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Yoon S, Nakamori S, Amyar A, Assana S, Cirillo J, Morales MA, Chow K, Bi X, Pierce P, Goddu B, Rodriguez J, H Ngo L, J Manning W, Nezafat R. Accelerated Cardiac MRI Cine with Use of Resolution Enhancement Generative Adversarial Inline Neural Network. Radiology 2023; 307:e222878. [PMID: 37249435 DOI: 10.1148/radiol.222878] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Background Cardiac cine can benefit from deep learning-based image reconstruction to reduce scan time and/or increase spatial and temporal resolution. Purpose To develop and evaluate a deep learning model that can be combined with parallel imaging or compressed sensing (CS). Materials and Methods The deep learning model was built on the enhanced super-resolution generative adversarial inline neural network, trained with use of retrospectively identified cine images and evaluated in participants prospectively enrolled from September 2021 to September 2022. The model was applied to breath-hold electrocardiography (ECG)-gated segmented and free-breathing real-time cine images collected with reduced spatial resolution with use of generalized autocalibrating partially parallel acquisitions (GRAPPA) or CS. The deep learning model subsequently restored spatial resolution. For comparison, GRAPPA-accelerated cine images were collected. Diagnostic quality and artifacts were evaluated by two readers with use of Likert scales and compared with use of Wilcoxon signed-rank tests. Agreement for left ventricle (LV) function, volume, and strain was assessed with Bland-Altman analysis. Results The deep learning model was trained on 1616 patients (mean age ± SD, 56 years ± 16; 920 men) and evaluated in 181 individuals, 126 patients (mean age, 57 years ± 16; 77 men) and 55 healthy subjects (mean age, 27 years ± 10; 15 men). In breath-hold ECG-gated segmented cine and free-breathing real-time cine, the deep learning model and GRAPPA showed similar diagnostic quality scores (2.9 vs 2.9, P = .41, deep learning vs GRAPPA) and artifact score (4.4 vs 4.3, P = .55, deep learning vs GRAPPA). Deep learning acquired more sections per breath-hold than GRAPPA (3.1 vs one section, P < .001). In free-breathing real-time cine, the deep learning showed a similar diagnostic quality score (2.9 vs 2.9, P = .21, deep learning vs GRAPPA) and lower artifact score (3.9 vs 4.3, P < .001, deep learning vs GRAPPA). For both sequences, the deep learning model showed excellent agreement for LV parameters, with near-zero mean differences and narrow limits of agreement compared with GRAPPA. Conclusion Deep learning-accelerated cardiac cine showed similarly accurate quantification of cardiac function, volume, and strain to a standardized parallel imaging method. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Vannier and Wang in this issue.
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Affiliation(s)
- Siyeop Yoon
- From the Department of Medicine (Cardiovascular Division) (S.Y., S.N., A.A., S.A., J.C., M.A.M., P.P., B.G., J.R., W.J.M., R.N.), Department of Medicine (General Medicine Division) (L.H.N.), and Department of Radiology (W.J.M.), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215; Siemens Medical Solutions, Chicago, Ill (K.C., X.B.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Mass (L.H.N.)
| | - Shiro Nakamori
- From the Department of Medicine (Cardiovascular Division) (S.Y., S.N., A.A., S.A., J.C., M.A.M., P.P., B.G., J.R., W.J.M., R.N.), Department of Medicine (General Medicine Division) (L.H.N.), and Department of Radiology (W.J.M.), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215; Siemens Medical Solutions, Chicago, Ill (K.C., X.B.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Mass (L.H.N.)
| | - Amine Amyar
- From the Department of Medicine (Cardiovascular Division) (S.Y., S.N., A.A., S.A., J.C., M.A.M., P.P., B.G., J.R., W.J.M., R.N.), Department of Medicine (General Medicine Division) (L.H.N.), and Department of Radiology (W.J.M.), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215; Siemens Medical Solutions, Chicago, Ill (K.C., X.B.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Mass (L.H.N.)
| | - Salah Assana
- From the Department of Medicine (Cardiovascular Division) (S.Y., S.N., A.A., S.A., J.C., M.A.M., P.P., B.G., J.R., W.J.M., R.N.), Department of Medicine (General Medicine Division) (L.H.N.), and Department of Radiology (W.J.M.), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215; Siemens Medical Solutions, Chicago, Ill (K.C., X.B.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Mass (L.H.N.)
| | - Julia Cirillo
- From the Department of Medicine (Cardiovascular Division) (S.Y., S.N., A.A., S.A., J.C., M.A.M., P.P., B.G., J.R., W.J.M., R.N.), Department of Medicine (General Medicine Division) (L.H.N.), and Department of Radiology (W.J.M.), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215; Siemens Medical Solutions, Chicago, Ill (K.C., X.B.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Mass (L.H.N.)
| | - Manuel A Morales
- From the Department of Medicine (Cardiovascular Division) (S.Y., S.N., A.A., S.A., J.C., M.A.M., P.P., B.G., J.R., W.J.M., R.N.), Department of Medicine (General Medicine Division) (L.H.N.), and Department of Radiology (W.J.M.), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215; Siemens Medical Solutions, Chicago, Ill (K.C., X.B.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Mass (L.H.N.)
| | - Kelvin Chow
- From the Department of Medicine (Cardiovascular Division) (S.Y., S.N., A.A., S.A., J.C., M.A.M., P.P., B.G., J.R., W.J.M., R.N.), Department of Medicine (General Medicine Division) (L.H.N.), and Department of Radiology (W.J.M.), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215; Siemens Medical Solutions, Chicago, Ill (K.C., X.B.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Mass (L.H.N.)
| | - Xiaoming Bi
- From the Department of Medicine (Cardiovascular Division) (S.Y., S.N., A.A., S.A., J.C., M.A.M., P.P., B.G., J.R., W.J.M., R.N.), Department of Medicine (General Medicine Division) (L.H.N.), and Department of Radiology (W.J.M.), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215; Siemens Medical Solutions, Chicago, Ill (K.C., X.B.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Mass (L.H.N.)
| | - Patrick Pierce
- From the Department of Medicine (Cardiovascular Division) (S.Y., S.N., A.A., S.A., J.C., M.A.M., P.P., B.G., J.R., W.J.M., R.N.), Department of Medicine (General Medicine Division) (L.H.N.), and Department of Radiology (W.J.M.), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215; Siemens Medical Solutions, Chicago, Ill (K.C., X.B.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Mass (L.H.N.)
| | - Beth Goddu
- From the Department of Medicine (Cardiovascular Division) (S.Y., S.N., A.A., S.A., J.C., M.A.M., P.P., B.G., J.R., W.J.M., R.N.), Department of Medicine (General Medicine Division) (L.H.N.), and Department of Radiology (W.J.M.), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215; Siemens Medical Solutions, Chicago, Ill (K.C., X.B.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Mass (L.H.N.)
| | - Jennifer Rodriguez
- From the Department of Medicine (Cardiovascular Division) (S.Y., S.N., A.A., S.A., J.C., M.A.M., P.P., B.G., J.R., W.J.M., R.N.), Department of Medicine (General Medicine Division) (L.H.N.), and Department of Radiology (W.J.M.), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215; Siemens Medical Solutions, Chicago, Ill (K.C., X.B.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Mass (L.H.N.)
| | - Long H Ngo
- From the Department of Medicine (Cardiovascular Division) (S.Y., S.N., A.A., S.A., J.C., M.A.M., P.P., B.G., J.R., W.J.M., R.N.), Department of Medicine (General Medicine Division) (L.H.N.), and Department of Radiology (W.J.M.), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215; Siemens Medical Solutions, Chicago, Ill (K.C., X.B.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Mass (L.H.N.)
| | - Warren J Manning
- From the Department of Medicine (Cardiovascular Division) (S.Y., S.N., A.A., S.A., J.C., M.A.M., P.P., B.G., J.R., W.J.M., R.N.), Department of Medicine (General Medicine Division) (L.H.N.), and Department of Radiology (W.J.M.), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215; Siemens Medical Solutions, Chicago, Ill (K.C., X.B.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Mass (L.H.N.)
| | - Reza Nezafat
- From the Department of Medicine (Cardiovascular Division) (S.Y., S.N., A.A., S.A., J.C., M.A.M., P.P., B.G., J.R., W.J.M., R.N.), Department of Medicine (General Medicine Division) (L.H.N.), and Department of Radiology (W.J.M.), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215; Siemens Medical Solutions, Chicago, Ill (K.C., X.B.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Mass (L.H.N.)
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Amyar A, Guo R, Cai X, Assana S, Chow K, Rodriguez J, Yankama T, Cirillo J, Pierce P, Goddu B, Ngo L, Nezafat R. Impact of deep learning architectures on accelerated cardiac T 1 mapping using MyoMapNet. NMR Biomed 2022; 35:e4794. [PMID: 35767308 PMCID: PMC9532368 DOI: 10.1002/nbm.4794] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 05/19/2022] [Accepted: 06/25/2022] [Indexed: 05/10/2023]
Abstract
The objective of the current study was to investigate the performance of various deep learning (DL) architectures for MyoMapNet, a DL model for T1 estimation using accelerated cardiac T1 mapping from four T1 -weighted images collected after a single inversion pulse (Look-Locker 4 [LL4]). We implemented and tested three DL architectures for MyoMapNet: (a) a fully connected neural network (FC), (b) convolutional neural networks (VGG19, ResNet50), and (c) encoder-decoder networks with skip connections (ResUNet, U-Net). Modified Look-Locker inversion recovery (MOLLI) images from 749 patients at 3 T were used for training, validation, and testing. The first four T1 -weighted images from MOLLI5(3)3 and/or MOLLI4(1)3(1)2 protocols were extracted to create accelerated cardiac T1 mapping data. We also prospectively collected data from 28 subjects using MOLLI and LL4 to further evaluate model performance. Despite rigorous training, conventional VGG19 and ResNet50 models failed to produce anatomically correct T1 maps, and T1 values had significant errors. While ResUNet yielded good quality maps, it significantly underestimated T1 . Both FC and U-Net, however, yielded excellent image quality with good T1 accuracy for both native (FC/U-Net/MOLLI = 1217 ± 64/1208 ± 61/1199 ± 61 ms, all p < 0.05) and postcontrast myocardial T1 (FC/U-Net/MOLLI = 578 ± 57/567 ± 54/574 ± 55 ms, all p < 0.05). In terms of precision, the U-Net model yielded better T1 precision compared with the FC architecture (standard deviation of 61 vs. 67 ms for the myocardium for native [p < 0.05], and 31 vs. 38 ms [p < 0.05], for postcontrast). Similar findings were observed in prospectively collected LL4 data. It was concluded that U-Net and FC DL models in MyoMapNet enable fast myocardial T1 mapping using only four T1 -weighted images collected from a single LL sequence with comparable accuracy. U-Net also provides a slight improvement in precision.
