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Guan X, Chen Y, Yang HJ, Zhang X, Ren D, Sykes J, Butler J, Han H, Zeng M, Prato FS, Dharmakumar R. Assessment of intramyocardial hemorrhage with dark-blood T2*-weighted cardiovascular magnetic resonance. J Cardiovasc Magn Reson 2021; 23:88. [PMID: 34261494 PMCID: PMC8281666 DOI: 10.1186/s12968-021-00787-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 06/08/2021] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND Intramyocardial hemorrhage (IMH) within myocardial infarction (MI) is associated with major adverse cardiovascular events. Bright-blood T2*-based cardiovascular magnetic resonance (CMR) has emerged as the reference standard for non-invasive IMH detection. Despite this, the dark-blood T2*-based CMR is becoming interchangeably used with bright-blood T2*-weighted CMR in both clinical and preclinical settings for IMH detection. To date however, the relative merits of dark-blood T2*-weighted with respect to bright-blood T2*-weighted CMR for IMH characterization has not been studied. We investigated the diagnostic capacity of dark-blood T2*-weighted CMR against bright-blood T2*-weighted CMR for IMH characterization in clinical and preclinical settings. MATERIALS AND METHODS Hemorrhagic MI patients (n = 20) and canines (n = 11) were imaged in the acute and chronic phases at 1.5 and 3 T with dark- and bright-blood T2*-weighted CMR. Imaging characteristics (Relative signal-to-noise (SNR), Relative contrast-to-noise (CNR), IMH Extent) and diagnostic performance (sensitivity, specificity, accuracy, area-under-the-curve, and inter-observer variability) of dark-blood T2*-weighted CMR for IMH characterization were assessed relative to bright-blood T2*-weighted CMR. RESULTS At both clinical and preclinical settings, compared to bright-blood T2*-weighted CMR, dark-blood T2*-weighted images had significantly lower SNR, CNR and reduced IMH extent (all p < 0.05). Dark-blood T2*-weighted CMR also demonstrated weaker sensitivity, specificity, accuracy, and inter-observer variability compared to bright-blood T2*-weighted CMR (all p < 0.05). These observations were consistent across infarct age and imaging field strengths. CONCLUSION While IMH can be visible on dark-blood T2*-weighted CMR, the overall conspicuity of IMH is significantly reduced compared to that observed in bright-blood T2*-weighted images, across infarct age in clinical and preclinical settings at 1.5 and 3 T. Hence, bright-blood T2*-weighted CMR would be preferable for clinical use since dark-blood T2*-weighted CMR carries the potential to misclassify hemorrhagic MIs as non-hemorrhagic MIs.
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Affiliation(s)
- Xingmin Guan
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, PACT Bldg - Suite 400, 8700 Beverly Blvd, Los Angeles, CA, USA
- University of California, Los Angeles, CA, USA
| | - Yinyin Chen
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, PACT Bldg - Suite 400, 8700 Beverly Blvd, Los Angeles, CA, USA
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Hsin-Jung Yang
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, PACT Bldg - Suite 400, 8700 Beverly Blvd, Los Angeles, CA, USA
| | - Xinheng Zhang
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, PACT Bldg - Suite 400, 8700 Beverly Blvd, Los Angeles, CA, USA
- University of California, Los Angeles, CA, USA
| | - Daoyuan Ren
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jane Sykes
- Lawson Health Research Institute, University of Western Ontario, London, ON, Canada
| | - John Butler
- Lawson Health Research Institute, University of Western Ontario, London, ON, Canada
| | - Hui Han
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, PACT Bldg - Suite 400, 8700 Beverly Blvd, Los Angeles, CA, USA
| | - Mengsu Zeng
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Frank S Prato
- Lawson Health Research Institute, University of Western Ontario, London, ON, Canada
| | - Rohan Dharmakumar
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, PACT Bldg - Suite 400, 8700 Beverly Blvd, Los Angeles, CA, USA.
- University of California, Los Angeles, CA, USA.
