curves was comparable between conventional and radial MS-CAIPIRINHA-based acquisitions.
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Affiliation(s)
- Tobias Wech
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Germany; Comprehensive Heart Failure Centre, University Hospital Würzburg, Germany.
| | - Karl P Kunze
- School of Medicine, Department of Nuclear Medicine, Technische Universität München, Germany
| | - Christoph Rischpler
- School of Medicine, Department of Nuclear Medicine, Technische Universität München, Germany; DZHK (Deutsches Zentrum für Herz-Kreislauf-Forschung e.V.), Partner Site Munich Heart Alliance, Munich, Germany; Clinic for Nuclear Medicine, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Daniel Stäb
- Siemens Healthcare Pty Ltd, Melbourne, Australia
| | - Peter Speier
- Magnetic Resonance, Siemens Healthcare GmbH, Erlangen, Germany
| | - Herbert Köstler
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Germany; Comprehensive Heart Failure Centre, University Hospital Würzburg, Germany
| | - Stephan G Nekolla
- School of Medicine, Department of Nuclear Medicine, Technische Universität München, Germany; DZHK (Deutsches Zentrum für Herz-Kreislauf-Forschung e.V.), Partner Site Munich Heart Alliance, Munich, Germany
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39
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Kim KN, Hernandez D, Seo JH, Noh Y, Han Y, Ryu YC, Chung JY. Quantitative assessment of phased array coils with different numbers of receiving channels in terms of signal-to-noise ratio and spatial noise variation in magnetic resonance imaging. PLoS One 2019; 14:e0219407. [PMID: 31276549 PMCID: PMC6611621 DOI: 10.1371/journal.pone.0219407] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Accepted: 06/21/2019] [Indexed: 11/19/2022] Open
Abstract
The neuroimaging of humans using 7T magnetic resonance imaging (MRI) has been conducted using phased array (PA) coils with different numbers of receiving channels. PA coils with a high number of channels may offer parallel imaging (PI) with a high reduction (R)-factor, which is enabled via under-sampling and coil geometry (g) factor, increasing the radiofrequency signal sensitivity provided by a small coil. The goals of this study were to assess and validate the coil performance of PA coils with different numbers of receiver (Rx)-channels in and to propose the coil selection guidelines by visualizing 7T brain images. The combined magnetic flux density (||B1||) distributions of four configurations of PA coils—4-, 8-, 12-, and 16-channel Rx-only mode under the local transmit (Tx) mode of birdcage coils—were evaluated using electromagnetic (EM) calculations. These four configurations of PA coils and a local Tx coil were designed and built for a 7T MRI experiment. For 7T brain imaging experiments, all PA coils with (w/) and without (w/o) R-factors were compared in terms of signal-to-noise ratio (SNR) and spatial noise variation (SNV). EM simulation results clearly demonstrated that PA coils with a high number of Rx channels showed more homogeneously distributed ||B1|| fields than a PA coils with a low number of Rx coils. The results of this study demonstrate that a collection of smaller surface coils can contribute to high RF signal sensitivity in terms of the anatomical coverage of the brain and may facilitate PI. With further improvement in coil technology, researchers and clinicians will be provided with PA coils with different numbers of channels, which can ensure the optimum SNR and PI benefits for 7T brain MR imaging.