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Affiliation(s)
- Amine Amyar
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Rui Guo
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Xiaoying Cai
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
- Siemens Medical Solutions USA, Inc., Boston, Massachusetts, USA
| | - Salah Assana
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Kelvin Chow
- Siemens Medical Solutions USA, Inc., Chicago, Illinois, USA
| | - Jennifer Rodriguez
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Tuyen Yankama
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Julia Cirillo
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Patrick Pierce
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Beth Goddu
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Long Ngo
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
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Morales MA, Assana S, Cai X, Chow K, Haji-Valizadeh H, Sai E, Tsao C, Matos J, Rodriguez J, Berg S, Whitehead N, Pierce P, Goddu B, Manning WJ, Nezafat R. An inline deep learning based free-breathing ECG-free cine for exercise cardiovascular magnetic resonance. J Cardiovasc Magn Reson 2022; 24:47. [PMID: 35948936 PMCID: PMC9367083 DOI: 10.1186/s12968-022-00879-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 07/21/2022] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Exercise cardiovascular magnetic resonance (Ex-CMR) is a promising stress imaging test for coronary artery disease (CAD). However, Ex-CMR requires accelerated imaging techniques that result in significant aliasing artifacts. Our goal was to develop and evaluate a free-breathing and electrocardiogram (ECG)-free real-time cine with deep learning (DL)-based radial acceleration for Ex-CMR. METHODS A 3D (2D + time) convolutional neural network was implemented to suppress artifacts from aliased radial cine images. The network was trained using synthetic real-time radial cine images simulated using breath-hold, ECG-gated segmented Cartesian k-space data acquired at 3 T from 503 patients at rest. A prototype real-time radial sequence with acceleration rate = 12 was used to collect images with inline DL reconstruction. Performance was evaluated in 8 healthy subjects in whom only rest images were collected. Subsequently, 14 subjects (6 healthy and 8 patients with suspected CAD) were prospectively recruited for an Ex-CMR to evaluate image quality. At rest (n = 22), standard breath-hold ECG-gated Cartesian segmented cine and free-breathing ECG-free real-time radial cine images were acquired. During post-exercise stress (n = 14), only real-time radial cine images were acquired. Three readers evaluated residual artifact level in all collected images on a 4-point Likert scale (1-non-diagnostic, 2-severe, 3-moderate, 4-minimal). RESULTS The DL model substantially suppressed artifacts in real-time radial cine images acquired at rest and during post-exercise stress. In real-time images at rest, 89.4% of scores were moderate to minimal. The mean score was 3.3 ± 0.7, representing increased (P < 0.001) artifacts compared to standard cine (3.9 ± 0.3). In real-time images during post-exercise stress, 84.6% of scores were moderate to minimal, and the mean artifact level score was 3.1 ± 0.6. Comparison of left-ventricular (LV) measures derived from standard and real-time cine at rest showed differences in LV end-diastolic volume (3.0 mL [- 11.7, 17.8], P = 0.320) that were not significantly different from zero. Differences in measures of LV end-systolic volume (7.0 mL [- 1.3, 15.3], P < 0.001) and LV ejection fraction (- 5.0% [- 11.1, 1.0], P < 0.001) were significant. Total inline reconstruction time of real-time radial images was 16.6 ms per frame. CONCLUSIONS Our proof-of-concept study demonstrated the feasibility of inline real-time cine with DL-based radial acceleration for Ex-CMR.
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Affiliation(s)
- Manuel A Morales
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA, 02215, USA
| | - Salah Assana
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA, 02215, USA
| | - Xiaoying Cai
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA, 02215, USA
- Siemens Medical Solutions USA, Inc, Chicago, IL, USA
| | - Kelvin Chow
- Siemens Medical Solutions USA, Inc, Chicago, IL, USA
| | - Hassan Haji-Valizadeh
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA, 02215, USA
| | - Eiryu Sai
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA, 02215, USA
| | - Connie Tsao
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA, 02215, USA
| | - Jason Matos
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA, 02215, USA
| | - Jennifer Rodriguez
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA, 02215, USA
| | - Sophie Berg
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA, 02215, USA
| | - Neal Whitehead
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA, 02215, USA
| | - Patrick Pierce
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA, 02215, USA
| | - Beth Goddu
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA, 02215, USA
| | - Warren J Manning
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA, 02215, USA
- Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA, 02215, USA.
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Guo R, Chen Z, Amyar A, El-Rewaidy H, Assana S, Rodriguez J, Pierce P, Goddu B, Nezafat R. Improving accuracy of myocardial T 1 estimation in MyoMapNet. Magn Reson Med 2022; 88:2573-2582. [PMID: 35916305 DOI: 10.1002/mrm.29397] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 07/01/2022] [Accepted: 07/05/2022] [Indexed: 11/09/2022]
Abstract
PURPOSE To improve the accuracy and robustness of T1 estimation by MyoMapNet, a deep learning-based approach using 4 inversion-recovery T1 -weighted images for cardiac T1 mapping. METHODS MyoMapNet is a fully connected neural network for T1 estimation of an accelerated cardiac T1 mapping sequence, which collects 4 T1 -weighted images by a single Look-Locker inversion-recovery experiment (LL4). MyoMapNet was originally trained using in vivo data from the modified Look-Locker inversion recovery sequence, which resulted in significant bias and sensitivity to various confounders. This study sought to train MyoMapNet using signals generated from numerical simulations and phantom MR data under multiple simulated confounders. The trained model was then evaluated by phantom data scanned using new phantom vials that differed from those used for training. The performance of the new model was compared with modified Look-Locker inversion recovery sequence and saturation-recovery single-shot acquisition for measuring native and postcontrast T1 in 25 subjects. RESULTS In the phantom study, T1 values measured by LL4 with MyoMapNet were highly correlated with reference values from the spin-echo sequence. Furthermore, the estimated T1 had excellent robustness to changes in flip angle and off-resonance. Native and postcontrast myocardium T1 at 3 Tesla measured by saturation-recovery single-shot acquisition, modified Look-Locker inversion recovery sequence, and MyoMapNet were 1483 ± 46.6 ms and 791 ± 45.8 ms, 1169 ± 49.0 ms and 612 ± 36.0 ms, and 1443 ± 57.5 ms and 700 ± 57.5 ms, respectively. The corresponding extracellular volumes were 22.90% ± 3.20%, 28.88% ± 3.48%, and 30.65% ± 3.60%, respectively. CONCLUSION Training MyoMapNet with numerical simulations and phantom data will improve the estimation of myocardial T1 values and increase its robustness to confounders while also reducing the overall T1 mapping estimation time to only 4 heartbeats.
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Affiliation(s)
- Rui Guo
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Zhensen Chen
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, People's Republic of China
| | - Amine Amyar
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Hossam El-Rewaidy
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Salah Assana
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Jennifer Rodriguez
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Patrick Pierce
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Beth Goddu
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
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Guo R, Qi H, Amyar A, Cai X, Kucukseymen S, Haji-Valizadeh H, Rodriguez J, Paskavitz A, Pierce P, Goddu B, Thompson RB, Nezafat R. Quantification of changes in myocardial T 1 * values with exercise cardiac MRI using a free-breathing non-electrocardiograph radial imaging. Magn Reson Med 2022; 88:1720-1733. [PMID: 35691942 DOI: 10.1002/mrm.29346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Revised: 05/09/2022] [Accepted: 05/16/2022] [Indexed: 11/11/2022]
Abstract
PURPOSE To develop and evaluate a free breathing non-electrocardiograph (ECG) myocardial T1 * mapping sequence using radial imaging to quantify the changes in myocardial T1 * between rest and exercise (T1 *reactivity ) in exercise cardiac MRI (Ex-CMR). METHODS A free-running T1 * sequence was developed using a saturation pulse followed by three Look-Locker inversion-recovery experiments. Each Look-Locker continuously acquired data as radial trajectory using a low flip-angle spoiled gradient-echo readout. Self-navigation was performed with a temporal resolution of ∼100 ms for retrospectively extracting respiratory motion. The mid-diastole phase for every cardiac cycle was retrospectively detected on the recorded electrocardiogram signal using an empirical model. Multiple measurements were performed to obtain mean value to reduce effects from the free-breathing acquisition. Finally, data acquired at both mid-diastole and end-expiration are picked and reconstructed by a low-rank plus sparsity constraint algorithm. The performance of this sequence was evaluated by simulations, phantoms, and in vivo studies at rest and after physiological exercise. RESULTS Numerical simulation demonstrated that changes in T1 * are related to the changes in T1 ; however, other factors such as breathing motion could influence T1 * measurements. Phantom T1 * values measured using free-running T1 * mapping sequence had good correlation with spin-echo T1 values and was insensitive to heart rate. In the Ex-CMR study, the measured T1 * reactivity was 10% immediately after exercise and declined over time. CONCLUSION The free-running T1 * mapping sequence allows free-breathing non-ECG quantification of changes in myocardial T1 * with physiological exercise. Although, absolute myocardial T1 * value is sensitive to various confounders such as B1 and B0 inhomogeneity, quantification of its change may be useful in revealing myocardial tissue properties with exercise.
