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Jafari R, Kandpal A, Verma R, Aggarwal V, Gupta RK, Singh A. Automatic pipeline for segmentation of LV myocardium on quantitative MR T1 maps using deep learning model and computation of radial T1 and ECV values. NMR IN BIOMEDICINE 2024:e5230. [PMID: 39097976 DOI: 10.1002/nbm.5230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 07/16/2024] [Accepted: 07/18/2024] [Indexed: 08/06/2024]
Abstract
Native T1 mapping is a non-invasive technique used for early detection of diffused myocardial abnormalities, and it provides baseline tissue characterization. Post-contrast T1 mapping enhances tissue differentiation, enables extracellular volume (ECV) calculation, and improves myocardial viability assessment. Accurate and precise segmenting of the left ventricular (LV) myocardium on T1 maps is crucial for assessing myocardial tissue characteristics and diagnosing cardiovascular diseases (CVD). This study presents a deep learning (DL)-based pipeline for automatically segmenting LV myocardium on T1 maps and automatic computation of radial T1 and ECV values. The study employs a multicentric dataset consisting of retrospective multiparametric MRI data of 332 subjects to develop and assess the performance of the proposed method. The study compared DL architectures U-Net and Deep Res U-Net for LV myocardium segmentation, which achieved a dice similarity coefficient of 0.84 ± 0.43 and 0.85 ± 0.03, respectively. The dice similarity coefficients computed for radial sub-segmentation of the LV myocardium on basal, mid-cavity, and apical slices were 0.77 ± 0.21, 0.81 ± 0.17, and 0.61 ± 0.14, respectively. The t-test performed between ground truth vs. predicted values of native T1, post-contrast T1, and ECV showed no statistically significant difference (p > 0.05) for any of the radial sub-segments. The proposed DL method leverages the use of quantitative T1 maps for automatic LV myocardium segmentation and accurately computing radial T1 and ECV values, highlighting its potential for assisting radiologists in objective cardiac assessment and, hence, in CVD diagnostics.
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Affiliation(s)
- Raufiya Jafari
- Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India
| | - Ankit Kandpal
- Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India
| | - Radhakrishan Verma
- Department of Radiology, Fortis Memorial Research Institute, Gurugram, India
| | - Vinayak Aggarwal
- Department of Cardiology, Fortis Memorial Research Institute, Gurugram, India
| | - Rakesh Kumar Gupta
- Department of Radiology, Fortis Memorial Research Institute, Gurugram, India
| | - Anup Singh
- Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India
- Department of Biomedical Engineering, AIIMS, New Delhi, India
- Yardi School of Artificial Intelligence, Indian Institute of Technology Delhi, New Delhi, India
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Chekhonin IV, Cohen O, Otazo R, Young RJ, Holodny AI, Pronin IN. Magnetic resonance relaxometry in quantitative imaging of brain gliomas: A literature review. Neuroradiol J 2024; 37:267-275. [PMID: 37133228 PMCID: PMC11138331 DOI: 10.1177/19714009231173100] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/04/2023] Open
Abstract
Magnetic resonance (MR) relaxometry is a quantitative imaging method that measures tissue relaxation properties. This review discusses the state of the art of clinical proton MR relaxometry for glial brain tumors. Current MR relaxometry technology also includes MR fingerprinting and synthetic MRI, which solve the inefficiencies and challenges of earlier techniques. Despite mixed results regarding its capability for brain tumor differential diagnosis, there is growing evidence that MR relaxometry can differentiate between gliomas and metastases and between glioma grades. Studies of the peritumoral zones have demonstrated their heterogeneity and possible directions of tumor infiltration. In addition, relaxometry offers T2* mapping that can define areas of tissue hypoxia not discriminated by perfusion assessment. Studies of tumor therapy response have demonstrated an association between survival and progression terms and dynamics of native and contrast-enhanced tumor relaxometric profiles. In conclusion, MR relaxometry is a promising technique for glial tumor diagnosis, particularly in association with neuropathological studies and other imaging techniques.
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Affiliation(s)
- Ivan V Chekhonin
- Federal State Autonomous Institution N.N. Burdenko National Medical Research Center of Neurosurgery of the Ministry of Health of the Russian Federation, Moscow, Russian Federation
- Federal State Budgetary Institution V.P. Serbsky National Medical Research Centre for Psychiatry and Narcology of the Ministry of Health of the Russian Federation, Moscow, Russian Federation
| | - Ouri Cohen
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Ricardo Otazo
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Robert J Young
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Andrei I Holodny
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA
- Department of Neuroscience, Weill Cornell Graduate School of the Medical Sciences, New York, NY, USA
| | - Igor N Pronin
- Federal State Autonomous Institution N.N. Burdenko National Medical Research Center of Neurosurgery of the Ministry of Health of the Russian Federation, Moscow, Russian Federation
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Cho J, Gagoski B, Kim TH, Wang F, Manhard MK, Dean D, Kecskemeti S, Caprihan A, Lo WC, Splitthoff DN, Liu W, Polak D, Cauley S, Setsompop K, Grant PE, Bilgic B. Time-efficient, high-resolution 3T whole-brain relaxometry using 3D-QALAS with wave-CAIPI readouts. Magn Reson Med 2024; 91:630-639. [PMID: 37705496 DOI: 10.1002/mrm.29865] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 07/16/2023] [Accepted: 08/25/2023] [Indexed: 09/15/2023]
Abstract
PURPOSE Volumetric, high-resolution, quantitative mapping of brain-tissue relaxation properties is hindered by long acquisition times and SNR challenges. This study combines time-efficient wave-controlled aliasing in parallel imaging (wave-CAIPI) readouts with the 3D quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS), enabling full-brain quantitative T1 , T2 , and proton density (PD) maps at 1.15-mm3 isotropic voxels in 3 min. METHODS Wave-CAIPI readouts were embedded in the standard 3D-QALAS encoding scheme, enabling full-brain quantitative parameter maps (T1 , T2 , and PD) at acceleration factors of R = 3 × 2 with minimum SNR loss due to g-factor penalties. The quantitative parameter maps were estimated using a dictionary-based mapping algorithm incorporating inversion efficiency and B1 -field inhomogeneity effects. The parameter maps using the accelerated protocol were quantitatively compared with those obtained from the conventional 3D-QALAS sequence using GRAPPA acceleration of R = 2 in the ISMRM/NIST phantom, and in 10 healthy volunteers. RESULTS When tested in both the ISMRM/NIST phantom and 10 healthy volunteers, the quantitative maps using the accelerated protocol showed excellent agreement against those obtained from conventional 3D-QALAS at RGRAPPA = 2. CONCLUSION Three-dimensional QALAS enhanced with wave-CAIPI readouts enables time-efficient, full-brain quantitative T1 , T2 , and PD mapping at 1.15 mm3 in 3 min at R = 3 × 2 acceleration. The quantitative maps obtained from the accelerated wave-CAIPI 3D-QALAS protocol showed very similar values to those from the standard 3D-QALAS (R = 2) protocol, alluding to the robustness and reliability of the proposed method.