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Affiliation(s)
- Kyoung-Nam Kim
- Department of Biomedical Engineering, Gachon University, Incheon, Korea
| | - Daniel Hernandez
- Department of Biomedical Engineering, Gachon University, Incheon, Korea
| | - Jeung-Hoon Seo
- Neuroscience Research Institute, Gachon University, Incheon, Korea
| | - Young Noh
- Department of Neurology, Gachon University Gil Medical Center, Incheon, Korea
| | - Yeji Han
- Department of Biomedical Engineering, Gachon University, Incheon, Korea
| | - Yeun Chul Ryu
- Neuroscience Research Institute, Gachon University, Incheon, Korea
| | - Jun-Young Chung
- Department of Neuroscience, College of Medicine, Gachon University, Incheon, Korea
- * E-mail:
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Takeshima H, Saitoh K, Nitta S, Shiodera T, Takeguchi T, Bannae S, Kuhara S. Estimation of Spatiotemporal Sensitivity Using Band-limited Signals with No Additional Acquisitions for k-t Parallel Imaging. Magn Reson Med Sci 2019. [PMID: 29540620 PMCID: PMC6326766 DOI: 10.2463/mrms.mp.2017-0132] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Purpose: Dynamic MR techniques, such as cardiac cine imaging, benefit from shorter acquisition times. The goal of the present study was to develop a method that achieves short acquisition times, while maintaining a cost-effective reconstruction, for dynamic MRI. k – t sensitivity encoding (SENSE) was identified as the base method to be enhanced meeting these two requirements. Methods: The proposed method achieves a reduction in acquisition time by estimating the spatiotemporal (x – f) sensitivity without requiring the acquisition of the alias-free signals, typical of the k – t SENSE technique. The cost-effective reconstruction, in turn, is achieved by a computationally efficient estimation of the x – f sensitivity from the band-limited signals of the aliased inputs. Such band-limited signals are suitable for sensitivity estimation because the strongly aliased signals have been removed. Results: For the same reduction factor 4, the net reduction factor 4 for the proposed method was significantly higher than the factor 2.29 achieved by k – t SENSE. The processing time is reduced from 4.1 s for k – t SENSE to 1.7 s for the proposed method. The image quality obtained using the proposed method proved to be superior (mean squared error [MSE] ± standard deviation [SD] = 6.85 ± 2.73) compared to the k – t SENSE case (MSE ± SD = 12.73 ± 3.60) for the vertical long-axis (VLA) view, as well as other views. Conclusion: In the present study, k – t SENSE was identified as a suitable base method to be improved achieving both short acquisition times and a cost-effective reconstruction. To enhance these characteristics of base method, a novel implementation is proposed, estimating the x – f sensitivity without the need for an explicit scan of the reference signals. Experimental results showed that the acquisition, computational times and image quality for the proposed method were improved compared to the standard k – t SENSE method.
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Affiliation(s)
- Hidenori Takeshima
- Clinical Application Research Department, Research and Development Center, Canon Medical Systems Corporation.,Analytics AI Laboratory, Corporate Research & Development Center, Toshiba Corporation
| | - Kanako Saitoh
- Analytics AI Laboratory, Corporate Research & Development Center, Toshiba Corporation
| | - Shuhei Nitta
- Analytics AI Laboratory, Corporate Research & Development Center, Toshiba Corporation
| | - Taichiro Shiodera
- Analytics AI Laboratory, Corporate Research & Development Center, Toshiba Corporation
| | - Tomoyuki Takeguchi
- Analytics AI Laboratory, Corporate Research & Development Center, Toshiba Corporation
| | - Shuhei Bannae
- Healthcare ICT Clinical Application Development Department, Healthcare ICT Development Center, Healthcare ICT Division, Canon Medical Systems Corporation
| | - Shigehide Kuhara
- Application Research Group, Clinical Application Research and Development Department, Center for Medical Research and Development, Toshiba Medical.,Department of Medical Radiological Technology, Faculty of Health Sciences, Kyorin University
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Nazir MS, Neji R, Speier P, Reid F, Stäb D, Schmidt M, Forman C, Razavi R, Plein S, Ismail TF, Chiribiri A, Roujol S. Simultaneous multi slice (SMS) balanced steady state free precession first-pass myocardial perfusion cardiovascular magnetic resonance with iterative reconstruction at 1.5 T. J Cardiovasc Magn Reson 2018; 20:84. [PMID: 30526627 PMCID: PMC6287353 DOI: 10.1186/s12968-018-0502-7] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Accepted: 10/24/2018] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Simultaneous-Multi-Slice (SMS) perfusion imaging has the potential to acquire multiple slices, increasing myocardial coverage without sacrificing in-plane spatial resolution. To maximise