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Affiliation(s)
- Rui Guo
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Haikun Qi
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
| | - Amine Amyar
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Xiaoying Cai
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA.,Siemens Medical Solutions USA, Inc., Boston, MA, USA
| | - Selcuk Kucukseymen
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Hassan Haji-Valizadeh
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Jennifer Rodriguez
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Amanda Paskavitz
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Patrick Pierce
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Beth Goddu
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Richard B Thompson
- Department of Biomedical Engineering, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada
| | - Reza Nezafat
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
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Guo R, El-Rewaidy H, Assana S, Cai X, Amyar A, Chow K, Bi X, Yankama T, Cirillo J, Pierce P, Goddu B, Ngo L, Nezafat R. Accelerated cardiac T 1 mapping in four heartbeats with inline MyoMapNet: a deep learning-based T 1 estimation approach. J Cardiovasc Magn Reson 2022; 24:6. [PMID: 34986850 PMCID: PMC8734349 DOI: 10.1186/s12968-021-00834-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 11/30/2021] [Indexed: 11/24/2022] Open
Abstract
PURPOSE To develop and evaluate MyoMapNet, a rapid myocardial T1 mapping approach that uses fully connected neural networks (FCNN) to estimate T1 values from four T1-weighted images collected after a single inversion pulse in four heartbeats (Look-Locker, LL4). METHOD We implemented an FCNN for MyoMapNet to estimate T1 values from a reduced number of T1-weighted images and corresponding inversion-recovery times. We studied MyoMapNet performance when trained using native, post-contrast T1, or a combination of both. We also explored the effects of number of T1-weighted images (four and five) for native T1. After rigorous training using in-vivo modified Look-Locker inversion recovery (MOLLI) T1 mapping data of 607 patients, MyoMapNet performance was evaluated using MOLLI T1 data from 61 patients by discarding the additional T1-weighted images. Subsequently, we implemented a prototype MyoMapNet and LL4 on a 3 T scanner. LL4 was used to collect T1 mapping data in 27 subjects with inline T1 map reconstruction by MyoMapNet. The resulting T1 values were compared to MOLLI. RESULTS MyoMapNet trained using a combination of native and post-contrast T1-weighted images had excellent native and post-contrast T1 accuracy compared to MOLLI. The FCNN model using four T1-weighted images yields similar performance compared to five T1-weighted images, suggesting that four T1 weighted images may be sufficient. The inline implementation of LL4 and MyoMapNet enables successful acquisition and reconstruction of T1 maps on the scanner. Native and post-contrast myocardium T1 by MOLLI and MyoMapNet was 1170 ± 55 ms vs. 1183 ± 57 ms (P = 0.03), and 645 ± 26 ms vs. 630 ± 30 ms (P = 0.60), and native and post-contrast blood T1 was 1820 ± 29 ms vs. 1854 ± 34 ms (P = 0.14), and 508 ± 9 ms vs. 514 ± 15 ms (P = 0.02), respectively. CONCLUSION A FCNN, trained using MOLLI data, can estimate T1 values from only four T1-weighted images. MyoMapNet enables myocardial T1 mapping in four heartbeats with similar accuracy as MOLLI with inline map reconstruction.
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Affiliation(s)
- Rui Guo
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, MA, 02215, Boston, USA
| | - Hossam El-Rewaidy
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, MA, 02215, Boston, USA
| | - Salah Assana
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, MA, 02215, Boston, USA
| | - Xiaoying Cai
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, MA, 02215, Boston, USA
- Siemens Medical Solutions USA, Inc, Boston, MA, USA
| | - Amine Amyar
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, MA, 02215, Boston, USA
| | - Kelvin Chow
- Siemens Medical Solutions USA, Inc, Chicago, IL, USA
| | - Xiaoming Bi
- Siemens Medical Solutions USA, Inc, Chicago, IL, USA
| | - Tuyen Yankama
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, MA, 02215, Boston, USA
| | - Julia Cirillo
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, MA, 02215, Boston, USA
| | - Patrick Pierce
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, MA, 02215, Boston, USA
| | - Beth Goddu
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, MA, 02215, Boston, USA
| | - Long Ngo
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, MA, 02215, Boston, USA
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, MA, 02215, Boston, USA.
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Haji-Valizadeh H, Guo R, Kucukseymen S, Cai X, Rodriguez J, Pierce P, Goddu B, Manning W, Nezafat R. Artifact reduction in free-breathing, free-running myocardial perfusion imaging with interleaved non-selective RF excitations. Magn Reson Med 2021; 86:954-963. [PMID: 33764599 DOI: 10.1002/mrm.28765] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 02/13/2021] [Accepted: 02/15/2021] [Indexed: 12/22/2022]
Abstract
PURPOSE To reduce inflow and motion artifacts in free-breathing, free-running, steady-state spoiled gradient echo T1 -weighted (SPGR) myocardial perfusion imaging. METHOD Unsaturated spins from inflowing blood or out-of-plane motion cause flashing artifacts in free-running SPGR myocardial perfusion. During free-running SPGR, 1 non-selective RF excitation was added after every 3 slice-selective RF excitations to suppress inflow artifacts by forcing magnetization in neighboring regions to steady-state. Bloch simulations and phantom experiments were performed to evaluate the impact of the flip angle and non-selective RF frequency on inflowing spins and tissue contrast. Free-running perfusion with (n = 11) interleaved non-selective RF or without (n = 11) were studied in 22 subjects (age = 60.2 ± 14.3 years, 11 male). Perfusion images were graded on a 5-point Likert scale for conspicuity of wall enhancement, inflow/motion artifact, and streaking artifact and compared using Wilcoxon sum-rank testing. RESULT Numeric simulation showed that 1 non-selective RF excitation applied after every 3 slice-selective RF excitations produced superior out-of-plane signal suppression compared to 1 non-selective RF excitation applied after every 6 or 9 slice-selective RF excitations. In vitro experiments showed that a 30° flip angle produced near-optimal myocardial contrast. In vivo experiments demonstrated that the addition of interleaved non-selective RF significantly (P < .01) improved conspicuity of wall enhancement (mean score = 4.4 vs. 3.2) and reduced inflow/motion (mean score = 4.5 vs. 2.5) and streaking (mean score = 3.9 vs. 2.4) artifacts. CONCLUSION Non-selective RF excitations interleaved between slice-selective excitations can reduce image artifacts in free-breathing, ungated perfusion images. Further studies are warranted to assess the diagnostic accuracy of the proposed solution for evaluating myocardial ischemia.
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Affiliation(s)
- Hassan Haji-Valizadeh
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Rui Guo
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Selcuk Kucukseymen
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Xiaoying Cai
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.,Siemens Medical Solutions Inc., Boston, Massachusetts, USA
| | - Jennifer Rodriguez
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Patrick Pierce
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Beth Goddu
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Warren Manning
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.,Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
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Haji-Valizadeh H, Guo R, Kucukseymen S, Paskavitz A, Cai X, Rodriguez J, Pierce P, Goddu B, Kim D, Manning W, Nezafat R. Highly accelerated free-breathing real-time phase contrast cardiovascular MRI via complex-difference deep learning. Magn Reson Med 2021; 86:804-819. [PMID: 33720465 DOI: 10.1002/mrm.28750] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 01/18/2021] [Accepted: 02/05/2021] [Indexed: 12/11/2022]
Abstract
PURPOSE To develop and evaluate a real-time phase contrast (PC) MRI protocol via complex-difference deep learning (DL) framework. METHODS DL used two 3D U-nets to separately filter aliasing artifact from radial real-time velocity-compensated and complex-difference images. U-nets were trained with synthetic real-time PC generated from electrocardiograph (ECG) -gated, breath-hold, segmented PC (ECG-gated segmented PC) acquired at the ascending aorta of 510 patients. In 21 patients, free-breathing, ungated real-time (acceleration rate = 28.8) and ECG-gated segmented (acceleration rate = 2) PC were prospectively acquired at the ascending aorta. Hemodynamic parameters (cardiac output [CO], stroke volume [SV], and mean velocity at peak systole [peak mean velocity]) were measured for ECG-gated segmented and DL-filtered synthetic real-time PC and compared using Bland-Altman and linear regression analyses. Additionally, hemodynamic parameters were quantified from DL-filtered, compressed-sensing (CS) -reconstructed, and gridding reconstructed prospective real-time PC and compared to ECG-gated segmented PC. RESULTS Synthetic real-time PC with DL showed strong correlation (R > 0.98) and good agreement with ECG-gated segmented PC for quantified hemodynamic parameters (mean-difference: CO = -0.3 L/min, SV = -4.3 mL, peak mean velocity = -2.3 cm/s). On average, DL required 0.39 s/frame to filter prospective real-time PC, which was 4.6-fold faster than CS. Compared to CS, DL showed superior correlation, tighter limits of agreement (LOAs), better bias for peak mean velocity, and worse bias for CO and SV. Compared to gridding, DL showed similar correlation, tighter LOAs for CO and SV, similar bias for CO, and worse bias for SV and peak mean velocity. CONCLUSION The complex-difference DL framework accelerated real-time PC-MRI by nearly 28-fold, enabling rapid free-running real-time assessment of flow hemodynamics.