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Affiliation(s)
- Jaejin Cho
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Borjan Gagoski
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Tae Hyung Kim
- Department of Computer Engineering, Hongik University, Seoul, South Korea
| | - Fuyixue Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Mary Kate Manhard
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Douglas Dean
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Steven Kecskemeti
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | | | - Wei-Ching Lo
- Siemens Medical Solutions USA, Inc., Charlestown, Massachusetts, USA
| | | | - Wei Liu
- Siemens Healthcare GmbH, Erlangen, Germany
| | | | - Stephen Cauley
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Kawin Setsompop
- Department of Electrical Engineering, Stanford University, Stanford, California, USA
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Patricia Ellen Grant
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
- Harvard/MIT Health Sciences and Technology, Cambridge, Massachusetts, USA
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Lin L, Liu P, Sun G, Wang J, Liang D, Zheng H, Jin Z, Wang Y. Bi-ventricular assessment with cardiovascular magnetic resonance at 5 Tesla: A pilot study. Front Cardiovasc Med 2022; 9:913707. [PMID: 36172590 PMCID: PMC9510665 DOI: 10.3389/fcvm.2022.913707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 08/19/2022] [Indexed: 11/21/2022] Open
Abstract
Background Cardiovascular magnetic resonance (CMR) imaging at ultra-high fields (UHF) such as 7T has encountered many challenges such as faster T2* relaxation, stronger B0 and B1+ field inhomogeneities and additional safety concerns due to increased specific absorption rate (SAR) and peripheral nervous stimulation (PNS). Recently, a new line of 5T whole body MRI system has become available, and this study aims at evaluating the performance and benefits of this new UHF system for CMR imaging. Methods Gradient echo (GRE) CINE imaging was performed on healthy volunteers at both 5 and 3T, and was compared to balanced steady-state-free-procession (bSSFP) CINE imaging at 3T as reference. Higher spatial resolution GRE CINE scans were additionally performed at 5T. All scans at both fields were performed with ECG-gating and breath-holding. Image quality was blindly evaluated by two radiologists, and the cardiac functional parameters (e.g., EDV/ESV/mass/EF) of the left and right ventricles were measured for statistical analyses using the Wilcoxon signed-rank test and Bland-Altman analysis. Results Compared to 3T GRE CINE imaging, 5T GRE CINE imaging achieved comparable or improved image quality with significantly superior SNR and CNR, and it has also demonstrated excellent capability for high resolution (1.0 × 1.0 × 6.0 mm3) imaging. Functional assessments from 5T GRE CINE images were highly similar with the 3T bSSFP CINE reference. Conclusions This pilot study has presented the initial evaluation of CMR CINE imaging at 5T UHF, which yielded superior image quality and accurate functional quantification when compared to 3T counterparts. Along with reliable ECG gating, the new 5T UHF system has the potential to achieve well-balanced performance for CMR applications.
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Affiliation(s)
- Lu Lin
- State Key Laboratory of Complex Severe and Rare Diseases, Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Peijun Liu
- State Key Laboratory of Complex Severe and Rare Diseases, Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Gan Sun
- State Key Laboratory of Complex Severe and Rare Diseases, Department of Medical Science Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jian Wang
- State Key Laboratory of Complex Severe and Rare Diseases, Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Dong Liang
- Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, China Academy of Sciences, Shenzhen, China
| | - Hairong Zheng
- Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, China Academy of Sciences, Shenzhen, China
| | - Zhengyu Jin
- State Key Laboratory of Complex Severe and Rare Diseases, Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yining Wang
- State Key Laboratory of Complex Severe and Rare Diseases, Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- *Correspondence: Yining Wang
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Langguth P, Salehi Ravesh M, Moritz JD, Rinne K, Harneit PL, Khodami JK, Graessner J, Uebing A, Jansen O, Both M, Hansen JH. Non-contrast enhanced magnetic resonance imaging for characterization of Fontan associated liver disease. Int J Cardiol 2021; 349:48-54. [PMID: 34808211 DOI: 10.1016/j.ijcard.2021.11.048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 11/16/2021] [Indexed: 11/05/2022]
Abstract
OBJECTIVES To evaluate the ability of non-contrast enhanced magnetic resonance imaging (MRI) techniques to characterize Fontan associated liver disease (FALD) in adolescent and adult Fontan patients. METHODS Fontan patients (n = 29) and healthy controls (n = 13) underwent an MRI protocol with T1, T2 and Apparent Diffusion Coefficient (ADC) mapping. Routine FALD screening included abdominal ultrasound and laboratory testing. RESULTS Median follow-up after Fontan operation was 15.1 (IQR 12.0-16.8) years. Distinct differences in tissue characteristics were visualized. T1 and T2 relaxation times were prolonged in Fontan patients, particularly of the right lobe (T1: 745 (IQR 715-784) ms vs. 586 (IQR 555-602) ms, p < 0.001; T2: 63 (IQR 59-64) ms vs. 58 (IQR 56-60) ms, p = 0.002). Left lobe ADC was lower in Fontan patients (1.10 (IQR 1.06-1.18) x 10-3 mm2/s vs. 1.23 (IQR 1.19-1.29) x 10-3 mm2/s, p < 0.001). T2 mapping was able to differentiate between controls and Fontan patients with different FALD severity. Right lobe T2 was higher in patients with moderate or severe in comparison to those with no or mild changes and healthy controls (64 (IQR 61-67) ms vs. 60 (IQR 59-63) ms vs. 58 (IQR 56-60) ms, p = 0.001). CONCLUSIONS Non-contrast enhanced MRI methods are able to visualize regional differences in liver tissue characteristics. T1 and T2 relaxation times were prolonged in Fontan patients suggestive of fibrosis or congestive hepatopathy, while reduced ADC might reflect impaired microperfusion. These methods have promising clinical potential for detection of liver abnormalities in Fontan patients. The usefulness of T2 mapping to grade FALD severity merits further investigation.
