Literature DB >> 23833042

Quantification of fibrosis in infarcted swine hearts by ex vivo late gadolinium-enhancement and diffusion-weighted MRI methods.

Mihaela Pop1, Nilesh R Ghugre, Venkat Ramanan, Lily Morikawa, Greg Stanisz, Alexander J Dick, Graham A Wright.   

Abstract

Many have speculated that MRI signal characteristics can be used to identify regions of heterogeneous infarct associated with an arrhythmogenic substrate; however, direct evidence of this relationship is limited. The aim of this study was to demonstrate the remodelling characteristics of fibrosis by means of histology and high-resolution MR imaging. For this purpose, we performed whole-mount histology in heart samples (n = 9) collected from five swine at six weeks post-infarction and compared the extent of fibrosis in the infarcted areas delineated in these histological images with that obtained ex vivo by MRI using late gadolinium-enhancement (LGE) and diffusion-weighted imaging (DWI) methods. All MR images were obtained at a submillimetre resolution (i.e., voxel size of 0.6×0.6×1.2 mm(3)). Specifically, in the histology images, we differentiated moderate fibrosis (consisting of a mixture of viable and non-viable myocytes, known as border zone, BZ) from severe fibrosis (i.e., the dense scar). Correspondingly, tissue heterogeneities in the MR images were categorized by a Gaussian mixture model into healthy, BZ and scar. Our results showed that (a) both MRI methods were capable of qualitatively distinguishing sharp edges between dense scar and healthy tissue from regions of heterogeneous BZ; (b) the BZ and dense scar areas had intermediate-to-high increased values of signal intensity in the LGE images and of apparent diffusion coefficient in the DWI, respectively. In addition, as demonstrated by the Picrosirius Red and immunohistochemistry stains, the viable bundles in the BZ were clearly separated by thin collagen strands and had reduced expression of Cx43, whereas the core scar was composed of dense fibrosis. A quantitative analysis demonstrated that the comparison between BZ/scar extent in LGE and DWI to the corresponding areas identified in histology yielded very good correlations (i.e., for the scar identified by LGE, R(2) was 0.96 compared to R(2) = 0.93 for the scar identified in ADC maps, whereas the BZ had R(2) = 0.95 for the correlation between LGE and histology compared to R(2) = 0.91 obtained for ADC). This novel study represents an intermediate step in translating such research to the in vivo stages, as well as in establishing the best and most accurate MR method to help identify arrhythmia substrate in patients with structural heart disease.

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Year:  2013        PMID: 23833042     DOI: 10.1088/0031-9155/58/15/5009

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  29 in total

1.  Sympathetic modulation of electrical activation in normal and infarcted myocardium: implications for arrhythmogenesis.

Authors:  Olujimi A Ajijola; Robert L Lux; Anadjeet Khahera; OhJin Kwon; Eric Aliotta; Daniel B Ennis; Michael C Fishbein; Jeffrey L Ardell; Kalyanam Shivkumar
Journal:  Am J Physiol Heart Circ Physiol       Date:  2017-01-13       Impact factor: 4.733

Review 2.  Sudden Cardiac Death Substrate Imaged by Magnetic Resonance Imaging: From Investigational Tool to Clinical Applications.

Authors:  Katherine C Wu
Journal:  Circ Cardiovasc Imaging       Date:  2017-07       Impact factor: 7.792

3.  Non-contrast myocardial infarct scar assessment using a hybrid native T1 and magnetization transfer imaging sequence at 1.5T.

Authors:  Chong Duan; Yanjie Zhu; Jihye Jang; Jennifer Rodriguez; Ulf Neisius; Ahmed S Fahmy; Reza Nezafat
Journal:  Magn Reson Med       Date:  2018-12-18       Impact factor: 4.668

4.  Cardiac Electrophysiology Under MRI Guidance: an Emerging Technology.

Authors:  Henry Chubb; Steven E Williams; John Whitaker; James L Harrison; Reza Razavi; Mark O'Neill
Journal:  Arrhythm Electrophysiol Rev       Date:  2017-06

Review 5.  Real-time MRI guidance of cardiac interventions.

Authors:  Adrienne E Campbell-Washburn; Mohammad A Tavallaei; Mihaela Pop; Elena K Grant; Henry Chubb; Kawal Rhode; Graham A Wright
Journal:  J Magn Reson Imaging       Date:  2017-05-11       Impact factor: 4.813

6.  In vivo diffusion-tensor MRI of the human heart on a 3 tesla clinical scanner: An optimized second order (M2) motion compensated diffusion-preparation approach.

Authors:  Christopher Nguyen; Zhaoyang Fan; Yibin Xie; Jianing Pang; Peter Speier; Xiaoming Bi; Jon Kobashigawa; Debiao Li
Journal:  Magn Reson Med       Date:  2016-08-23       Impact factor: 4.668

7.  Quantitative diffusion-weighted magnetic resonance imaging in the assessment of myocardial fibrosis in hypertrophic cardiomyopathy compared with T1 mapping.

Authors:  Lian-Ming Wu; Bing-Hua Chen; Qiu-Ying Yao; Yang-Rongzheng Ou; Rui Wu; Meng Jiang; Jiani Hu; Dong-Aolei An; Jian-Rong Xu
Journal:  Int J Cardiovasc Imaging       Date:  2016-05-19       Impact factor: 2.357

8.  Upregulation of transforming growth factor-β signaling in a rat model of rotator cuff tears.

Authors:  Xuhui Liu; Sunil K Joshi; Bharat Ravishankar; Dominique Laron; Hubert T Kim; Brian T Feeley
Journal:  J Shoulder Elbow Surg       Date:  2014-05-27       Impact factor: 3.019

9.  Muscle atrophy and fatty infiltration after an acute rotator cuff repair in a sheep model.

Authors:  Tammy Luan; Xuhui Liu; Jeremiah T Easley; Bharat Ravishankar; Christian Puttlitz; Brian T Feeley
Journal:  Muscles Ligaments Tendons J       Date:  2015-07-03

10.  Characterization of diffuse fibrosis in the failing human heart via diffusion tensor imaging and quantitative histological validation.

Authors:  Osama M Abdullah; Stavros G Drakos; Nikolaos A Diakos; Omar Wever-Pinzon; Abdallah G Kfoury; Josef Stehlik; Craig H Selzman; Bruce B Reid; Kim Brunisholz; Divya Ratan Verma; Craig Myrick; Frank B Sachse; Dean Y Li; Edward W Hsu
Journal:  NMR Biomed       Date:  2014-09-09       Impact factor: 4.044

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