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Affiliation(s)
- Hassan Haji-Valizadeh
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Rui Guo
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Selcuk Kucukseymen
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Amanda Paskavitz
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Xiaoying Cai
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.,Siemens Medical Solutions USA, Inc., Boston, Massachusetts, USA
| | - Jennifer Rodriguez
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Patrick Pierce
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Beth Goddu
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Daniel Kim
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Warren Manning
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.,Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
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Jang J, El‐Rewaidy H, Ngo LH, Mancio J, Csecs I, Rodriguez J, Pierce P, Goddu B, Neisius U, Manning W, Nezafat R. Sensitivity of Myocardial Radiomic Features to Imaging Parameters in Cardiac
MR
Imaging. J Magn Reson Imaging 2021; 54:787-794. [DOI: 10.1002/jmri.27581] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 02/04/2021] [Accepted: 02/13/2021] [Indexed: 02/05/2023] Open
Affiliation(s)
- Jihye Jang
- Department of Medicine (Cardiovascular Division) Beth Israel Deaconess Medical Center and Harvard Medical School Boston Massachusetts USA
| | - Hossam El‐Rewaidy
- Department of Medicine (Cardiovascular Division) Beth Israel Deaconess Medical Center and Harvard Medical School Boston Massachusetts USA
| | - Long H. Ngo
- Department of Medicine (Cardiovascular Division) Beth Israel Deaconess Medical Center and Harvard Medical School Boston Massachusetts USA
- Department of Biostatistics Harvard T.H. Chan School of Public Health Boston Massachusetts USA
| | - Jennifer Mancio
- Department of Medicine (Cardiovascular Division) Beth Israel Deaconess Medical Center and Harvard Medical School Boston Massachusetts USA
| | - Ibolya Csecs
- Department of Medicine (Cardiovascular Division) Beth Israel Deaconess Medical Center and Harvard Medical School Boston Massachusetts USA
| | - Jennifer Rodriguez
- Department of Medicine (Cardiovascular Division) Beth Israel Deaconess Medical Center and Harvard Medical School Boston Massachusetts USA
| | - Patrick Pierce
- Department of Medicine (Cardiovascular Division) Beth Israel Deaconess Medical Center and Harvard Medical School Boston Massachusetts USA
| | - Beth Goddu
- Department of Medicine (Cardiovascular Division) Beth Israel Deaconess Medical Center and Harvard Medical School Boston Massachusetts USA
| | - Ulf Neisius
- Department of Medicine (Cardiovascular Division) Beth Israel Deaconess Medical Center and Harvard Medical School Boston Massachusetts USA
| | - Warren Manning
- Department of Medicine (Cardiovascular Division) Beth Israel Deaconess Medical Center and Harvard Medical School Boston Massachusetts USA
- Radiology Beth Israel Deaconess Medical Center and Harvard Medical School Boston Massachusetts USA
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division) Beth Israel Deaconess Medical Center and Harvard Medical School Boston Massachusetts USA
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Guo R, Cai X, Kucukseymen S, Rodriguez J, Paskavitz A, Pierce P, Goddu B, Thompson RB, Nezafat R. Free-breathing simultaneous myocardial T 1 and T 2 mapping with whole left ventricle coverage. Magn Reson Med 2020; 85:1308-1321. [PMID: 33078443 DOI: 10.1002/mrm.28506] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 08/13/2020] [Accepted: 08/14/2020] [Indexed: 01/20/2023]
Abstract
PURPOSE To develop a free-breathing sequence, that is, Multislice Joint T1 -T2 , for simultaneous measurement of myocardial T1 and T2 for multiple slices to achieve whole left-ventricular coverage. METHODS Multislice Joint T1 -T2 adopts slice-interleaved acquisition to collect 10 single-shot electrocardiogram-triggered images for each slice prepared by saturation and T2 preparation to simultaneously estimate myocardial T1 and T2 and achieve whole left-ventricular coverage. Prospective slice-tracking using a respiratory navigator and retrospective image registration are used to reduce through-plane and in-plane motion, respectively. Multislice Joint T1 -T2 was validated through numerical simulations and phantom and in vivo experiments, and compared with saturation-recovery single-shot acquisition and T2 -prepared balanced Steady-State Free Precession (T2 -prep SSFP) sequences. RESULTS Phantom T1 and T2 from Multislice Joint T1 -T2 had good accuracy and precision, and were insensitive to heart rate. Multislice Joint T1 -T2 yielded T1 and T2 maps of nine left-ventricular slices in 1.4 minutes. The mean left-ventricular T1 difference between saturation-recovery single-shot acquisition and Multislice Joint T1 -T2 across healthy subjects and patients was 191 ms (1564 ± 60 ms versus 1373 ± 50 ms; P < .05) and 111 ms (1535 ± 49 ms vs 1423 ± 49 ms; P < .05), respectively. The mean difference in left-ventricular T2 between T2 -prep SSFP and Multislice Joint T1 -T2 across healthy subjects and patients was -6.3 ms (42.4 ± 1.4 ms vs 48.7 ± 2.5; P < .05) and -5.7 ms (41.6 ± 2.5 ms vs 47.3 ± 2.7; P < .05), respectively. CONCLUSION Multislice Joint T1 -T2 enables quantification of whole left-ventricular T1 and T2 during free breathing within a clinically feasible scan time of less than 2 minutes.
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Affiliation(s)
- Rui Guo
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Xiaoying Cai
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.,Siemens Medical Solutions USA, Inc., Boston, Massachusetts, USA
| | - Selcuk Kucukseymen
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Jennifer Rodriguez
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Amanda Paskavitz
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Patrick Pierce
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Beth Goddu
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Richard B Thompson
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
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11
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Guo R, Cai X, Kucukseymen S, Rodriguez J, Paskavitz A, Pierce P, Goddu B, Nezafat R. Free-breathing whole-heart multi-slice myocardial T 1 mapping in 2 minutes. Magn Reson Med 2020; 85:89-102. [PMID: 32662908 DOI: 10.1002/mrm.28402] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Revised: 05/13/2020] [Accepted: 06/08/2020] [Indexed: 12/26/2022]
Abstract
PURPOSE To develop and validate a saturation-delay-inversion recovery preparation, slice tracking and multi-slice based sequence for measuring whole-heart native T1 . METHOD The proposed free-breathing sequence performs T1 mapping of multiple left-ventricular slices by slice-interleaved acquisition to collect 10 electrocardiogram-triggered single-shot slice-selective images for each slice. A saturation-delay-inversion recovery pulse is used for T1 preparation. Prospective slice tracking by the diaphragm navigator and retrospective registration are used to reduce through-plane and in-plane motion, respectively. The proposed sequence was validated in both phantom and human subjects (12 healthy subjects and 15 patients who were referred for a clinical cardiac MR exam) and compared with saturation recovery single-shot acquisition (SASHA) and modified Look-Locker inversion recovery (MOLLI). RESULTS Phantom T1 measured by the proposed sequence had excellent agreement (R2 = 0.99) with the ground-truth T1 and was insensitive to heart rate. In both healthy subjects and patients, the proposed sequence yielded nine left-ventricular T1 maps per volume in less than 2 minutes (healthy volunteers: 1.8 ± 0.4 minutes; patients: 1.9 ± 0.2 minutes). The average T1 of whole left ventricle for all healthy subjects and patients were 1560 ± 61 and 1535 ± 49 ms by SASHA, 1208 ± 42 and 1233 ± 56 ms by MOLLI5(3)3, and 1397 ± 34 and 1433 ± 56 ms by the proposed sequence, respectively. The corresponding coefficient of variation of T1 were 6.2 ± 1.4% and 5.8 ± 1.6%, 5.3 ± 1.1% and 5.1 ± 0.8%, and 4.9 ± 0.8% and 4.5 ± 0.8%, respectively. CONCLUSION The proposed sequence enables quantification of whole heart T1 with good accuracy and precision in less than 2 minutes during free breathing.
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Affiliation(s)
- Rui Guo
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Xiaoying Cai
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA.,Siemens Medical Solutions USA, Inc., Boston, MA, USA
| | - Selcuk Kucukseymen
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Jennifer Rodriguez
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Amanda Paskavitz
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Patrick Pierce
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Beth Goddu
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
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Jang J, Ngo LH, Mancio J, Kucukseymen S, Rodriguez J, Pierce P, Goddu B, Nezafat R. Reproducibility of Segmentation-based Myocardial Radiomic Features with Cardiac MRI. Radiol Cardiothorac Imaging 2020; 2:e190216. [PMID: 32734275 DOI: 10.1148/ryct.2020190216] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Revised: 02/19/2020] [Accepted: 03/04/2020] [Indexed: 11/11/2022]
Abstract
Purpose To investigate reproducibility of myocardial radiomic features with cardiac MRI. Materials and Methods Test-retest studies were performed with a 3-T MRI system using commonly used cardiac MRI sequences of cine balanced steady-state free precession (cine bSSFP), T1-weighted and T2-weighted imaging, and quantitative T1 and T2 mapping in phantom experiments and 10 healthy participants (mean ± standard deviation age, 29 years ± 13). In addition, this study assessed repeatability in 51 patients (56 years ± 14) who underwent imaging twice during the same session. Three readers independently delineated the myocardium to investigate inter- and intraobserver reproducibility of radiomic features. A total of 1023 radiomic features were extracted by using PyRadiomics (https://pyradiomics.readthedocs.io/) with 11 image filters and six feature families. The intraclass correlation coefficient (ICC) was estimated to assess reproducibility and repeatability, and features with ICCs greater than or equal to 0.8 were considered reproducible. Results Different reproducibility patterns were observed among sequences in in vivo test-retest studies. In cine bSSFP, the gray-level run-length matrix was the most reproducible feature family, and the wavelet low-pass filter applied horizontally and vertically was the most reproducible image filter. In T1 and T2 maps, intensity-based statistics (first-order) and gray-level co-occurrence matrix features were the most reproducible feature families, without a dominant reproducible image filter. Across all sequences, gray-level nonuniformity was the most frequently identified reproducible feature name. In inter- and intraobserver reproducibility studies, respectively, only 32%-47% and 61%-73% of features were identified as reproducible. Conclusion Only a small subset of myocardial radiomic features was reproducible, and these reproducible radiomic features varied among different sequences. Supplemental material is available for this article. © RSNA, 2020See also the commentary by Leiner in this issue.