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Affiliation(s)
- Patrick Langguth
- Department of Radiology and Neuroradiology, University Hospital Schleswig-Holstein, Campus Kiel, Germany
| | - Mona Salehi Ravesh
- Department of Radiology and Neuroradiology, University Hospital Schleswig-Holstein, Campus Kiel, Germany
| | - Jörg Detlev Moritz
- Department of Radiology and Neuroradiology, University Hospital Schleswig-Holstein, Campus Kiel, Germany
| | - Katy Rinne
- Department of Congenital Heart Disease and Pediatric Cardiology, University Hospital Schleswig-Holstein, Campus Kiel, Germany
| | - Paul Lennard Harneit
- Department of Congenital Heart Disease and Pediatric Cardiology, University Hospital Schleswig-Holstein, Campus Kiel, Germany
| | - Joshua Kian Khodami
- Department of Congenital Heart Disease and Pediatric Cardiology, University Hospital Schleswig-Holstein, Campus Kiel, Germany
| | | | - Anselm Uebing
- Department of Congenital Heart Disease and Pediatric Cardiology, University Hospital Schleswig-Holstein, Campus Kiel, Germany; DZHK (German Center for Cardiovascular Research), Partner Site Hamburg/Kiel/Lübeck, Germany
| | - Olav Jansen
- Department of Radiology and Neuroradiology, University Hospital Schleswig-Holstein, Campus Kiel, Germany
| | - Marcus Both
- Department of Radiology and Neuroradiology, University Hospital Schleswig-Holstein, Campus Kiel, Germany
| | - Jan Hinnerk Hansen
- Department of Congenital Heart Disease and Pediatric Cardiology, University Hospital Schleswig-Holstein, Campus Kiel, Germany; DZHK (German Center for Cardiovascular Research), Partner Site Hamburg/Kiel/Lübeck, Germany.
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Zhang R, Shen Y, Bai Y, Zhang X, Wei W, Lin R, Feng Q, Wang M, Zhang M, Nittka M, Koerzdoerfer G, Wang M. Application of magnetic resonance fingerprinting to differentiate grade I transitional and fibrous meningiomas from meningothelial meningiomas. Quant Imaging Med Surg 2021; 11:1447-1457. [PMID: 33816181 DOI: 10.21037/qims-20-732] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Background The choice of surgical treatment for meningiomas is affected by the subtype and clinical characteristics. Therefore, an accurate preoperative diagnosis is essential. Current magnetic resonance imaging (MRI) technology is unable to distinguish between meningioma subtypes. In the present study, we compared and evaluated the utility of conventional MRI, magnetic resonance fingerprinting (MRF), and diffusion-weighted imaging (DWI) in differentiating World Health Organization grade I transitional and fibrous meningiomas from meningothelial meningiomas. Methods Forty-six patients with pathologically confirmed meningiomas (15 meningothelial, 18 transitional, and 13 fibrous) were enrolled in the present study. All patients underwent conventional MRI, MRF, and DWI scans before surgery using a 3T scanner. The Jonckheere-Terpstra test was used to analyze differences in the signal and enhancement characteristics of the three groups from T1-weighted imaging (T1WI) and T2-weighted imaging (T2WI). To investigate the difference in quantitative T1 and T2 values derived from MRF and apparent diffusion coefficient (ADC) values between the three groups using the Kruskal-Wallis test, regions of interest (ROIs) were manually drawn on the parenchymal portion of the tumors; P<0.017 was considered statistically significant after Bonferroni correction for multiple comparison. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performances of the different parameters. Results Meningothelial meningiomas had significantly higher T1 and T2 values than transitional and fibrous meningiomas (all P<0.017). ROC analysis results revealed that the combination of T1 and T2 values had the largest area under the curve (AUC). The AUC for the combination of T1 and T2 values was 0.826 between meningothelial and transitional meningiomas, and the AUC for the combination of T1 and T2 values between meningothelial and fibrous meningiomas was 0.903. No significant differences were found in the T1 and T2 values between transitional and fibrous meningiomas. There were also no statistically significant differences in the conventional MRI (including T1WI, T2WI, and contrast-enhanced T1WI) and ADC values between the three meningioma subtypes (all P>0.05). Conclusions MRF may provide more quantitative information than either conventional MRI or DWI for differentiating transitional and fibrous meningiomas from meningothelial meningiomas. T1 and T2 values derived from MRF may distinguish transitional and fibrous meningiomas from meningothelial meningiomas, and the combination of T1 and T2 values provides the highest diagnostic efficacy.
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Affiliation(s)
- Rui Zhang
- Department of Medical Imaging, Zhengzhou University People's Hospital and Henan Provincial People's Hospital, Zhengzhou, China.,Henan Key Laboratory of Neurological Imaging, Zhengzhou, China.,Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Yu Shen
- Department of Medical Imaging, Zhengzhou University People's Hospital and Henan Provincial People's Hospital, Zhengzhou, China.,Henan Key Laboratory of Neurological Imaging, Zhengzhou, China
| | - Yan Bai
- Department of Medical Imaging, Zhengzhou University People's Hospital and Henan Provincial People's Hospital, Zhengzhou, China.,Henan Key Laboratory of Neurological Imaging, Zhengzhou, China
| | | | - Wei Wei
- Department of Medical Imaging, Zhengzhou University People's Hospital and Henan Provincial People's Hospital, Zhengzhou, China.,Henan Key Laboratory of Neurological Imaging, Zhengzhou, China
| | - Ruijuan Lin
- Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Qin Feng
- Department of Medical Imaging, Zhengzhou University People's Hospital and Henan Provincial People's Hospital, Zhengzhou, China.,Henan Key Laboratory of Neurological Imaging, Zhengzhou, China
| | - Mengke Wang
- Department of Medical Imaging, Zhengzhou University People's Hospital and Henan Provincial People's Hospital, Zhengzhou, China.,Henan Key Laboratory of Neurological Imaging, Zhengzhou, China
| | - Menghuan Zhang
- Department of Medical Imaging, Zhengzhou University People's Hospital and Henan Provincial People's Hospital, Zhengzhou, China.,Henan Key Laboratory of Neurological Imaging, Zhengzhou, China
| | - Mathias Nittka
- Magnetic Resonance, Siemens Healthcare, Erlangen, Germany
| | | | - Meiyun Wang
- Department of Medical Imaging, Zhengzhou University People's Hospital and Henan Provincial People's Hospital, Zhengzhou, China.,Henan Key Laboratory of Neurological Imaging, Zhengzhou, China
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Heinen A, Gödecke S, Flögel U, Miklos D, Bottermann K, Spychala A, Gödecke A. 4-hydroxytamoxifen does not deteriorate cardiac function in cardiomyocyte-specific MerCreMer transgenic mice. Basic Res Cardiol 2021; 116:8. [PMID: 33544211 PMCID: PMC7864833 DOI: 10.1007/s00395-020-00841-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Accepted: 12/28/2020] [Indexed: 01/28/2023]
Abstract
Conditional, cell-type-specific transgenic mouse lines are of high value in cardiovascular research. A standard tool for cardiomyocyte-restricted DNA editing is the αMHC-MerCreMer/loxP system. However, there is an ongoing debate on the occurrence of cardiac side effects caused by unspecific Cre activity or related to tamoxifen/oil overload. Here, we investigated potential adverse effects of DNA editing by the αMHC-MerCreMer/loxP system in combination with a low-dose treatment protocol with the tamoxifen metabolite 4-hydroxytamoxifen (OH-Txf). αMHC-MerCreMer mice received intraperitoneally OH-Txf (20 mg/kg) for 5 or 10 days. These treatment protocols were highly efficient to induce DNA editing in adult mouse hearts. Multi-parametric magnetic resonance imaging revealed neither transient nor permanent effects on cardiac function during or up to 19 days after 5 day OH-Txf treatment. Furthermore, OH-Txf did not affect cardiac phosphocreatine/ATP ratios assessed by in vivo 31P MR spectroscopy, indicating no Cre-mediated side effects on cardiac energy status. No MRI-based indication for the development of cardiac fibrosis was found as mean T1 relaxation time was unchanged. Histological analysis of myocardial collagen III content after OH-Txf confirmed this result. Last, mean T2 relaxation time was not altered after Txf treatment suggesting no pronounced cardiac lipid accumulation or tissue oedema. In additional experiments, cardiac function was assessed for up to 42 days to investigate potential delayed side effects of OH-Txf treatment. Neither 5- nor 10-day treatment resulted in a depression of cardiac function. Efficient cardiomyocyte-restricted DNA editing that is free of unwanted side effects on cardiac function, energetics or fibrosis can be achieved in adult mice when the αMHC-MerCreMer/loxP system is activated by the tamoxifen metabolite OH-Txf.