signal-to-noise ratio (SNR), SMS can be combined with a balanced steady state free precession (bSSFP) readout. Furthermore, application of gradient-controlled local Larmor adjustment (GC-LOLA) can ensure robustness against off-resonance artifacts and SNR loss can be mitigated by applying iterative reconstruction with spatial and temporal regularisation. The objective of this study was to compare cardiovascular magnetic resonance (CMR) myocardial perfusion imaging using SMS bSSFP imaging with GC-LOLA and iterative reconstruction to 3 slice bSSFP. METHODS Two contrast-enhanced rest perfusion sequences were acquired in random order in 8 patients: 6-slice SMS bSSFP and 3 slice bSSFP. All images were reconstructed with TGRAPPA. SMS images were also reconstructed using a non-linear iterative reconstruction with L1 regularisation in wavelet space (SMS-iter) with 7 different combinations for spatial (λσ) and temporal (λτ) regularisation parameters. Qualitative ratings of overall image quality (0 = poor image quality, 1 = major artifact, 2 = minor artifact, 3 = excellent), perceived SNR (0 = poor SNR, 1 = major noise, 2 = minor noise, 3 = high SNR), frequency of sequence related artifacts and patient related artifacts were undertaken. Quantitative analysis of contrast ratio (CR) and percentage of dark rim artifact (DRA) was performed. RESULTS Among all SMS-iter reconstructions, SMS-iter 6 (λσ 0.001 λτ 0.005) was identified as the optimal reconstruction with the highest overall image quality, least sequence related artifact and higher perceived SNR. SMS-iter 6 had superior overall image quality (2.50 ± 0.53 vs 1.50 ± 0.53, p = 0.005) and perceived SNR (2.25 ± 0.46 vs 0.75 ± 0.46, p = 0.010) compared to 3 slice bSSFP. There were no significant differences in sequence related artifact, CR (3.62 ± 0.39 vs 3.66 ± 0.65, p = 0.88) or percentage of DRA (5.25 ± 6.56 vs 4.25 ± 4.30, p = 0.64) with SMS-iter 6 compared to 3 slice bSSFP. CONCLUSIONS SMS bSSFP with GC-LOLA and iterative reconstruction improved image quality compared to a 3 slice bSSFP with doubled spatial coverage and preserved in-plane spatial resolution. Future evaluation in patients with coronary artery disease is warranted.
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Affiliation(s)
- Muhummad Sohaib Nazir
- School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor Lambeth Wing, St Thomas’ Hospital, Westminster Bridge Road, London, SW1 7EH UK
| | - Radhouene Neji
- School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor Lambeth Wing, St Thomas’ Hospital, Westminster Bridge Road, London, SW1 7EH UK
- MR Research Collaborations, Siemens Healthcare Limited, Frimley, UK
| | | | - Fiona Reid
- Division of Health and Social Care Research, King’s College London, London, UK
| | - Daniel Stäb
- Siemens Healthcare Pty Ltd, Melbourne, Australia
| | | | | | - Reza Razavi
- School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor Lambeth Wing, St Thomas’ Hospital, Westminster Bridge Road, London, SW1 7EH UK
| | - Sven Plein
- School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor Lambeth Wing, St Thomas’ Hospital, Westminster Bridge Road, London, SW1 7EH UK
- Leeds Institute of Cardiovascular and Metabolic Medicine, LIGHT Laboratories, Clarendon Way, University of Leeds, Leeds, LS2 9JT UK
| | - Tevfik F. Ismail
- School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor Lambeth Wing, St Thomas’ Hospital, Westminster Bridge Road, London, SW1 7EH UK
| | - Amedeo Chiribiri
- School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor Lambeth Wing, St Thomas’ Hospital, Westminster Bridge Road, London, SW1 7EH UK
| | - Sébastien Roujol
- School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor Lambeth Wing, St Thomas’ Hospital, Westminster Bridge Road, London, SW1 7EH UK
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Naresh NK, Haji-Valizadeh H, Aouad PJ, Barrett MJ, Chow K, Ragin AB, Collins JD, Carr JC, Lee DC, Kim D. Accelerated, first-pass cardiac perfusion pulse sequence with radial k-space sampling, compressed sensing, and k-space weighted image contrast reconstruction tailored for visual analysis and quantification of myocardial blood flow. Magn Reson Med 2018; 81:2632-2643. [PMID: 30417932 DOI: 10.1002/mrm.27573] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2018] [Revised: 09/19/2018] [Accepted: 09/28/2018] [Indexed: 12/21/2022]
Abstract