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Henningsson M, Malik S, Botnar R, Castellanos D, Hussain T, Leiner T. Black-Blood Contrast in Cardiovascular MRI. J Magn Reson Imaging 2020; 55:61-80. [PMID: 33078512 PMCID: PMC9292502 DOI: 10.1002/jmri.27399] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 09/22/2020] [Accepted: 09/23/2020] [Indexed: 12/14/2022] Open
Abstract
MRI is a versatile technique that offers many different options for tissue contrast, including suppressing the blood signal, so‐called black‐blood contrast. This contrast mechanism is extremely useful to visualize the vessel wall with high conspicuity or for characterization of tissue adjacent to the blood pool. In this review we cover the physics of black‐blood contrast and different techniques to achieve blood suppression, from methods intrinsic to the imaging readout to magnetization preparation pulses that can be combined with arbitrary readouts, including flow‐dependent and flow‐independent techniques. We emphasize the technical challenges of black‐blood contrast that can depend on flow and motion conditions, additional contrast weighting mechanisms (T1, T2, etc.), magnetic properties of the tissue, and spatial coverage. Finally, we describe specific implementations of black‐blood contrast for different vascular beds.
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Affiliation(s)
- Markus Henningsson
- Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.,Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Shaihan Malik
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Rene Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Daniel Castellanos
- Division of Pediatric Cardiology, Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Tarique Hussain
- Division of Pediatric Cardiology, Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Division of Pediatric Radiology, Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Tim Leiner
- Department of Radiology, Utrecht University Medical Center, Utrecht, The Netherlands
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Triadyaksa P, Oudkerk M, Sijens PE. Cardiac T 2 * mapping: Techniques and clinical applications. J Magn Reson Imaging 2019; 52:1340-1351. [PMID: 31837078 PMCID: PMC7687175 DOI: 10.1002/jmri.27023] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Accepted: 11/25/2019] [Indexed: 12/12/2022] Open
Abstract
Cardiac T2* mapping is a noninvasive MRI method that is used to identify myocardial iron accumulation in several iron storage diseases such as hereditary hemochromatosis, sickle cell disease, and β‐thalassemia major. The method has improved over the years in terms of MR acquisition, focus on relative artifact‐free myocardium regions, and T2* quantification. Several improvement factors involved include blood pool signal suppression, the reproducibility of T2* measurement as affected by scanner hardware, and acquisition software. Regarding the T2* quantification, improvement factors include the applied curve‐fitting method with or without truncation of the signals acquired at longer echo times and whether or not T2* measurement focuses on multiple segmental regions or the midventricular septum only. Although already widely applied in clinical practice, data processing still differs between centers, contributing to measurement outcome variations. State of the art T2* measurement involves pixelwise quantification providing better spatial iron loading information than region of interest‐based quantification. Improvements have been proposed, such as on MR acquisition for free‐breathing mapping, the generation of fast mapping, noise reduction, automatic myocardial contour delineation, and different T2* quantification methods. This review deals with the pro and cons of different methods used to quantify T2* and generate T2* maps. The purpose is to recommend a combination of MR acquisition and T2* mapping quantification techniques for reliable outcomes in measuring and follow‐up of myocardial iron overload. The clinical application of cardiac T2* mapping for iron overload's early detection, monitoring, and treatment is addressed. The prospects of T2* mapping combined with different MR acquisition methods, such as cardiac T1 mapping, are also described. Level of Evidence: 4 Technical Efficacy Stage: 5 J. Magn. Reson. Imaging 2019.