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Affiliation(s)
- Andre Heinen
- Institut für Herz- und Kreislaufphysiologie, Medizinische Fakultät und Universitätsklinikum Düsseldorf, Heinrich-Heine-Universität Düsseldorf, Universitätsstraße 1, 40225, Düsseldorf, Germany
| | - Stefanie Gödecke
- Institut für Herz- und Kreislaufphysiologie, Medizinische Fakultät und Universitätsklinikum Düsseldorf, Heinrich-Heine-Universität Düsseldorf, Universitätsstraße 1, 40225, Düsseldorf, Germany
| | - Ulrich Flögel
- Institut für Molekulare Kardiologie, Medizinische Fakultät und Universitätsklinikum Düsseldorf, Heinrich-Heine-Universität Düsseldorf, 40225, Düsseldorf, Germany
| | - Dominika Miklos
- Institut für Herz- und Kreislaufphysiologie, Medizinische Fakultät und Universitätsklinikum Düsseldorf, Heinrich-Heine-Universität Düsseldorf, Universitätsstraße 1, 40225, Düsseldorf, Germany
| | - Katharina Bottermann
- Institut für Herz- und Kreislaufphysiologie, Medizinische Fakultät und Universitätsklinikum Düsseldorf, Heinrich-Heine-Universität Düsseldorf, Universitätsstraße 1, 40225, Düsseldorf, Germany
| | - André Spychala
- Institut für Herz- und Kreislaufphysiologie, Medizinische Fakultät und Universitätsklinikum Düsseldorf, Heinrich-Heine-Universität Düsseldorf, Universitätsstraße 1, 40225, Düsseldorf, Germany
| | - Axel Gödecke
- Institut für Herz- und Kreislaufphysiologie, Medizinische Fakultät und Universitätsklinikum Düsseldorf, Heinrich-Heine-Universität Düsseldorf, Universitätsstraße 1, 40225, Düsseldorf, Germany.
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Farrag NA, Lochbihler A, White JA, Ukwatta E. Evaluation of fully automated myocardial segmentation techniques in native and contrast-enhanced T1-mapping cardiovascular magnetic resonance images using fully convolutional neural networks. Med Phys 2020; 48:215-226. [PMID: 33131085 DOI: 10.1002/mp.14574] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 07/28/2020] [Accepted: 10/25/2020] [Indexed: 11/07/2022] Open
Abstract
PURPOSE T1-mapping cardiac magnetic resonance (CMR) imaging permits noninvasive quantification of myocardial fibrosis (MF); however, manual delineation of myocardial boundaries is time-consuming and introduces user-dependent variability for such measurements. In this study, we compare several automated pipelines for myocardial segmentation of the left ventricle (LV) in native and contrast-enhanced T1-maps using fully convolutional neural networks (CNNs). METHODS Sixty patients with known MF across three distinct cardiomyopathy states (20 ischemic (ICM), 20 dilated (DCM), and 20 hypertrophic (HCM)) underwent a standard CMR imaging protocol inclusive of cinematic (CINE), late gadolinium enhancement (LGE), and pre/post-contrast T1 imaging. Native and contrast-enhanced T1-mapping was performed using a shortened modified Look-Locker imaging (shMOLLI) technique at the basal, mid-level, and/or apex of the LV. Myocardial segmentations in native and post-contrast T1-maps were performed using three state-of-the-art CNN-based methods: standard U-Net, densely connected neural networks (Dense Nets), and attention networks (Attention Nets) after dividing the dataset using fivefold cross validation. These direct segmentation techniques were compared to an alternative registration-based segmentation method, wherein spatially corresponding CINE images are segmented automatically using U-Net, and a nonrigid registration technique transforms and propagates CINE contours to the myocardial regions of T1-maps. The methodologies were validated in 125 native and 100 contrast-enhanced T1-maps using standard segmentation accuracy metrics. Pearson correlation coefficient r and Bland-Altman analysis were used to compare the computed global T1 values derived by manual, U-Net, and CINE registration methodologies. RESULTS The U-Net-based method yielded optimal results in myocardial segmentation of native, contrast-enhanced, and CINE images compared to Dense Nets and Attention Nets. The direct U-Net-based method outperformed the CINE registration-based method in native T1-maps, yielding Dice similarity coefficient (DSC) of 82.7 ± 12% compared to 81.4 ± 6.9% (P < 0.0001). However, in contrast-enhanced T1-maps, the CINE-registration-based method outperformed direct U-Net segmentation, yielding DSC of 77.0 ± 9.6% vs 74.2 ± 18% across all patient groups (P = 0.0014) and specifically 73.2 ± 7.3% vs 65.5 ± 18% in the ICM patient group. High linear correlation of global T1 values was demonstrated in Pearson analysis of the U-Net-based technique and the CINE-registration technique in both native T1-maps (r = 0.93, P < 0.0001 and r = 0.87, P < 0.0001, respectively) and contrast-enhanced T1-maps (r = 0.93, P < 0.0001 and r = 0.98, P < 0.0001, respectively). CONCLUSIONS The direct U-Net-based myocardial segmentation technique provided accurate, fully automated segmentations in native and contrast-enhanced T1-maps. Myocardial borders can alternatively be segmented from spatially matched CINE images and applied to T1-maps via deformation and propagation through a modality-independent neighborhood descriptor (MIND). The direct U-Net approach is more efficient in myocardial segmentation of native T1-maps and eliminates cross-technique dependence. However, the CINE-registration-based technique may be more appropriate for contrast-enhanced T1-maps and/or for patients with dense regions of replacement fibrosis, such as those with ICM.