PURPOSE To develop an accelerated cardiac perfusion pulse sequence and test whether it is capable of increasing spatial coverage, generating high-quality images, and enabling quantification of myocardial blood flow (MBF). METHODS We implemented an accelerated first-pass cardiac perfusion pulse sequence by combining radial k-space sampling, compressed sensing (CS), and k-space weighted image contrast (KWIC) filtering. The proposed and clinical standard pulse sequences were evaluated in a randomized order in 13 patients at rest. For visual analysis, 3 readers graded the conspicuity of wall enhancement, artifact, and noise level on a 5-point Likert scale (overall score index = sum of 3 individual scores). Resting MBF was calculated using a Fermi function model with and without KWIC filtering. Mean visual scores and MBF values were compared between sequences using appropriate statistical tests. RESULTS The proposed pulse sequence produced greater spatial coverage (6-8 slices) with higher spatial resolution (1.6 × 1.6 × 8 mm3 ) and shorter readout duration (78 ms) compared to clinical standard (3-4 slices, 3 × 3 × 8 mm3 , 128 ms, respectively). The overall image score index between accelerated (11.1 ± 1.3) and clinical standard (11.2 ± 1.3) was not significantly different (P = 0.64). Mean resting MBF values with KWIC filtering (0.9-1.2 mL/g/min across different slices) were significantly lower (P < 0.0001) than those without KWIC filtering (3.1-4.3 mL/g/min) and agreed better with values reported in literature. CONCLUSION An accelerated, first-pass cardiac perfusion pulse sequence with radial k-space sampling, CS, and KWIC filtering is capable of increasing spatial coverage, generating high-quality images, and enabling quantification of MBF.
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Affiliation(s)
- Nivedita K Naresh
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Hassan Haji-Valizadeh
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois.,Department of Biomedical Engineering, Northwestern University, Evanston, Illinois
| | - Pascale J Aouad
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Matthew J Barrett
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Kelvin Chow
- Siemens Medical Solutions USA, Inc, Chicago, Illinois
| | - Ann B Ragin
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Jeremy D Collins
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - James C Carr
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Daniel C Lee
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois.,Internal Medicine, Division of Cardiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Daniel Kim
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois.,Department of Biomedical Engineering, Northwestern University, Evanston, Illinois
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43
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Ferrazzi G, Bassenge JP, Wink C, Ruh A, Markl M, Moeller S, Metzger GJ, Ittermann B, Schmitter S. Autocalibrated multiband CAIPIRINHA with through‐time encoding: Proof of principle and application to cardiac tissue phase mapping. Magn Reson Med 2018; 81:1016-1030. [DOI: 10.1002/mrm.27460] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Revised: 06/30/2018] [Accepted: 07/02/2018] [Indexed: 12/27/2022]
Affiliation(s)
- Giulio Ferrazzi
- Physikalisch‐Technische Bundesanstalt (PTB) Braunschweig and Berlin Germany
| | - Jean Pierre Bassenge
- Physikalisch‐Technische Bundesanstalt (PTB) Braunschweig and Berlin Germany
- Working Group on Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, a joint cooperation between the Charité Medical Faculty and the Max‐Delbrueck Center for Molecular Medicine
| | - Clarissa Wink
- Physikalisch‐Technische Bundesanstalt (PTB) Braunschweig and Berlin Germany
| | - Alexander Ruh
- Department of Radiology, Feinberg School of Medicine Northwestern University Chicago Illinois
| | - Michael Markl
- Department of Radiology, Feinberg School of Medicine Northwestern University Chicago Illinois
- Department of Biomedical Engineering, McCormick School of Engineering Northwestern University Chicago Illinois
| | - Steen Moeller
- University of Minnesota, Center for Magnetic Resonance Research (CMRR) Minneapolis Minnesota
| | - Gregory J. Metzger
- University of Minnesota, Center for Magnetic Resonance Research (CMRR) Minneapolis Minnesota
| | - Bernd Ittermann
- Physikalisch‐Technische Bundesanstalt (PTB) Braunschweig and Berlin Germany
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44
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Hong K, Collins JD, Knight BP, Carr JC, Lee DC, Kim D. Wideband myocardial perfusion pulse sequence for imaging patients with a cardiac implantable electronic device. Magn Reson Med 2018; 81:1219-1228. [PMID: 30229560 DOI: 10.1002/mrm.27458] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2018] [Revised: 06/29/2018] [Accepted: 06/30/2018] [Indexed: 01/28/2023]
Abstract