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Affiliation(s)
- Jihye Jang
- Cardiovascular Division, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 (J.J., L.H.N., J.M., S.K., J.R., P.P., B.G., R.N.); Department of Computer Science, Technical University of Munich, Munich, Germany (J.J.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Mass (L.H.N.)
| | - Long H Ngo
- Cardiovascular Division, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 (J.J., L.H.N., J.M., S.K., J.R., P.P., B.G., R.N.); Department of Computer Science, Technical University of Munich, Munich, Germany (J.J.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Mass (L.H.N.)
| | - Jennifer Mancio
- Cardiovascular Division, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 (J.J., L.H.N., J.M., S.K., J.R., P.P., B.G., R.N.); Department of Computer Science, Technical University of Munich, Munich, Germany (J.J.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Mass (L.H.N.)
| | - Selcuk Kucukseymen
- Cardiovascular Division, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 (J.J., L.H.N., J.M., S.K., J.R., P.P., B.G., R.N.); Department of Computer Science, Technical University of Munich, Munich, Germany (J.J.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Mass (L.H.N.)
| | - Jennifer Rodriguez
- Cardiovascular Division, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 (J.J., L.H.N., J.M., S.K., J.R., P.P., B.G., R.N.); Department of Computer Science, Technical University of Munich, Munich, Germany (J.J.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Mass (L.H.N.)
| | - Patrick Pierce
- Cardiovascular Division, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 (J.J., L.H.N., J.M., S.K., J.R., P.P., B.G., R.N.); Department of Computer Science, Technical University of Munich, Munich, Germany (J.J.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Mass (L.H.N.)
| | - Beth Goddu
- Cardiovascular Division, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 (J.J., L.H.N., J.M., S.K., J.R., P.P., B.G., R.N.); Department of Computer Science, Technical University of Munich, Munich, Germany (J.J.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Mass (L.H.N.)
| | - Reza Nezafat
- Cardiovascular Division, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 (J.J., L.H.N., J.M., S.K., J.R., P.P., B.G., R.N.); Department of Computer Science, Technical University of Munich, Munich, Germany (J.J.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Mass (L.H.N.)
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13
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Nakamori S, Fahmy A, Jang J, El-Rewaidy H, Neisius U, Berg S, Goddu B, Pierce P, Rodriguez J, Hauser T, Ngo LH, Manning WJ, Nezafat R. Changes in Myocardial Native T1 and T2 After Exercise Stress. JACC Cardiovasc Imaging 2020; 13:667-680. [DOI: 10.1016/j.jcmg.2019.05.019] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Revised: 05/07/2019] [Accepted: 05/10/2019] [Indexed: 02/01/2023]
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Nakamori S, Jang J, Tschabrunn CM, Pierce P, Goddu B, Rodriguez J, Ngo LH, Tung NM, Manning WJ, Nezafat R. Noncontrast CMR for Detecting Early Myocardial Tissue Injury in a Swine Model of Anthracycline-Induced Cardiotoxicity. JACC Cardiovasc Imaging 2019; 12:2085-2087. [PMID: 31202765 DOI: 10.1016/j.jcmg.2019.05.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Revised: 04/30/2019] [Accepted: 05/01/2019] [Indexed: 10/26/2022]
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Akhtari S, Chuang ML, Salton CJ, Berg S, Kissinger KV, Goddu B, O’Donnell CJ, Manning WJ. Effect of isolated left bundle-branch block on biventricular volumes and ejection fraction: a cardiovascular magnetic resonance assessment. J Cardiovasc Magn Reson 2018; 20:66. [PMID: 30231875 PMCID: PMC6146610 DOI: 10.1186/s12968-018-0457-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2017] [Accepted: 05/08/2018] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND Left bundle branch block (LBBB) is associated with abnormal left ventricular (LV) contraction, and is frequently associated with co-morbid cardiovascular disease, but the effect of an isolated (i.e. in the absence of cardiovascular dissease) LBBB on biventricular volumes and ejection fraction (EF) is not well characterized. The objective of this study was to compare LV and right ventricular (RV) volumes and EF in adults with an isolated LBBB to matched healthy controls and to population-derived normative values, using cardiovascular magnetic resonance (CMR) imaging. METHODS We reviewed our clinical echocardiography database and the Framingham Heart Study Offspring cohort CMR database to identify adults with an isolated LBBB. Age-, sex-, hypertension-status, and body-surface area (BSA)-matched controls were identified from the Offspring cohort. All study subjects were scanned using the same CMR hardware and imaging sequence. Isolated-LBBB cases were compared with matched controls using Wilcoxon paired signed-rank test, and to normative reference values via Z-score. RESULTS Isolated-LBBB subjects (n = 18, 10F) ranged in age from 37 to 82 years. An isolated LBBB was associated with larger LV end-diastolic and end-systolic volumes (both p < 0.01) and lower LVEF (56+/- 7% vs. 68+/- 6%; p <0.001) with similar myocardial contraction fraction. LVEF in isolated LBBB was nearly two standard deviations (Z = - 1.95) below mean sex and age-matched group values. LV stroke volume, cardiac output, and mass, and all RV parameters were similar (p = NS) between the groups. CONCLUSIONS Adults with an isolated LBBB have greater LV volumes and markedly reduced LVEF, despite the absence of overt cardiovascular disease. These data may be useful toward the clinical interpretation of imaging studies performed on patients with an isolated LBBB.
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MESH Headings
- Adult
- Aged
- Aged, 80 and over
- Bundle-Branch Block/complications
- Bundle-Branch Block/diagnostic imaging
- Bundle-Branch Block/physiopathology
- Case-Control Studies
- Databases, Factual
- Female
- Humans
- Hypertrophy, Left Ventricular/diagnostic imaging
- Hypertrophy, Left Ventricular/etiology
- Hypertrophy, Left Ventricular/physiopathology
- Magnetic Resonance Imaging
- Male
- Middle Aged
- Myocardial Contraction
- Predictive Value of Tests
- Stroke Volume
- Ventricular Dysfunction, Left/diagnostic imaging
- Ventricular Dysfunction, Left/etiology
- Ventricular Dysfunction, Left/physiopathology
- Ventricular Function, Left
- Ventricular Function, Right
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Affiliation(s)
- Shadi Akhtari
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215 USA
| | - Michael L. Chuang
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215 USA
- The NHLBI’s Framingham Heart Study, Framingham, MA USA
| | - Carol J. Salton
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215 USA
| | - Sophie Berg
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215 USA
| | - Kraig V. Kissinger
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215 USA
| | - Beth Goddu
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215 USA
| | - Christopher J. O’Donnell
- The NHLBI’s Framingham Heart Study, Framingham, MA USA
- Cardiology Section, Veterans Affairs Healthcare System, Boston, MA USA
| | - Warren J. Manning
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215 USA
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA USA
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Wang C, Jang J, Neisius U, Nezafat M, Fahmy A, Kang J, Rodriguez J, Goddu B, Pierce P, Berg S, Zhang J, Wang X, Nezafat R. Black blood myocardial T 2 mapping. Magn Reson Med 2018; 81:153-166. [PMID: 30058162 DOI: 10.1002/mrm.27360] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2017] [Revised: 04/21/2018] [Accepted: 04/23/2018] [Indexed: 01/04/2023]
Abstract
PURPOSE To develop a black blood heart-rate adaptive T2 -prepared balanced steady-state free-precession (BEATS) sequence for myocardial T2 mapping. METHODS In BEATS, blood suppression is achieved by using a combination of preexcitation and double inversion recovery pulses. The timing and flip angles of the preexcitation pulse are auto-calculated in each patient based on heart rate. Numerical simulations, phantom studies, and in vivo studies were conducted to evaluate the performance of BEATS. BEATS T2 maps were acquired in 36 patients referred for clinical cardiac MRI and in 1 swine with recent myocardial infarction. Two readers assessed all images acquired in patients to identify the presence of artifacts associated with slow blood flow. RESULTS Phantom experiments showed that the BEATS sequence provided accurate T2 values over a wide range of simulated heart rates. Black blood myocardial T2 maps were successfully obtained in all subjects. No significant difference was found between the average T2 measurements obtained from the BEATS and conventional bright-blood T2 ; however, there was a decrease in precision using the BEATS sequence. A suppression of the blood pool resulted in sharper definition of the blood-myocardium border and reduced partial voluming effect. The subjective assessment showed that 16% (18 out of 108) of short-axis slices have residual blood artifacts (12 in the apical slice, 4 in the midventricular slice, and 2 in the basal slice). CONCLUSION The BEATS sequence yields dark blood myocardial T2 maps with better definition of the blood-myocardium border. Further studies are warranted to evaluate diagnostic accuracy of black blood T2 mapping.