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Affiliation(s)
- Nadia A Farrag
- Department of Systems and Computer Engineering, Carleton University, 1125 Colonel By Drive, Mackenzie 4456, Ottawa, ON, K1S5B6, Canada
| | - Aidan Lochbihler
- Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, K1S 5B6, Canada
| | - James A White
- Department of Cardiac Sciences, University of Calgary, Calgary, AB, T2N 1N4, Canada
| | - Eranga Ukwatta
- School of Engineering, University of Guelph, Guelph, ON, N1G 2W1, Canada
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9
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Assadi H, Jones R, Swift AJ, Al-Mohammad A, Garg P. Cardiac MRI for the prognostication of heart failure with preserved ejection fraction: A systematic review and meta-analysis. Magn Reson Imaging 2020; 76:116-122. [PMID: 33221422 PMCID: PMC7819363 DOI: 10.1016/j.mri.2020.11.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2020] [Revised: 11/07/2020] [Accepted: 11/16/2020] [Indexed: 12/23/2022]
Abstract
Background Cardiac magnetic resonance imaging (MRI) is emerging as an important imaging tool in the assessment of heart failure with preserved ejection fraction (HFpEF). This systematic review and meta-analysis aim to synthesise and consolidate the current literature on cardiac MRI for prognostication of HFpEF. Methods design Systematic review and meta-analysis. Data sources: Scopus (PubMed and Embase) for studies published between 2008 and 2019. Eligibility criteria for study selection were studies that evaluated the prognostic role of cardiac MRI in HFpEF. Random effects meta-analyses of the reported hazard ratios (HR) for clinical outcomes was performed. Results Initial screening identified 97 studies. From these, only nine (9%) studies met all the criteria. The main cardiac MRI methods that demonstrated association to prognosis in HFpEF included late gadolinium enhancement (LGE) assessment of scar (n = 3), tissue characterisation with T1-mapping (n = 4), myocardial ischaemia (n = 1) and right ventricular dysfunction (RVSD) (n = 1). The pooled HR for all 9 studies was 1.52 (95% CI 1.05–1.99, P < 0.01). Sub-evaluation by cardiac MRI methods revealed varying HRs: LGE (net n = 402, HR = 1.6, 95% CI 0.42–2.78, P = 0.008); T1-mapping (n = 1623, HR = 1.25, 95% CI 0.891–1.60, P < 0.001); myocardial ischaemia or RVSD (n = 325, HR = 3.19, 95% CI 0.30–6.08, P = 0.03). Conclusion This meta-analysis demonstrates that multiparametric cardiac MRI has value in prognostication of patients with HFpEF. HFpEF patients with a detectable scar on LGE, fibrosis on T1-mapping, myocardial ischaemia or RVSD appear to have a worse prognosis. PROSPERO registration number CRD42020187228.
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Affiliation(s)
- Hosamadin Assadi
- Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - Rachel Jones
- Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - Andrew J Swift
- Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - Abdallah Al-Mohammad
- Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK; Sheffield Teaching Hospital NHS Foundation Trust, Sheffield, UK
| | - Pankaj Garg
- Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK; Sheffield Teaching Hospital NHS Foundation Trust, Sheffield, UK.
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10
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Wetscherek M, Rutschke W, Frank C, Stehning C, Lurz P, Grothoff M, Thiele H, Gutberlet M, Lücke C. High inter- and intra-observer agreement in mapping sequences compared to classical Lake Louise Criteria assessment of myocarditis by inexperienced observers. Clin Radiol 2020; 75:796.e17-796.e26. [DOI: 10.1016/j.crad.2020.05.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2019] [Accepted: 05/08/2020] [Indexed: 11/24/2022]
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11
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Nordio G, Bustin A, Odille F, Schneider T, Henningsson M, Prieto C, Botnar RM. Faster 3D saturation-recovery based myocardial T1 mapping using a reduced number of saturation points and denoising. PLoS One 2020; 15:e0221071. [PMID: 32275668 PMCID: PMC7147792 DOI: 10.1371/journal.pone.0221071] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Accepted: 03/21/2020] [Indexed: 11/19/2022] Open
Abstract
PURPOSE To accelerate the acquisition of free-breathing 3D saturation-recovery-based (SASHA) myocardial T1 mapping by acquiring fewer saturation points in combination with a post-processing 3D denoising technique to maintain high accuracy and precision. METHODS 3D SASHA T1 mapping acquires nine T1-weighted images along the saturation recovery curve, resulting in long acquisition times. In this work, we propose to accelerate conventional cardiac T1 mapping by reducing the number of saturation points. High T1 accuracy and low standard deviation (as a surrogate for precision) is maintained by applying a 3D denoising technique to the T1-weighted images prior to pixel-wise T1 fitting. The proposed approach was evaluated on a T1 phantom and 20 healthy subjects, by varying the number of T1-weighted images acquired between three and nine, both prospectively and retrospectively. Following the results from the healthy subjects, three patients with suspected cardiovascular disease were acquired using five T1-weighted images. T1 accuracy and precision was determined for all the acquisitions before and after denoising. RESULTS In the T1 phantom, no statistical difference was found in terms of accuracy and precision for the different number of T1-weighted images before or after denoising (P = 0.99 and P = 0.99 for accuracy, P = 0.64 and P = 0.42 for precision, respectively). In vivo, both prospectively and retrospectively, the precision improved considerably with the number of T1-weighted images employed before denoising (P<0.05) but was independent on the number of T1-weighted images after denoising. CONCLUSION We demonstrate the feasibility of accelerating 3D SASHA T1 mapping by reducing the number of acquired T1-weighted images in combination with an efficient 3D denoising, without affecting accuracy and precision of T1 values.