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Affiliation(s)
- Pandji Triadyaksa
- University of Groningen, Groningen, The Netherlands.,Universitas Diponegoro, Department of Physics, Faculty of Science and Mathematics, Semarang, Indonesia
| | - Matthijs Oudkerk
- University of Groningen, Groningen, The Netherlands.,Institute for Diagnostic Accuracy, Groningen, The Netherlands
| | - Paul E Sijens
- University of Groningen, Groningen, The Netherlands.,University Medical Center Groningen, Department of Radiology, Groningen, The Netherlands
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4
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Barrera CA, Otero HJ, Hartung HD, Biko DM, Serai SD. Protocol optimization for cardiac and liver iron content assessment using MRI: What sequence should I use? Clin Imaging 2019; 56:52-57. [PMID: 30889418 DOI: 10.1016/j.clinimag.2019.02.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Revised: 01/31/2019] [Accepted: 02/19/2019] [Indexed: 01/19/2023]
Abstract
OBJECTIVE To determine the optimal MRI protocol and sequences for liver and cardiac iron estimation in children. METHODS We evaluated patients ≤18 years with cardiac and liver MRIs for iron content estimation. Liver T2 was determined by a third-party company. Cardiac and Liver T2* values were measured by an observer. Liver T2* values were calculated using the available liver parenchyma in the cardiac MRI. Linear correlations and Bland-Altman plots were run between liver T2 and T2*, cardiac T2* values; and liver T2* on dedicated cardiac and liver MRIs. RESULTS 139 patients were included. Mean liver T2 and T2* values were 8.6 ± 5.4 ms and 4.5 ± 4.1 ms, respectively. A strong correlation between liver T2 and T2* values was observed (r = 0.96, p < 0.001) with a bias (+4.1 ms). Mean cardiac bright- and dark-blood T2* values were 26.5 ± 12.9 ms and 27.2 ± 11.9 ms, respectively. Cardiac T2* values showed a strong correlation (r = 0.81, p < 0.001) with a low bias (-1.0 ms). The mean liver T2* on liver and cardiac MRIs were 4.9 ± 4.7 ms and 4.6 ± 3.9 ms, respectively. A strong correlation between T2* values was observed (r = 0.96, p < 0.001) with a small bias (-0.2 ms). CONCLUSION MRI protocols for iron concentration in the liver and the heart can be simplified to avoid redundant information and reduce scan time. In most patients, a single breath-hold GRE sequence can be used to evaluate the iron concentration in both the liver and heart.
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Affiliation(s)
- Christian A Barrera
- Department of Radiology, The Children's Hospital of Philadelphia, 34th Street & Civic Center Boulevard, Philadelphia, PA 19104, USA.
| | - Hansel J Otero
- Department of Radiology, The Children's Hospital of Philadelphia, 34th Street & Civic Center Boulevard, Philadelphia, PA 19104, USA
| | - Helge D Hartung
- Department of Pediatrics, The Children's Hospital of Philadelphia, 34th Street & Civic Center Boulevard, Philadelphia, PA 19104, USA
| | - David M Biko
- Department of Radiology, The Children's Hospital of Philadelphia, 34th Street & Civic Center Boulevard, Philadelphia, PA 19104, USA
| | - Suraj D Serai
- Department of Radiology, The Children's Hospital of Philadelphia, 34th Street & Civic Center Boulevard, Philadelphia, PA 19104, USA
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Malvarosa I, Massaroni C, Liguori C, Paul J, Beomonte Zobel B, Saccomandi P, Vogl TJ, Silvestri S, Schena E. Estimation of liver iron concentration by dual energy CT images: influence of X-ray energy on sensitivity. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2015; 2014:5129-32. [PMID: 25571147 DOI: 10.1109/embc.2014.6944779] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
In hemochromatosis an abnormal accumulation of iron is present in parenchymal organs and especially in liver. Among the several techniques employed to diagnose the iron overload, magnetic resonance imaging (MRI) and Computed Tomography (CT) are the most promising non-invasive ones. MRI is largely used but shows limitation including an overestimation of iron and inability to quantify iron at very high concentrations. Therefore, some research groups are focusing on the estimation of iron concentration by CT images. Single X-ray CTs are not able to accurately perform this task in case of the presence of confounding factors (e.g., fat). A potential solution to overcome this concern is the employment of Dual-Energy CT (DECT). The aim of this work is to investigate influence of the kVp and mAs on CT number sensitivity to iron concentration. A phantom with test tubes filled with homogenized porcine liver at different iron concentrations, has been scanned with DECT at different mAs. The images have been analyzed using an ad-hoc developed algorithm which allows minimizing the influence of air bubbles present in the homogenized. Data show that the sensitivity is strongly influenced by kVp (its value almost halves from 80 kVp to 140 kVp; e.g. 0.41 g·μmol(-1) and 0.19 g·μmol(-1) at 80 kVp/120 mAs and 140 kVp/60 mAs respectively), on the other hand the influence of mAs value is negligible.
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