PURPOSE To develop a wideband cardiac perfusion pulse sequence and test whether it is capable of suppressing image artifacts in patients with a cardiac implantable electronic device (CIED), while not exceeding the specific absorption rate (SAR) limit (2.0 W/kg). METHODS A wideband perfusion pulse sequence was developed by incorporating a wideband saturation pulse to achieve a good balance between saturation of magnetization and SAR. Clinical standard and wideband perfusion MRI scans were performed back-to-back in a randomized order on 16 patients with a CIED undergoing clinical cardiac MRI. Two expert readers graded the artifact intensity and extent on a segmental basis using a 5-point Likert scale, where significant artifact was defined by a composite score. The variance in myocardial signal prior to tissue-enhancement was analyzed to quantify artifact-intensity. Whole-body SAR values computed by the MR scanner were read from the DICOM header. Either a paired t-test or Wilcoxon signed-rank test was performed to compare two groups. RESULTS While the mean whole-body SAR for a single-slice wideband perfusion scan (0.38 ± 0.08W/kg) was significantly (p < 0.05) higher than for a single-slice standard perfusion scan (0.11 ± 0.03W/kg), it was 81% below 2.0 W/kg. The mean variance in myocardial signal prior to tissue-enhancement was significantly (p < 0.001) higher for standard (422.6 ± 306.6 a.u.) than wideband (107.0 ± 60.9 a.u.). Among 105 myocardial segments, standard produced 19 segments (18%) that were deemed to have significant artifacts, whereas wideband produced only 3 segments (3%). CONCLUSION A wideband perfusion pulse sequence is capable of suppressing image artifacts induced by a CIED while not exceeding SAR at 2.0 W/kg.
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Affiliation(s)
- KyungPyo Hong
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Jeremy D Collins
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Bradley P Knight
- Division of Cardiology, Internal Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - James C Carr
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Daniel C Lee
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL.,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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45
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Stäb D, Speier P. Gradient-controlled local Larmor adjustment (GC-LOLA) for simultaneous multislice bSSFP imaging with improved banding behavior. Magn Reson Med 2018; 81:129-139. [DOI: 10.1002/mrm.27356] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Revised: 04/19/2018] [Accepted: 04/21/2018] [Indexed: 12/27/2022]
Affiliation(s)
- Daniel Stäb
- The Centre for Advanced Imaging, The University of Queensland; Brisbane Queensland Australia
- Department of Diagnostic and Interventional Radiology; University of Würzburg; Germany
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46
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Motion-Corrected Real-Time Cine Magnetic Resonance Imaging of the Heart: Initial Clinical Experience. Invest Radiol 2018; 53:35-44. [PMID: 28857861 DOI: 10.1097/rli.0000000000000406] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
OBJECTIVES Free-breathing real-time (RT) imaging can be used in patients with difficulty in breath-holding; however, RT cine imaging typically experiences poor image quality compared with segmented cine imaging because of low resolution. Here, we validate a novel unsupervised motion-corrected (MOCO) reconstruction technique for free-breathing RT cardiac images, called MOCO-RT. Motion-corrected RT uses elastic image registration to generate a single heartbeat of high-quality data from a free-breathing RT acquisition. MATERIALS AND METHODS Segmented balanced steady-state free precession (bSSFP) cine images and free-breathing RT images (Cartesian, TGRAPPA factor 4) were acquired with the same spatial/temporal resolution in 40 patients using clinical 1.5 T magnetic resonance scanners. The respiratory cycle was estimated using the reconstructed RT images, and nonrigid unsupervised motion correction was applied to eliminate breathing motion. Conventional segmented RT and MOCO-RT single-heartbeat cine images were analyzed to evaluate left ventricular (LV) function and volume measurements. Two radiologists scored images for overall image quality, artifact, noise, and wall motion abnormalities. Intraclass correlation coefficient was used to assess the reliability of MOCO-RT measurement. RESULTS Intraclass correlation coefficient showed excellent reliability (intraclass correlation coefficient ≥ 0.95) of MOCO-RT with segmented cine in measuring LV function, mass, and volume. Comparison of the qualitative ratings indicated comparable image quality for MOCO-RT (4.80 ± 0.35) with segmented cine (4.45 ± 0.88, P = 0.215) and significantly higher than conventional RT techniques (3.51 ± 0.41, P < 0.001). Artifact and noise ratings for MOCO-RT (1.11 ± 0.26 and 1.08 ± 0.19) and segmented cine (1.51 ± 0.90, P = 0.088 and 1.23 ± 0.45, P = 0.182) were not different. Wall motion abnormality ratings were comparable among different techniques (P = 0.96). CONCLUSIONS The MOCO-RT technique can be used to process conventional free-breathing RT cine images and provides comparable quantitative assessment of LV function and volume measurements to conventional segmented cine imaging while providing improved image quality and less artifact and noise. The free-breathing MOCO-RT reconstruction method may have considerable clinical utility in cardiac magnetic resonance imaging for patients with difficulty breath-holding.
