Myocardial tissue characterization by combining late gadolinium enhancement imaging and percent edema mapping: a novel T2 map-based MRI method in canine myocardial infarction

被引：4
作者：
Suranyi P. [1 ]
Elgavish G.A. [2 ]
Schoepf U.J. [1 ]
Ruzsics B. [3 ]
Kiss P. [2 ]
van Assen M. [1 ,4 ]
Jacobs B.E. [1 ]
Brott B.C. [5 ]
Elgavish A. [6 ]
Varga-Szemes A. [1 ,2 ]
机构：
[1] Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, 29425, SC
[2] Department of Biochemistry and Molecular Genetics, University of Alabama at Birmingham, MCLM 556, Birmingham, 35294-0005, AL
[3] Department of Cardiology, Royal Liverpool and Broadgreen University Hospital, Thomas Dr, Liverpool
[4] University of Groningen, University Medical Center Groningen, Center for Medical Imaging - North East Netherlands, Hanzeplein 1, Groningen
[5] Department of Medicine, Division of Cardiovascular Disease, University of Alabama at Birmingham, FOT 907, Birmingham, 35294-3407, AL
[6] Department of Medicine, Division of Clinical Immunology and Rheumatology, University of Alabama at Birmingham, MCLM 556, Birmingham, 35294-0005, AL
来源：
European Radiology Experimental | / 2卷 / 1期
基金：
美国国家卫生研究院;
关键词：
Magnetic resonance imaging; Myocardial edema; Myocardial hemorrhage; Myocardial infarction; Tissue characterization;
D O I：
10.1186/s41747-018-0037-6
中图分类号：
学科分类号：
摘要：
Background: Assessing the extent of ischemic and reperfusion-associated myocardial injuries remains challenging with current magnetic resonance imaging (MRI) techniques. Our aim was to develop a tissue characterization mapping (TCM) technique by combining late gadolinium enhancement (LGE) with our novel percent edema mapping (PEM) approach to enable the classification of tissue represented by MRI voxels as healthy, myocardial edema (ME), necrosis, myocardial hemorrhage (MH), or scar. Methods: Six dogs underwent closed-chest myocardial infarct (MI) generation. Serial MRI scans were performed post-MI on days 3, 4, 6, 14, and 56, including T2 mapping and LGE. Dogs were sacrificed on day 4 (n = 4, acute MI) or day 56 (n = 2, chronic MI). TCMs were generated based on a voxel classification algorithm taking into account signal intensity from LGE and T2-based estimation of ME. TCM-based MI and MH were validated with post mortem triphenyl tetrazolium chloride (TTC) staining. Pearson’s correlation and Bland-Altman analyses were performed. Results: The MI, ME, and MH measured by TCM were 13.4% [25th–75th percentile 1.6–28.8], 28.1% [2.1–37.5] and 4.3% [1.0–11.3], respectively. TCM measured higher MH and MI compared to TTC (p = 0.0033 and p = 0.0007, respectively). MH size was linearly correlated with MI size by both MRI (r = 0.9528, p < 0.0001) and TTC (r = 0.9625, p < 0.0001). MH quantification demonstrated good agreement between TCM and TTC (r = 0.8766, p < 0.0001, 2.4% overestimation by TCM). A similar correlation was observed for MI size (r = 0.9429, p < 0.0001, 6.1% overestimation by TCM). Conclusions: Preliminary results suggest that the TCM method is feasible for the in vivo localization and quantification of various MI-related tissue components. © 2018, The Author(s).
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