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Affiliation(s)
- Giovanna Nordio
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, England, United Kingdom
| | - Aurelien Bustin
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, England, United Kingdom
| | - Freddy Odille
- CIC-IT 1433, INSERM, Université de Lorraine and CHRU de Nancy, Nancy, France
- IADI, INSERM U1254 and Université de Lorraine, Nancy, France
| | | | - Markus Henningsson
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, England, United Kingdom
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, England, United Kingdom
- Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - René M. Botnar
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, England, United Kingdom
- Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
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12
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Elwazir MY, Bois JP, Abouezzeddine OF, Chareonthaitawee P. Imaging cardiac sarcoidosis and infiltrative diseases: diagnosis and therapeutic response. THE QUARTERLY JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING : OFFICIAL PUBLICATION OF THE ITALIAN ASSOCIATION OF NUCLEAR MEDICINE (AIMN) [AND] THE INTERNATIONAL ASSOCIATION OF RADIOPHARMACOLOGY (IAR), [AND] SECTION OF THE SOCIETY OF RADIOPHARMACEUTICAL CHEMISTRY AND BIOLOGY 2020; 64:51-73. [DOI: 10.23736/s1824-4785.20.03235-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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13
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Hamilton JI, Pahwa S, Adedigba J, Frankel S, O'Connor G, Thomas R, Walker JR, Killinc O, Lo WC, Batesole J, Margevicius S, Griswold M, Rajagopalan S, Gulani V, Seiberlich N. Simultaneous Mapping of T 1 and T 2 Using Cardiac Magnetic Resonance Fingerprinting in a Cohort of Healthy Subjects at 1.5T. J Magn Reson Imaging 2020; 52:1044-1052. [PMID: 32222092 DOI: 10.1002/jmri.27155] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Revised: 03/13/2020] [Accepted: 03/13/2020] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Cardiac MR fingerprinting (cMRF) is a novel technique for simultaneous T1 and T2 mapping. PURPOSE To compare T1 /T2 measurements, repeatability, and map quality between cMRF and standard mapping techniques in healthy subjects. STUDY TYPE Prospective. POPULATION In all, 58 subjects (ages 18-60). FIELD STRENGTH/SEQUENCE: cMRF, modified Look-Locker inversion recovery (MOLLI), and T2 -prepared balanced steady-state free precession (bSSFP) at 1.5T. ASSESSMENT T1 /T2 values were measured in 16 myocardial segments at apical, medial, and basal slice positions. Test-retest and intrareader repeatability were assessed for the medial slice. cMRF and conventional mapping sequences were compared using ordinal and two alternative forced choice (2AFC) ratings. STATISTICAL TESTS Paired t-tests, Bland-Altman analyses, intraclass correlation coefficient (ICC), linear regression, one-way analysis of variance (ANOVA), and binomial tests. RESULTS Average T1 measurements were: basal 1007.4±96.5 msec (cMRF), 990.0±45.3 msec (MOLLI); medial 995.0±101.7 msec (cMRF), 995.6±59.7 msec (MOLLI); apical 1006.6±111.2 msec (cMRF); and 981.6±87.6 msec (MOLLI). Average T2 measurements were: basal 40.9±7.0 msec (cMRF), 46.1±3.5 msec (bSSFP); medial 41.0±6.4 msec (cMRF), 47.4±4.1 msec (bSSFP); apical 43.5±6.7 msec (cMRF), 48.0±4.0 msec (bSSFP). A statistically significant bias (cMRF T1 larger than MOLLI T1 ) was observed in basal (17.4 msec) and apical (25.0 msec) slices. For T2 , a statistically significant bias (cMRF lower than bSSFP) was observed for basal (-5.2 msec), medial (-6.3 msec), and apical (-4.5 msec) slices. Precision was lower for cMRF-the average of the standard deviation measured within each slice was 102 msec for cMRF vs. 61 msec for MOLLI T1 , and 6.4 msec for cMRF vs. 4.0 msec for bSSFP T2 . cMRF and conventional techniques had similar test-retest repeatability as quantified by ICC (0.87 cMRF vs. 0.84 MOLLI for T1 ; 0.85 cMRF vs. 0.85 bSSFP for T2 ). In the ordinal image quality comparison, cMRF maps scored higher than conventional sequences for both T1 (all five features) and T2 (four features). DATA CONCLUSION This work reports on myocardial T1 /T2 measurements in healthy subjects using cMRF and standard mapping sequences. cMRF had slightly lower precision, similar test-retest and intrareader repeatability, and higher scores for map quality. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 1 J. Magn. Reson. Imaging 2020;52:1044-1052.
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Affiliation(s)
- Jesse I Hamilton
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Shivani Pahwa
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Joseph Adedigba
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Samuel Frankel
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Gregory O'Connor
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Rahul Thomas
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Jonathan R Walker
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Ozden Killinc
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Wei-Ching Lo
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Joshua Batesole
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Seunghee Margevicius
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA
| | - Mark Griswold
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Sanjay Rajagopalan
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA.,Division of Cardiovascular Medicine, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Vikas Gulani
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Nicole Seiberlich
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
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14
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Körzdörfer G, Kirsch R, Liu K, Pfeuffer J, Hensel B, Jiang Y, Ma D, Gratz M, Bär P, Bogner W, Springer E, Lima Cardoso P, Umutlu L, Trattnig S, Griswold M, Gulani V, Nittka M. Reproducibility and Repeatability of MR Fingerprinting Relaxometry in the Human Brain. Radiology 2019; 292:429-437. [PMID: 31210615 DOI: 10.1148/radiol.2019182360] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background Only sparse literature investigates the reproducibility and repeatability of relaxometry methods in MRI. However, statistical data on reproducibility and repeatability of any quantitative method is essential for clinical application. Purpose To evaluate the reproducibility and repeatability of two-dimensional fast imaging with steady-state free precession MR fingerprinting in vivo in human brains. Materials and Methods Two-dimensional section-selective MR fingerprinting based on a steady-state free precession sequence with an external radiofrequency transmit field, or B1+, correction was used to generate T1 and T2 maps. This prospective study was conducted between July 2017 and January 2018 with 10 scanners from a single manufacturer, including different models, at four different sites. T1 and T2 relaxation times and their variation across scanners (reproducibility) as well as across repetitions on a scanner (repeatability) were analyzed. The relative deviations of T1 and T2 to the average (95% confidence interval) were calculated for several brain compartments. Results Ten healthy volunteers (mean age ± standard deviation, 28.5 years ± 6.9; eight men, two women) participated in this study. Reproducibility and repeatability of T1 and T2 measures in the human brain varied across brain compartments (1.8%-20.9%) and were higher in solid tissues than in the cerebrospinal fluid. T1 measures in solid tissue brain compartments were more stable compared with T2 measures. The half-widths of the confidence intervals for relative deviations were 3.4% for mean T1 and 8.0% for mean T2 values across scanners. Intrascanner repeatability half-widths of the confidence intervals for relative deviations were in the range of 2.0%-3.1% for T1 and 3.1%-7.9% for T2. Conclusion This study provides values on reproducibility and repeatability of T1 and T2 relaxometry measured with fast imaging with steady-state free precession MR fingerprinting in brain tissues of healthy volunteers. Reproducibility and repeatability are considerably higher in solid brain compartments than in cerebrospinal fluid and are higher for T1 than for T2. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Barkhof and Parker in this issue.