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47
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Zhou R, Huang W, Yang Y, Chen X, Weller DS, Kramer CM, Kozerke S, Salerno M. Simple motion correction strategy reduces respiratory-induced motion artifacts for k-t accelerated and compressed-sensing cardiovascular magnetic resonance perfusion imaging. J Cardiovasc Magn Reson 2018; 20:6. [PMID: 29386056 PMCID: PMC5793398 DOI: 10.1186/s12968-018-0427-1] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2017] [Accepted: 01/02/2018] [Indexed: 01/28/2023] Open
Abstract
BACKGROUND Cardiovascular magnetic resonance (CMR) stress perfusion imaging provides important diagnostic and prognostic information in coronary artery disease (CAD). Current clinical sequences have limited temporal and/or spatial resolution, and incomplete heart coverage. Techniques such as k-t principal component analysis (PCA) or k-t sparcity and low rank structure (SLR), which rely on the high degree of spatiotemporal correlation in first-pass perfusion data, can significantly accelerate image acquisition mitigating these problems. However, in the presence of respiratory motion, these techniques can suffer from significant degradation of image quality. A number of techniques based on non-rigid registration have been developed. However, to first approximation, breathing motion predominantly results in rigid motion of the heart. To this end, a simple robust motion correction strategy is proposed for k-t accelerated and compressed sensing (CS) perfusion imaging. METHODS A simple respiratory motion compensation (MC) strategy for k-t accelerated and compressed-sensing CMR perfusion imaging to selectively correct respiratory motion of the heart was implemented based on linear k-space phase shifts derived from rigid motion registration of a region-of-interest (ROI) encompassing the heart. A variable density Poisson disk acquisition strategy was used to minimize coherent aliasing in the presence of respiratory motion, and images were reconstructed using k-t PCA and k-t SLR with or without motion correction. The strategy was evaluated in a CMR-extended cardiac torso digital (XCAT) phantom and in prospectively acquired first-pass perfusion studies in 12 subjects undergoing clinically ordered CMR studies. Phantom studies were assessed using the Structural Similarity Index (SSIM) and Root Mean Square Error (RMSE). In patient studies, image quality was scored in a blinded fashion by two experienced cardiologists. RESULTS In the phantom experiments, images reconstructed with the MC strategy had higher SSIM (p < 0.01) and lower RMSE (p < 0.01) in the presence of respiratory motion. For patient studies, the MC strategy improved k-t PCA and k-t SLR reconstruction image quality (p < 0.01). The performance of k-t SLR without motion correction demonstrated improved image quality as compared to k-t PCA in the setting of respiratory motion (p < 0.01), while with motion correction there is a trend of better performance in k-t SLR as compared with motion corrected k-t PCA. CONCLUSIONS Our simple and robust rigid motion compensation strategy greatly reduces motion artifacts and improves image quality for standard k-t PCA and k-t SLR techniques in setting of respiratory motion due to imperfect breath-holding.