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Affiliation(s)
- Chengyan Wang
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts.,Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, People's Republic of China
| | - Jihye Jang
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts.,Department of Computer Science, Technical University of Munich, Munich, Germany
| | - Ulf Neisius
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Maryam Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Ahmed Fahmy
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts.,Biomedical Engineering Department, Cairo University, Giza, Egypt
| | - Jinkyu Kang
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Jennifer Rodriguez
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Beth Goddu
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Patrick Pierce
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Sophie Berg
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Jue Zhang
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, People's Republic of China
| | - Xiaoying Wang
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, People's Republic of China.,Department of Radiology, Peking University First Hospital, Beijing, People's Republic of China
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
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Tang M, Basha T, Berg S, Kissinger KV, Goddu B, Manning WJ, Nezafat R. Left atrial wall imaging using a novel black-blood late gadolinium enhancement sequence. J Cardiovasc Magn Reson 2016. [PMCID: PMC5032178 DOI: 10.1186/1532-429x-18-s1-p62] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
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18
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Kato S, Bellm S, Roujol S, Jang J, Basha T, Berg S, Kissinger KV, Goddu B, Maron M, Manning WJ, Nezafat R. Diffuse Myocardial Fibrosis detected by Multi-slice T1 Mapping using Slice Interleaved T1 (STONE) Sequence in Patients with Hypertrophic Cardiomyopathy. J Cardiovasc Magn Reson 2016. [PMCID: PMC5032287 DOI: 10.1186/1532-429x-18-s1-p238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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19
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Bellm S, Basha T, Ngo L, Berg S, Kissinger KV, Goddu B, Manning WJ, Nezafat R. Reproducibility of slice-interleaved myocardial T2 mapping sequences. J Cardiovasc Magn Reson 2016. [PMCID: PMC5032037 DOI: 10.1186/1532-429x-18-s1-p54] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023] Open
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20
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Bellm S, Kato S, Shah RV, Berg S, Kissinger KV, Goddu B, Ngo L, Manning WJ, Nezafat R. The native T1 in remote myocardium of patients with prior chronic infarction is not normal. J Cardiovasc Magn Reson 2016. [PMCID: PMC5032617 DOI: 10.1186/1532-429x-18-s1-p102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
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21
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Akhtari S, Chuang ML, Berg S, Kissinger KV, Goddu B, Manning WJ. Left and Right Ventricular Volumes and Global Systolic Function in Isolated Left Bundle Branch Block: A Cardiac Magnetic Resonance Imaging Study. J Cardiovasc Magn Reson 2016. [PMCID: PMC5032546 DOI: 10.1186/1532-429x-18-s1-p296] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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22
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Bellm S, Ngo L, Jang J, Berg S, Kissinger KV, Goddu B, Manning WJ, Nezafat R. Blood T1 measurements using slice-interleaved T1 mapping (STONE) sequence. J Cardiovasc Magn Reson 2016. [PMCID: PMC5032439 DOI: 10.1186/1532-429x-18-s1-p57] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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23
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Kato S, Roujol S, Akhtari S, Delling FN, Jang J, Basha T, Berg S, Kissinger KV, Goddu B, Manning WJ, Nezafat R. Papillary muscle native T1 time is associated with severity of functional mitral regurgitation in patients with non-ischemic dilated cardiomyopathy. J Cardiovasc Magn Reson 2016. [PMCID: PMC5032423 DOI: 10.1186/1532-429x-18-s1-p244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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24
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Bellm S, Basha T, Ngo L, Berg S, Kissinger KV, Goddu B, Manning WJ, Nezafat R. Reproducibility of slice-interleaved T1 (STONE) mapping sequence. J Cardiovasc Magn Reson 2016. [PMCID: PMC5032266 DOI: 10.1186/1532-429x-18-s1-p51] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
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25
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Kato S, Nakamori S, Roujol S, Delling FN, Akhtari S, Jang J, Basha T, Berg S, Kissinger KV, Goddu B, Manning WJ, Nezafat R. Relationship between native papillary muscle T 1 time and severity of functional mitral regurgitation in patients with non-ischemic dilated cardiomyopathy. J Cardiovasc Magn Reson 2016; 18:79. [PMID: 27846845 PMCID: PMC5111188 DOI: 10.1186/s12968-016-0301-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2016] [Accepted: 10/29/2016] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Functional mitral regurgitation is one of the severe complications of non-ischemic dilated cardiomyopathy (DCM). Non-contrast native T1 mapping has emerged as a non-invasive method to evaluate myocardial fibrosis. We sought to evaluate the potential relationship between papillary muscle T1 time and mitral regurgitation in DCM patients. METHODS Forty DCM patients (55 ± 13 years) and 20 healthy adult control subjects (54 ± 13 years) were studied. Native T1 mapping was performed using a slice interleaved T1 mapping sequence (STONE) which enables acquisition of 5 slices in the short-axis plane within a 90 s free-breathing scan. We measured papillary muscle diameter, length and shortening. DCM patients were allocated into 2 groups based on the presence or absence of functional mitral regurgitation. RESULTS Papillary muscle T1 time was significantly elevated in DCM patients with mitral regurgitation (n = 22) in comparison to those without mitral regurgitation (n = 18) (anterior papillary muscle: 1127 ± 36 msec vs 1063 ± 16 msec, p < 0.05; posterior papillary muscle: 1124 ± 30 msec vs 1062 ± 19 msec, p < 0.05), but LV T1 time was similar (1129 ± 38 msec vs 1134 ± 58 msec, p = 0.93). Multivariate linear regression analysis showed that papillary muscle native T1 time (β = 0.10, 95 % CI: 0.05-0.17, p < 0.05) is significantly correlated with mitral regurgitant fraction. Elevated papillary muscle T1 time was associated with larger diameter, longer length and decreased papillary muscle shortening (all p values <0.05). CONCLUSIONS In DCM, papillary muscle native T1 time is significantly elevated and related to mitral regurgitant fraction.
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Affiliation(s)
- Shingo Kato
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215 USA
- Department of Cardiology, Yokohama City University Hospital, Yokohama, Japan
| | - Shiro Nakamori
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215 USA
| | - Sébastien Roujol
- Biomedical Engineering Department, King’s College London, London, UK
| | - Francesca N. Delling
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215 USA
| | - Shadi Akhtari
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215 USA
| | - Jihye Jang
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215 USA
| | - Tamer Basha
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215 USA
- Biomedical Engineering Department, Cairo University, Giza, Egypt
| | - Sophie Berg
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215 USA
| | - Kraig V. Kissinger
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215 USA
| | - Beth Goddu
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215 USA
| | - Warren J. Manning
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215 USA
- Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA USA
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215 USA
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26
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Bui AH, Roujol S, Foppa M, Kissinger KV, Goddu B, Hauser TH, Zimetbaum PJ, Ngo LH, Manning WJ, Nezafat R, Delling FN. Diffuse myocardial fibrosis in patients with mitral valve prolapse and ventricular arrhythmia. Heart 2016; 103:204-209. [PMID: 27515954 DOI: 10.1136/heartjnl-2016-309303] [Citation(s) in RCA: 91] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2016] [Revised: 07/09/2016] [Accepted: 07/19/2016] [Indexed: 12/18/2022] Open
Abstract
OBJECTIVE We aimed to investigate the association of diffuse myocardial fibrosis by cardiac magnetic resonance (CMR) T1 with complex ventricular arrhythmia (ComVA) in mitral valve prolapse (MVP). METHODS A retrospective analysis was performed on 41 consecutive patients with MVP referred for CMR between 2006 and 2011, and 31 healthy controls. Arrhythmia analysis was available in 23 patients with MVP with Holter/event monitors. Left ventricular (LV) septal T1 times were derived from Look-Locker sequences after administration of 0.2 mmol/kg gadopentetate dimeglumine. Late gadolinium enhancement (LGE) CMR images were available for all subjects. RESULTS Patients with MVP had significantly shorter postcontrast T1 times when compared with controls (334±52 vs 363±58 ms; p=0.03) despite similar LV ejection fraction (LVEF) (63±7 vs 60±6%, p=0.10). In a multivariable analysis, LV end-diastolic volume, LVEF and mitral regurgitation fraction were all correlates of T1 times, with LVEF and LV end-diastolic volume being the strongest (p=0.005, p=0.008 and p=0.045, respectively; model adjusted R2=0.30). Patients with MVP with ComVA had significantly shorter postcontrast T1 times when compared with patients with MVP without ComVA (324 (296, 348) vs 354 (327, 376) ms; p=0.03) and only 5/14 (36%) had evidence of papillary muscle LGE. CONCLUSIONS MVP may be associated with diffuse LV myocardial fibrosis as suggested by reduced postcontrast T1 times. Diffuse interstitial derangement is linked to subclinical systolic dysfunction, and may contribute to ComVA in MVP-related mitral regurgitation, even in the absence of focal fibrosis.
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Affiliation(s)
- An H Bui
- Cardiovascular Division, Department of Medicine, Harvard-Thorndike Electrophysiology Institute, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.,Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Sébastien Roujol
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Murilo Foppa
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.,Division of Cardiology, Hospital de Clinicas de Porto Alegre, Federal University of Rio Grande do Sul, Brazil
| | - Kraig V Kissinger
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Beth Goddu
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Thomas H Hauser
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Peter J Zimetbaum
- Cardiovascular Division, Department of Medicine, Harvard-Thorndike Electrophysiology Institute, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.,Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Long H Ngo
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Warren J Manning
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.,Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Reza Nezafat
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Francesca N Delling
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.,Department of Medicine, Division of Cardiology, University of California, San Francisco, California, USA
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Akcakaya M, Basha T, Tsao C, Berg S, Kissinger KV, Goddu B, Manning WJ, Nezafat R. High-resolution late gadolinium enhancement imaging with compressed sensing: a single-center clinical study. J Cardiovasc Magn Reson 2016. [PMCID: PMC5032303 DOI: 10.1186/1532-429x-18-s1-o56] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
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Kissinger KV, Berg S, Goddu B, Manning WJ. A greater incidence of nausea/vomiting reactions to Multihance® is seen among those of African descent. J Cardiovasc Magn Reson 2015. [PMCID: PMC4328265 DOI: 10.1186/1532-429x-17-s1-t6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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29
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Bui A, Roujol S, Foppa M, Kissinger K, Goddu B, Hauser T, Zimetbaum P, Manning W, Nezafat R, Delling F. CARDIAC MAGNETIC RESONANCE EVIDENCE OF MYOCARDIAL DIFFUSE FIBROSIS IN PATIENTS WITH MITRAL VALVE PROLAPSE. J Am Coll Cardiol 2015. [DOI: 10.1016/s0735-1097(15)61195-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Bui AH, Roujol S, Foppa M, Kissinger KV, Goddu B, Hauser TH, Zimetbaum PJ, Manning WJ, Nezafat R, Delling FN. Cardiac magnetic resonance evidence of diffuse myocardial fibrosis in patients with mitral valve prolapse. J Cardiovasc Magn Reson 2015. [PMCID: PMC4328942 DOI: 10.1186/1532-429x-17-s1-p337] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Basha T, Roujol S, Kissinger KV, Goddu B, Manning WJ, Nezafat R. Black blood late gadolinium enhancement using combined T2 magnetization preparation and inversion recovery. J Cardiovasc Magn Reson 2015. [PMCID: PMC4328755 DOI: 10.1186/1532-429x-17-s1-o14] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Basha TA, Akçakaya M, Goddu B, Berg S, Nezafat R. Accelerated three-dimensional cine phase contrast imaging using randomly undersampled echo planar imaging with compressed sensing reconstruction. NMR Biomed 2015; 28:30-39. [PMID: 25323208 DOI: 10.1002/nbm.3225] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2014] [Revised: 09/04/2014] [Accepted: 09/10/2014] [Indexed: 06/04/2023]
Abstract
The aim of this study was to implement and evaluate an accelerated three-dimensional (3D) cine phase contrast MRI sequence by combining a randomly sampled 3D k-space acquisition sequence with an echo planar imaging (EPI) readout. An accelerated 3D cine phase contrast MRI sequence was implemented by combining EPI readout with randomly undersampled 3D k-space data suitable for compressed sensing (CS) reconstruction. The undersampled data were then reconstructed using low-dimensional structural self-learning and thresholding (LOST). 3D phase contrast MRI was acquired in 11 healthy adults using an overall acceleration of 7 (EPI factor of 3 and CS rate of 3). For comparison, a single two-dimensional (2D) cine phase contrast scan was also performed with sensitivity encoding (SENSE) rate 2 and approximately at the level of the pulmonary artery bifurcation. The stroke volume and mean velocity in both the ascending and descending aorta were measured and compared between two sequences using Bland-Altman plots. An average scan time of 3 min and 30 s, corresponding to an acceleration rate of 7, was achieved for 3D cine phase contrast scan with one direction flow encoding, voxel size of 2 × 2 × 3 mm(3) , foot-head coverage of 6 cm and temporal resolution of 30 ms. The mean velocity and stroke volume in both the ascending and descending aorta were statistically equivalent between the proposed 3D sequence and the standard 2D cine phase contrast sequence. The combination of EPI with a randomly undersampled 3D k-space sampling sequence using LOST reconstruction allows a seven-fold reduction in scan time of 3D cine phase contrast MRI without compromising blood flow quantification.