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Affiliation(s)
- Gregor Körzdörfer
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Rainer Kirsch
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Kecheng Liu
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Josef Pfeuffer
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Bernhard Hensel
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Yun Jiang
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Dan Ma
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Marcel Gratz
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Peter Bär
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Wolfgang Bogner
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Elisabeth Springer
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Pedro Lima Cardoso
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Lale Umutlu
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Siegfried Trattnig
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Mark Griswold
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Vikas Gulani
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
| | - Mathias Nittka
- From Siemens Healthcare, Allee am Roethelheimpark 2, 91052 Erlangen, Germany (G.K., R.K., J.P., M.N.); Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (G.K., B.H.); Siemens Medical Solutions USA, Malvern, Pa (K.L.); Departments of Biomedical Engineering (Y.J., D.M., M. Griswold, V.G.) and Radiology (M. Griswold, V.G.), Case Western Reserve University, Cleveland, Ohio; Department of High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (M. Gratz); Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany (M. Gratz); Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Vienna, Austria (P.B., W.B., E.S., P.L.C., S.T.); Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (L.U.); and Christian Doppler Laboratory for Clinical Molecular MR Imaging, MOLIMA, Vienna, Austria (W.B., S.T.)
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15
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Cardiac magnetic resonance T1 mapping. Part 1: Aspects of acquisition and evaluation. Eur J Radiol 2018; 109:223-234. [PMID: 30539758 DOI: 10.1016/j.ejrad.2018.10.011] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2018] [Revised: 09/29/2018] [Accepted: 10/05/2018] [Indexed: 12/13/2022]
Abstract
While an enormous number of studies have documented pathological alterations of the myocardial native longitudinal relaxation time (T1) and the fraction of the extracellular myocardial volume (ECV), it has also become clear that continuously evolving T1 mapping sequence, acquisition and evaluation techniques have a substantial impact on quantitative results, making the translation of reported findings into routine clinical use particularly challenging. To provide a basis for the discussion of pathological myocardial T1 and ECV alterations, the present review aims to summarize the methodological aspects of myocardial T1 mapping along with technical and physiological factors influencing results and normal ranges of myocardial native T1 and ECV reported across studies.
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Bouazizi K, Rahhal A, Kusmia S, Evin M, Defrance C, Cluzel P, Berthet M, Atassi F, Leprince P, Lebreton G, Kachenoura N, Hatem SN, Redheuil A. Differentiation and quantification of fibrosis, fat and fatty fibrosis in human left atrial myocardium using ex vivo MRI. PLoS One 2018; 13:e0205104. [PMID: 30296279 PMCID: PMC6175289 DOI: 10.1371/journal.pone.0205104] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Accepted: 09/19/2018] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Atrial fibrillation is associated with an atrial cardiomyopathy composed mainly of fibrosis and adipose tissue accumulation. We hypothesized that MRI, when used in an optimal ex vivo setting allowing high spatial resolution without motion artifacts, can help characterizing the complex 3D left atrial (LA) wall composition in human myocardial samples, as compared to histology. METHODS This prospective case-control study was approved by the institutional review board. 3D MRI acquisitions including saturation-recovery T1 mapping and DIXON imaging was performed at 4.0 T on 9 human LA samples collected from patients who underwent cardiac surgery. Histological quantification of fibrosis and fat was obtained. MRI T1 maps were clustered based on a Gaussian Mixture Model allowing quantification of total, interstitial and fatty fibrosis components. Fat maps were computed from DIXON images and fat fractions were calculated. MRI measurements were performed on the same location as the histological analysis (plane) and on the entire sample volume (3D). RESULTS High correlations and levels of agreement were observed between MRI and histology for total (r = 0.93), interstitial (r = 0.93) and fatty fibrosis (r = 0.98) and fat (r = 0.96). Native T1 correlated with the amount of fibrosis from MRI and histology. The 3D MRI total, interstitial and fatty fibrosis ranges were between 6% and 23%, 4% and 17.3%; and 1.4% and 19.7% respectively. CONCLUSION High Field ex vivo MRI was able to quantify different LA myocardial components with high agreement in 2D with histology and moreover to provide 3D quantification of such components whereas in vivo application remains a challenge.
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Affiliation(s)
- Khaoula Bouazizi
- Institute of Cardiometabolism And Nutrition, La Pitié-Salpêtrière Hospital, Paris, France
- Sorbonne University, INSERM 1146, CNRS 7371, Laboratoire d’Imagerie Biomédicale, Paris, France
| | - Amer Rahhal
- Sorbonne University, Faculté de médecine, UMRS 1166, Research unit on cardiovascular, metabolic and nutrition diseases, Paris, France
| | - Slawomir Kusmia
- Institute of Cardiometabolism And Nutrition, La Pitié-Salpêtrière Hospital, Paris, France
| | - Morgane Evin
- Institute of Cardiometabolism And Nutrition, La Pitié-Salpêtrière Hospital, Paris, France
- Sorbonne University, INSERM 1146, CNRS 7371, Laboratoire d’Imagerie Biomédicale, Paris, France
| | - Carine Defrance
- Department of cardiovascular and thoracic surgery, Cardiology Institute, La Pitié-Salpêtrière Hospital AP-HP, Paris, France
| | - Philippe Cluzel
- Institute of Cardiometabolism And Nutrition, La Pitié-Salpêtrière Hospital, Paris, France
- Sorbonne University, INSERM 1146, CNRS 7371, Laboratoire d’Imagerie Biomédicale, Paris, France
- Department of cardiovascular imaging, interventional and thoracic radiology (DICVRIT), Cardiology Institute, La Pitié-Salpêtrière Hospital AP-HP, Paris, France
| | - Myriam Berthet
- Sorbonne University, Faculté de médecine, UMRS 1166, Research unit on cardiovascular, metabolic and nutrition diseases, Paris, France
| | - Fabrice Atassi