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Affiliation(s)
- Ruixi Zhou
- Departments of Medicine, Cardiovascular Imaging Center, University of Virginia Health System, Charlottesville, VA USA
| | - Wei Huang
- Departments of Medicine, Cardiovascular Imaging Center, University of Virginia Health System, Charlottesville, VA USA
- Department of Biomedical Engineering, Cardiovascular Imaging Center, University of Virginia Health System, Charlottesville, VA USA
- Medical Imaging Technologies, Siemens Healthineers, Princeton, NJ USA
- Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA USA
- Department of Radiology, Cardiovascular Imaging Center, University of Virginia Health System, Charlottesville, VA USA
- Department of Information Technology and Electrical Engineering, Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
- Cardiovascular Division, University of Virginia Health System, 1215 Lee Street, PO Box 800158, Charlottesville, VA 22908 USA
| | - Yang Yang
- Departments of Medicine, Cardiovascular Imaging Center, University of Virginia Health System, Charlottesville, VA USA
- Department of Biomedical Engineering, Cardiovascular Imaging Center, University of Virginia Health System, Charlottesville, VA USA
| | - Xiao Chen
- Medical Imaging Technologies, Siemens Healthineers, Princeton, NJ USA
| | - Daniel S. Weller
- Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA USA
| | - Christopher M. Kramer
- Departments of Medicine, Cardiovascular Imaging Center, University of Virginia Health System, Charlottesville, VA USA
- Department of Radiology, Cardiovascular Imaging Center, University of Virginia Health System, Charlottesville, VA USA
- Department of Information Technology and Electrical Engineering, Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Sebastian Kozerke
- Department of Radiology, Cardiovascular Imaging Center, University of Virginia Health System, Charlottesville, VA USA
- Department of Information Technology and Electrical Engineering, Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Michael Salerno
- Departments of Medicine, Cardiovascular Imaging Center, University of Virginia Health System, Charlottesville, VA USA
- Department of Biomedical Engineering, Cardiovascular Imaging Center, University of Virginia Health System, Charlottesville, VA USA
- Department of Radiology, Cardiovascular Imaging Center, University of Virginia Health System, Charlottesville, VA USA
- Department of Information Technology and Electrical Engineering, Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
- Cardiovascular Division, University of Virginia Health System, 1215 Lee Street, PO Box 800158, Charlottesville, VA 22908 USA
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Accelerated real-time cardiac MRI using iterative sparse SENSE reconstruction: comparing performance in patients with sinus rhythm and atrial fibrillation. Eur Radiol 2018; 28:3088-3096. [DOI: 10.1007/s00330-017-5283-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2017] [Revised: 12/12/2017] [Accepted: 12/22/2017] [Indexed: 12/19/2022]
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49
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Dedeić Z, Sutendra G, Hu Y, Chung K, Slee EA, White MJ, Zhou FY, Goldin RD, Ferguson DJP, McAndrew D, Schneider JE, Lu X. Cell autonomous role of iASPP deficiency in causing cardiocutaneous disorders. Cell Death Differ 2018; 25:1289-1303. [PMID: 29352264 DOI: 10.1038/s41418-017-0039-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2017] [Revised: 10/20/2017] [Accepted: 10/30/2017] [Indexed: 12/13/2022] Open
Abstract
Desmosome components are frequently mutated in cardiac and cutaneous disorders in animals and humans and enhanced inflammation is a common feature of these diseases. Previous studies showed that inhibitor of Apoptosis Stimulating p53 Protein (iASPP) regulates desmosome integrity at cell-cell junctions and transcription in the nucleus, and its deficiency causes cardiocutaneous disorder in mice, cattle, and humans. As iASPP is a ubiquitously expressed shuttling protein with multiple functions, a key question is whether the observed cardiocutaneous phenotypes are caused by loss of a cell autonomous role of iASPP in cardiomyocytes and keratinocytes specifically or by a loss of iASPP in other cell types such as immune cells. To address this, we developed cardiomyocyte-specific and keratinocyte-specific iASPP-deficient mouse models and show that the cell-type specific loss of iASPP in cardiomyocytes or keratinocytes is sufficient to induce cardiac or cutaneous disorders, respectively. Additionally, keratinocyte-specific iASPP-deficient mice have delayed eyelid development and wound healing. In keratinocytes, junctional iASPP is critical for stabilizing desmosomes and iASPP deficiency results in increased and disorganized cell migration, as well as impaired cell adhesion, consistent with delayed wound healing. The identification of a cell autonomous role of iASPP deficiency in causing cardiocutaneous syndrome, impaired eyelid development and wound healing suggests that variants in the iASPP gene also may contribute to polygenic heart and skin diseases.