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Affiliation(s)
- Tamer A Basha
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
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Roujol S, Foppa M, Basha TA, Akçakaya M, Kissinger KV, Goddu B, Berg S, Nezafat R. Accelerated free breathing ECG triggered contrast enhanced pulmonary vein magnetic resonance angiography using compressed sensing. J Cardiovasc Magn Reson 2014; 16:91. [PMID: 25416082 PMCID: PMC4240816 DOI: 10.1186/s12968-014-0091-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2014] [Accepted: 11/04/2014] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND To investigate the feasibility of accelerated electrocardiogram (ECG)-triggered contrast enhanced pulmonary vein magnetic resonance angiography (CE-PV MRA) with isotropic spatial resolution using compressed sensing (CS). METHODS Nineteen patients (59±13 y, 11 M) referred for MR were scanned using the proposed accelerated free breathing ECG-triggered 3D CE-PV MRA sequence (FOV=340×340×110 mm3, spatial resolution=1.5×1.5×1.5 mm3, acquisition window=140 ms at mid diastole and CS acceleration factor=5) and a conventional first-pass breath-hold non ECG-triggered 3D CE-PV MRA sequence. CS data were reconstructed offline using low-dimensional-structure self-learning and thresholding reconstruction (LOST) CS reconstruction. Quantitative analysis of PV sharpness and subjective qualitative analysis of overall image quality were performed using a 4-point scale (1: poor; 4: excellent). RESULTS Quantitative PV sharpness was increased using the proposed approach (0.73±0.09 vs. 0.51±0.07 for the conventional CE-PV MRA protocol, p<0.001). There were no significant differences in the subjective image quality scores between the techniques (3.32±0.94 vs. 3.53±0.77 using the proposed technique). CONCLUSIONS CS-accelerated free-breathing ECG-triggered CE-PV MRA allows evaluation of PV anatomy with improved sharpness compared to conventional non-ECG gated first-pass CE-PV MRA. This technique may be a valuable alternative for patients in which the first pass CE-PV MRA fails due to inaccurate first pass timing or inability of the patient to perform a 20-25 seconds breath-hold.
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Affiliation(s)
- Sébastien Roujol
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 USA
| | - Murilo Foppa
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 USA
| | - Tamer A Basha
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 USA
| | - Mehmet Akçakaya
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 USA
| | - Kraig V Kissinger
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 USA
| | - Beth Goddu
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 USA
| | - Sophie Berg
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 USA
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 USA
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Basha TA, Roujol S, Kissinger KV, Goddu B, Berg S, Manning WJ, Nezafat R. Free-breathing cardiac MR stress perfusion with real-time slice tracking. Magn Reson Med 2014; 72:689-98. [PMID: 24123153 PMCID: PMC3979504 DOI: 10.1002/mrm.24977] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2013] [Revised: 09/09/2013] [Accepted: 09/11/2013] [Indexed: 12/30/2022]
Abstract
PURPOSE To develop a free-breathing cardiac MR perfusion sequence with slice tracking for use after physical exercise. METHODS We propose to use a leading navigator, placed immediately before each 2D slice acquisition, for tracking the respiratory motion and updating the slice location in real-time. The proposed sequence was used to acquire CMR perfusion datasets in 12 healthy adult subjects and 8 patients. Images were compared with the conventional perfusion (i.e., without slice tracking) results from the same subjects. The location and geometry of the myocardium were quantitatively analyzed, and the perfusion signal curves were calculated from both sequences to show the efficacy of the proposed sequence. RESULTS The proposed sequence was significantly better compared with the conventional perfusion sequence in terms of qualitative image scores. Changes in the myocardial location and geometry decreased by 50% in the slice tracking sequence. Furthermore, the proposed sequence had signal curves that are smoother and less noisy. CONCLUSION The proposed sequence significantly reduces the effect of the respiratory motion on the image acquisition in both rest and stress perfusion scans.
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Affiliation(s)
- Tamer A. Basha
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA
| | - Sébastien Roujol
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA
| | - Kraig V. Kissinger
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA
| | - Beth Goddu
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA
| | - Sophie Berg
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA
| | - Warren J. Manning
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA
- Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA
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Pflugi S, Roujol S, Akçakaya M, Kawaji K, Foppa M, Heydari B, Goddu B, Kissinger K, Berg S, Manning WJ, Kozerke S, Nezafat R. Accelerated cardiac MR stress perfusion with radial sampling after physical exercise with an MR-compatible supine bicycle ergometer. Magn Reson Med 2014; 74:384-95. [PMID: 25105469 DOI: 10.1002/mrm.25405] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2013] [Revised: 06/30/2014] [Accepted: 07/22/2014] [Indexed: 12/30/2022]
Abstract
PURPOSE To evaluate the feasibility of accelerated cardiac MR (CMR) perfusion with radial sampling using nonlinear image reconstruction after exercise on an MR-compatible supine bike ergometer. METHODS Eight healthy subjects were scanned on two separate days using radial and Cartesian CMR perfusion sequences in rest and exercise stress perfusion. Four different methods (standard gridding, conjugate gradient SENSE [CG-SENSE], nonlinear inversion with joint estimation of coil-sensitivity profiles [NLINV] and compressed sensing with a total variation constraint [TV]) were compared for the reconstruction of radial data. Cartesian data were reconstructed using SENSE. All images were assessed by two blinded readers in terms of image quality and diagnostic value. RESULTS CG-SENSE and NLINV were scored more favorably than TV (in both rest and stress perfusion cases, P < 0.05) and gridding (for rest perfusion cases, P < 0.05). TV images showed patchy artifacts, which negatively influenced image quality especially in the stress perfusion images acquired with a low number of radial spokes. Although CG-SENSE and NLINV received better scores than Cartesian sampling in both rest and exercise stress perfusion cases, these differences were not statistically significant (P > 0.05). CONCLUSION We have demonstrated the feasibility of accelerated CMR perfusion using radial sampling after physical exercise using a supine bicycle ergometer in healthy subjects. For reconstruction of undersampled radial perfusion, CG-SENSE and NLINV resulted in better image quality than standard gridding or TV reconstruction. Further technical improvements and clinical assessment are needed before using this approach in patients with suspected coronary artery disease.
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Affiliation(s)
- Silvio Pflugi
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.,Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Sébastien Roujol
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Mehmet Akçakaya
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Keigo Kawaji
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Murilo Foppa
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Bobby Heydari
- Department of Medicine, Brigham and Women Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Beth Goddu
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Kraig Kissinger
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Sophie Berg
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Warren J Manning
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.,Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Sebastian Kozerke
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
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Weingärtner S, Akçakaya M, Roujol S, Basha T, Stehning C, Kissinger KV, Goddu B, Berg S, Manning WJ, Nezafat R. Free-breathing post-contrast three-dimensional T1 mapping: Volumetric assessment of myocardial T1 values. Magn Reson Med 2014; 73:214-22. [PMID: 24554395 DOI: 10.1002/mrm.25124] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2013] [Revised: 11/18/2013] [Accepted: 12/18/2013] [Indexed: 12/22/2022]
Abstract
PURPOSE To develop a three-dimensional (3D) free-breathing myocardial T1 mapping sequence for assessment of left ventricle diffuse fibrosis after contrast administration. METHODS In the proposed sequence, multiple 3D inversion recovery images are acquired in an interleaved manner. A mixed prospective/retrospective navigator scheme is used to obtain the 3D Cartesian k-space data with fully sampled center and randomly undersampled outer k-space. The resulting undersampled 3D k-space data are then reconstructed using compressed sensing. Subsequently, T1 maps are generated by voxel-wise curve fitting of the individual interleaved images. In a phantom study, the accuracy of the 3D sequence was evaluated against two-dimensional (2D) modified Look-Locker inversion recovery (MOLLI) and spin-echo sequences. In vivo T1 times of the proposed method were compared with 2D multislice MOLLI T1 mapping. Subsequently, the feasibility of high-resolution 3D T1 mapping with spatial resolution of 1.7 × 1.7 × 4 mm(3) was demonstrated. RESULTS The proposed method shows good agreement with 2D MOLLI and the spin-echo reference in phantom. No significant difference was found in the in vivo T1 times estimated using the proposed sequence and the 2D MOLLI technique (myocardium, 330 ± 66 ms versus 319 ± 93 ms; blood pools, 211 ± 68 ms versus 210 ± 98 ms). However, improved homogeneity, as measured using standard deviation of the T1 signal, was observed in the 3D T1 maps. CONCLUSION The proposed sequence enables high-resolution 3D T1 mapping after contrast injection during free-breathing with volumetric left ventricle coverage.