- Sorbonne University, Faculté de médecine, UMRS 1166, Research unit on cardiovascular, metabolic and nutrition diseases, Paris, France
| | - Pascal Leprince
- Department of cardiovascular and thoracic surgery, Cardiology Institute, La Pitié-Salpêtrière Hospital AP-HP, Paris, France
| | - Guillaume Lebreton
- Department of cardiovascular and thoracic surgery, Cardiology Institute, La Pitié-Salpêtrière Hospital AP-HP, Paris, France
| | - Nadjia Kachenoura
- Sorbonne University, INSERM 1146, CNRS 7371, Laboratoire d’Imagerie Biomédicale, Paris, France
| | - Stéphane N. Hatem
- Institute of Cardiometabolism And Nutrition, La Pitié-Salpêtrière Hospital, Paris, France
- Sorbonne University, Faculté de médecine, UMRS 1166, Research unit on cardiovascular, metabolic and nutrition diseases, Paris, France
- Department of cardiovascular and thoracic surgery, Cardiology Institute, La Pitié-Salpêtrière Hospital AP-HP, Paris, France
| | - Alban Redheuil
- Institute of Cardiometabolism And Nutrition, La Pitié-Salpêtrière Hospital, Paris, France
- Sorbonne University, INSERM 1146, CNRS 7371, Laboratoire d’Imagerie Biomédicale, Paris, France
- Department of cardiovascular imaging, interventional and thoracic radiology (DICVRIT), Cardiology Institute, La Pitié-Salpêtrière Hospital AP-HP, Paris, France
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17
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Nchimi A, Dibato JE, Davin L, Schoysman L, Oury C, Lancellotti P. Predicting Disease Progression and Mortality in Aortic Stenosis: A Systematic Review of Imaging Biomarkers and Meta-Analysis. Front Cardiovasc Med 2018; 5:112. [PMID: 30186838 PMCID: PMC6113371 DOI: 10.3389/fcvm.2018.00112] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2018] [Accepted: 08/02/2018] [Indexed: 12/11/2022] Open
Abstract
Background: Detecting among patients with aortic stenosis (AS) those who are likely to rapidly progress, yet potentially benefiting from prophylactic aortic valve replacement, is needed for improved patient care. The objective of this study was to evaluate the role of imaging biomarkers in predicting the progression to clinical symptoms and death in patients with AS. Methods: We searched the Pubmed and the International Clinical Trials Registry Platform databases for studies including patients with AS, and investigating imaging techniques, published in any language until Jan 1, 2018. Eligible sets of data include effect of imaging biomarkers relative to: (1) Overall mortality, (2) Cardiac mortality, and (3) Overall events (Symptom onset and Major Adverse Cardiovascular Events). Meta-analysis was used to examine associations between the imaging biomarkers and outcomes of AS using Random Effect models. Results: Eight studies and 1,639 patients were included after systematic review. Four studies investigated aortic valve calcification (AVC) whereas the remaining investigated biomarkers provided by cardiac magnetic resonance (CMR). Four articles investigated the presence of midwall fibrosis on late-gadolinium enhancement imaging, three reported its extent (LGE%) and two, the myocardial extracellular volume (ECV). By decreasing strength of association, there were significant associations between cardiac mortality and LGE% [Relative Risk (RR) = 1.05, 95% Confidence Interval (CI) 1.01-1.10]; overall mortality and AVC (RR = 1.19, 95%CI: 1.05-1.36); overall events and ECV (RR = 1.68, 95%CI: 1.17-2.41); cardiac mortality and midwall fibrosis (RR = 2.88, 95%CI: 1.12-7.39). Conclusion: AVC and myocardial fibrosis imaging biomarkers predict the outcomes in AS, and help understanding AS pathophysiology and setting therapeutic targets.
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Affiliation(s)
- Alain Nchimi
- GIGA Cardiovascular Sciences, Department of Cardiology, Heart Valve Clinic, CHU Sart Tilman, University of Liège Hospital, Liège, Belgium
- Department of Medical Imaging, Centre Hospitalier de Luxembourg, Liège, Luxembourg
| | - John E. Dibato
- GIGA Cardiovascular Sciences, Department of Cardiology, Heart Valve Clinic, CHU Sart Tilman, University of Liège Hospital, Liège, Belgium
| | - Laurent Davin
- GIGA Cardiovascular Sciences, Department of Cardiology, Heart Valve Clinic, CHU Sart Tilman, University of Liège Hospital, Liège, Belgium
| | | | - Cécile Oury
- GIGA Cardiovascular Sciences, Department of Cardiology, Heart Valve Clinic, CHU Sart Tilman, University of Liège Hospital, Liège, Belgium
| | - Patrizio Lancellotti
- GIGA Cardiovascular Sciences, Department of Cardiology, Heart Valve Clinic, CHU Sart Tilman, University of Liège Hospital, Liège, Belgium
- Gruppo Villa Maria Care and Research, Anthea Hospital, Bari, Italy
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18
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Hohendanner F, Messroghli D, Bode D, Blaschke F, Parwani A, Boldt L, Heinzel FR. Atrial remodelling in heart failure: recent developments and relevance for heart failure with preserved ejection fraction. ESC Heart Fail 2018; 5:211-221. [PMID: 29457877 PMCID: PMC5880666 DOI: 10.1002/ehf2.12260] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2017] [Accepted: 12/11/2017] [Indexed: 12/11/2022] Open
Affiliation(s)
- Felix Hohendanner
- Department of CardiologyCharité University MedicineCampus Virchow‐Klinikum, Augustenburger Platz 113353BerlinGermany
- German Center for Cardiovascular Research (DZHK), Partner SiteBerlinGermany
| | - Daniel Messroghli
- Department of CardiologyCharité University MedicineCampus Virchow‐Klinikum, Augustenburger Platz 113353BerlinGermany
- German Center for Cardiovascular Research (DZHK), Partner SiteBerlinGermany
- Department of Internal Medicine—CardiologyDeutsches Herzzentrum BerlinBerlinGermany
| | - David Bode
- Department of CardiologyCharité University MedicineCampus Virchow‐Klinikum, Augustenburger Platz 113353BerlinGermany
- German Center for Cardiovascular Research (DZHK), Partner SiteBerlinGermany
| | - Florian Blaschke
- Department of CardiologyCharité University MedicineCampus Virchow‐Klinikum, Augustenburger Platz 113353BerlinGermany
- German Center for Cardiovascular Research (DZHK), Partner SiteBerlinGermany
| | - Abdul Parwani
- Department of CardiologyCharité University MedicineCampus Virchow‐Klinikum, Augustenburger Platz 113353BerlinGermany
- German Center for Cardiovascular Research (DZHK), Partner SiteBerlinGermany
| | - Leif‐Hendrik Boldt
- Department of CardiologyCharité University MedicineCampus Virchow‐Klinikum, Augustenburger Platz 113353BerlinGermany
- German Center for Cardiovascular Research (DZHK), Partner SiteBerlinGermany
| | - Frank R. Heinzel
- Department of CardiologyCharité University MedicineCampus Virchow‐Klinikum, Augustenburger Platz 113353BerlinGermany
- German Center for Cardiovascular Research (DZHK), Partner SiteBerlinGermany
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