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Affiliation(s)
- Zinaida Dedeić
- Ludwig Institute for Cancer Research Ltd., Nuffield Department of Clinical Medicine, University of Oxford, Oxford, OX3 7DQ, UK
| | - Gopinath Sutendra
- Ludwig Institute for Cancer Research Ltd., Nuffield Department of Clinical Medicine, University of Oxford, Oxford, OX3 7DQ, UK.,Department of Medicine, University of Alberta, Edmonton, Alberta, T6G 2B7, Canada
| | - Ying Hu
- Ludwig Institute for Cancer Research Ltd., Nuffield Department of Clinical Medicine, University of Oxford, Oxford, OX3 7DQ, UK.,The School of Life Science and Technology, Harbin Institute of Technology, Harbin, 1500080, China
| | - Kathryn Chung
- Ludwig Institute for Cancer Research Ltd., Nuffield Department of Clinical Medicine, University of Oxford, Oxford, OX3 7DQ, UK
| | - Elizabeth A Slee
- Ludwig Institute for Cancer Research Ltd., Nuffield Department of Clinical Medicine, University of Oxford, Oxford, OX3 7DQ, UK
| | - Michael J White
- Ludwig Institute for Cancer Research Ltd., Nuffield Department of Clinical Medicine, University of Oxford, Oxford, OX3 7DQ, UK
| | - Felix Y Zhou
- Ludwig Institute for Cancer Research Ltd., Nuffield Department of Clinical Medicine, University of Oxford, Oxford, OX3 7DQ, UK
| | - Robert D Goldin
- Centre for Pathology, St. Mary's Hospital, Imperial College, London, W2 1NY, UK
| | - David J P Ferguson
- Nuffield Department of Clinical Laboratory Science, University of Oxford, Oxford, OX3 9DU, UK
| | - Debra McAndrew
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK
| | - Jurgen E Schneider
- Division of Biomedical Imaging, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9JT, UK
| | - Xin Lu
- Ludwig Institute for Cancer Research Ltd., Nuffield Department of Clinical Medicine, University of Oxford, Oxford, OX3 7DQ, UK.
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50
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Ahmad R, Hu HH, Krishnamurthy R, Krishnamurthy R. Reducing sedation for pediatric body MRI using accelerated and abbreviated imaging protocols. Pediatr Radiol 2018; 48:37-49. [PMID: 29292482 DOI: 10.1007/s00247-017-3987-6] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Revised: 06/13/2017] [Accepted: 09/12/2017] [Indexed: 12/01/2022]
Abstract
Magnetic resonance imaging (MRI) is an established diagnostic imaging tool for investigating pediatric disease. MRI allows assessment of structure, function, and morphology in cardiovascular imaging, as well as tissue characterization in body imaging, without the use of ionizing radiation. For MRI in children, sedation and general anesthesia (GA) are often utilized to suppress patient motion, which can otherwise compromise image quality and diagnostic efficacy. However, evidence is emerging that use of sedation and GA in children might have long-term neurocognitive side effects, in addition to the short-term procedure-related risks. These concerns make risk-benefit assessment of sedation and GA more challenging. Therefore, reducing or eliminating the need for sedation and GA is an important goal of imaging innovation and research in pediatric MRI. In this review, the authors focus on technical and clinical approaches to reducing and eliminating the use of sedation in the pediatric population based on image acquisition acceleration and imaging protocols abbreviation. This paper covers important physiological and technical considerations for pediatric body MR imaging and discusses MRI techniques that offer the potential of recovering diagnostic-quality images from accelerated scans. In this review, the authors also introduce the concept of reporting elements for important indications for pediatric body MRI and use this as a basis for abbreviating the MR protocols. By employing appropriate accelerated and abbreviated approaches based on an understanding of the imaging needs and reporting elements for a given clinical indication, it is possible to reduce sedation and GA for pediatric chest, cardiovascular and abdominal MRI.
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Affiliation(s)
- Rizwan Ahmad
- Department of Biomedical Engineering, The Ohio State University, Columbus, OH, USA
| | - Houchun Harry Hu
- Department of Radiology, Nationwide Children's Hospital, 700 Children's Drive, Columbus, OH, 43205, USA
| | - Ramkumar Krishnamurthy
- Department of Radiology, Nationwide Children's Hospital, 700 Children's Drive, Columbus, OH, 43205, USA
| | - Rajesh Krishnamurthy
- Department of Radiology, Nationwide Children's Hospital, 700 Children's Drive, Columbus, OH, 43205, USA.
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