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Affiliation(s)
- Sebastian Weingärtner
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.,Computer Assisted Clinical Medicine, University Medical Center Mannheim, Heidelberg University, Mannheim, Germany
| | - Mehmet Akçakaya
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Sébastien Roujol
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Tamer Basha
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | | | - Kraig V Kissinger
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Beth Goddu
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Sophie Berg
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Warren J Manning
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.,Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Reza Nezafat
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
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Roujol S, Weingartner S, Foppa M, Chow K, Kawaji K, Kissinger KV, Goddu B, Berg S, Kellman P, Manning WJ, Thompson RB, Nezafat R. Accuracy and reproducibility of four T1 mapping sequences: a head-to-head comparison of MOLLI, ShMOLLI, SASHA, and SAPPHIRE. J Cardiovasc Magn Reson 2014. [PMCID: PMC4044062 DOI: 10.1186/1532-429x-16-s1-o26] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
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Basha TA, Kissinger KV, Goddu B, Berg S, Nezafat R. Accelerated 4D flow imaging using randomly undersampled echo planer imaging with compressed-sensing reconstruction. J Cardiovasc Magn Reson 2014. [PMCID: PMC4044877 DOI: 10.1186/1532-429x-16-s1-w18] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Basha TA, Roujol S, Kissinger KV, Goddu B, Nezafat R. Software platform for flexible automated reconstruction of CMR data in a clinically feasible workflow. J Cardiovasc Magn Reson 2014. [PMCID: PMC4043400 DOI: 10.1186/1532-429x-16-s1-w9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Roujol S, Basha TA, Akçakaya M, Foppa M, Chan RH, Kissinger KV, Goddu B, Berg S, Manning WJ, Nezafat R. 3D late gadolinium enhancement in a single prolonged breath-hold using supplemental oxygenation and hyperventilation. Magn Reson Med 2013; 72:850-7. [PMID: 24186772 DOI: 10.1002/mrm.24969] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2013] [Revised: 08/28/2013] [Accepted: 09/04/2013] [Indexed: 11/07/2022]
Abstract
PURPOSE To evaluate the feasibility of three-dimensional (3D) single breath-hold late gadolinium enhancement (LGE) of the left ventricle (LV) using supplemental oxygen and hyperventilation and compressed-sensing acceleration. METHODS Breath-hold metrics [breath-hold duration, diaphragmatic/LV position drift, and maximum variation of R wave to R wave (RR) interval] without and with supplemental oxygen and hyperventilation were assessed in healthy adult subjects using a real-time single shot acquisition. Ten healthy subjects and 13 patients then underwent assessment of the proposed 3D breath-hold LGE acquisition (field of view = 320 × 320 × 100 mm(3) , resolution = 1.6 × 1.6 × 5.0 mm(3) , acceleration rate of 4) and a free-breathing acquisition with right hemidiaphragm navigator (NAV) respiratory gating. Semiquantitative grading of overall image quality, motion artifact, myocardial nulling, and diagnostic value was performed by consensus of two blinded observers. RESULTS Supplemental oxygenation and hyperventilation increased the breath-hold duration (35 ± 11 s to 58 ± 21 s; P < 0.0125) without significant impact on diaphragmatic/LV position drift or maximum variation of RR interval (both P > 0.01). LGE images were of similar quality when compared with free-breathing acquisitions, but with reduced total scan time (85 ± 22 s to 35 ± 6 s; P < 0.001). CONCLUSIONS Supplemental oxygenation and hyperventilation allow for prolonged breath-holding and enable single breath-hold 3D accelerated LGE with similar image quality as free breathing with NAV.
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Affiliation(s)
- Sébastien Roujol
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
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Nam S, Hong SN, Akçakaya M, Kwak Y, Goddu B, Kissinger KV, Manning WJ, Tarokh V, Nezafat R. Compressed sensing reconstruction for undersampled breath-hold radial cine imaging with auxiliary free-breathing data. J Magn Reson Imaging 2013; 39:179-88. [PMID: 23857797 DOI: 10.1002/jmri.24098] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2012] [Accepted: 02/06/2013] [Indexed: 12/21/2022] Open
Abstract
PURPOSE To improve compressed sensing (CS) reconstruction of accelerated breath-hold (BH) radial cine magnetic resonance imaging (MRI) by exploiting auxiliary data acquired between different BHs. MATERIALS AND METHODS Cardiac function is usually assessed using segmented cine acquisitions over multiple BHs to cover the entire left ventricle (LV). Subjects are given a resting period between adjacent BHs, when conventionally no data are acquired and subjects rest in the scanner. In this study the resting periods between BHs were used to acquire additional free-breathing (FB) data, which are subsequently used to generate a sparsity constraint for each cardiac phase. Images reconstructed using the proposed sparsity constraint were compared with conventional CS using a composite image generated by averaging different cardiac phases. The efficacy of the proposed reconstruction was compared using indices of LV function and blood-myocardium sharpness. RESULTS The proposed method provided accurate LV ejection fraction measurements for 33% and 20% sampled datasets compared with fully sampled reference images, and showed 14% and 11% higher blood-myocardium border sharpness scores compared to the conventional CS. CONCLUSION The FB data acquired during resting periods can be efficiently used to improve the image quality of the undersampled BH data without increasing the total scan time.
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Affiliation(s)
- Seunghoon Nam
- Department of Medicine (Cardiovascular Division), Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA; School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
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Weingärtner S, Akçakaya M, Basha T, Kissinger KV, Goddu B, Berg S, Manning WJ, Nezafat R. Combined saturation/inversion recovery sequences for improved evaluation of scar and diffuse fibrosis in patients with arrhythmia or heart rate variability. Magn Reson Med 2013; 71:1024-34. [DOI: 10.1002/mrm.24761] [Citation(s) in RCA: 128] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Affiliation(s)
- Sebastian Weingärtner
- Department of Medicine; Beth Israel Deaconess Medical Center and Harvard Medical School; Boston, Massachusetts USA
- Computer Assisted Clinical Medicine; University Medical Center Mannheim, Heidelberg University; Mannheim Germany
| | - Mehmet Akçakaya
- Department of Medicine; Beth Israel Deaconess Medical Center and Harvard Medical School; Boston, Massachusetts USA
| | - Tamer Basha
- Department of Medicine; Beth Israel Deaconess Medical Center and Harvard Medical School; Boston, Massachusetts USA
| | - Kraig V. Kissinger
- Department of Medicine; Beth Israel Deaconess Medical Center and Harvard Medical School; Boston, Massachusetts USA
| | - Beth Goddu
- Department of Medicine; Beth Israel Deaconess Medical Center and Harvard Medical School; Boston, Massachusetts USA
| | - Sophie Berg
- Department of Medicine; Beth Israel Deaconess Medical Center and Harvard Medical School; Boston, Massachusetts USA
| | - Warren J. Manning
- Department of Medicine; Beth Israel Deaconess Medical Center and Harvard Medical School; Boston, Massachusetts USA
- Department of Radiology; Beth Israel Deaconess Medical Center and Harvard Medical School; Boston, Massachusetts USA
| | - Reza Nezafat
- Department of Medicine; Beth Israel Deaconess Medical Center and Harvard Medical School; Boston, Massachusetts USA
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Chan RH, Foppa M, Weingärtner S, Kissinger KV, Goddu B, Manning WJ, Nezafat R. Detection of left ventricular diffuse fibrosis with quantitative T1 mapping in patients with paroxysmal atrial fibrillation. J Cardiovasc Magn Reson 2013. [PMCID: PMC3559665 DOI: 10.1186/1532-429x-15-s1-p117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Affiliation(s)
- Raymond H Chan
- Beth Israel Deaconess Medical Center, Chestnut Hill, MA, USA
| | - Murilo Foppa
- Beth Israel Deaconess Medical Center, Chestnut Hill, MA, USA
| | | | | | - Beth Goddu
- Beth Israel Deaconess Medical Center, Chestnut Hill, MA, USA
| | | | - Reza Nezafat
- Beth Israel Deaconess Medical Center, Chestnut Hill, MA, USA
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Foppa M, Pond K, Jones DD, Kissinger KV, Goddu B, Schneider B, Jhaveri R, Manning WJ. Subcutaneous fat thickness, but not epicardial fat thickness, parallel weight reduction after bariatric surgery: a cardiac magnetic resonance study. J Cardiovasc Magn Reson 2013. [PMCID: PMC3559423 DOI: 10.1186/1532-429x-15-s1-e54] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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Akcakaya M, Rayatzadeh H, Hong S, Hauser TH, Chan RH, Basha TA, Kissinger KV, Goddu B, Manning WJ, Nezafat R. Improved late gadolinium enhancement imaging of left ventricle with isotropic spatial resolution. J Cardiovasc Magn Reson 2012. [PMCID: PMC3304806 DOI: 10.1186/1532-429x-14-s1-o22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Nam S, Akcakaya M, Kwak Y, Goddu B, Kissinger KV, Manning WJ, Tarokh V, Nezafat R. Improved accelerated breath-hold radial cine image reconstruction by acquiring additional free-breathing data between breath-holds. J Cardiovasc Magn Reson 2012. [PMCID: PMC3305222 DOI: 10.1186/1532-429x-14-s1-p269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Kwak Y, Nam S, Kissinger KV, Goddu B, Goepfert LA, Manning WJ, Tarokh V, Nezafat R. Accelerated phase contrast imaging using compressed sensing with complex difference sparsity. J Cardiovasc Magn Reson 2012. [PMCID: PMC3305709 DOI: 10.1186/1532-429x-14-s1-w24] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Moghari MH, Rayatzadeh H, Hong S, Chan RH, Akcakaya M, Goddu B, Goepfert LA, Kissinger KV, Manning WJ, Nezafat R. Free-breathing late gadolinium enhancement CMR with a fixed short scan time using CosMo. J Cardiovasc Magn Reson 2012. [PMCID: PMC3304973 DOI: 10.1186/1532-429x-14-s1-o21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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Moghari MH, Roujol S, Henningsson M, Chan RH, Hong S, Goddu B, Goepfert LA, Kissinger KV, Manning WJ, Nezafat R. Improved data acquisition efficiency for respiratory motion correction in coronary MRI. J Cardiovasc Magn Reson 2012. [PMCID: PMC3304968 DOI: 10.1186/1532-429x-14-s1-p246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
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