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Int J Cardiovasc Imaging. 2017 Nov;33(11):1797-1807. doi: 10.1007/s10554-017-1187-y. Epub 2017 Jun 14.

A systematic comparison of cardiovascular magnetic resonance and high resolution histological fibrosis quantification in a chronic porcine infarct model.

Author information

1
Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Room E03.511, P.O. Box 85500, 3508 GA, Utrecht, The Netherlands.
2
Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Room E03.511, P.O. Box 85500, 3508 GA, Utrecht, The Netherlands. r.vanes-2@umcutrecht.nl.
3
Netherlands Heart Institute, Utrecht, The Netherlands.
4
Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands.
5
Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands.
6
Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, Utrecht, The Netherlands.
7
Faculty of Population Health Sciences, Institute of Cardiovascular Science, University College London, London, UK.

Abstract

The noninvasive reference standard for myocardial fibrosis detection on cardiovascular magnetic resonance imaging (CMR) is late gadolinium enhancement (LGE). Currently there is no consensus on the preferred method for LGE quantification. Moreover myocardial wall thickening (WT) and strain are measures of regional deformation and function. The aim of this research was to systematically compare in vivo CMR parameters, such as LGE, WT and strain, with histological fibrosis quantification. Eight weeks after 90 min ischemia/reperfusion of the LAD artery, 16 pigs underwent in vivo Cine and LGE CMR. Histological sections from transverse heart slices were digitally analysed for fibrosis quantification. Mean fibrosis percentage of analysed sections was related to the different CMR techniques (using segmentation or feature tracking software) for each slice using a linear mixed model analysis. The full width at half maximum (FWHM) technique for quantification of LGE yielded the highest R2 of 60%. Cine derived myocardial WT explained 16-36% of the histological myocardial fibrosis. The peak circumferential and radial strain measured by feature tracking could explain 15 and 10% of the variance of myocardial fibrosis, respectively. The used method to systematically compare CMR image data with digital histological images is novel and feasible. Myocardial WT and strain were only modestly related with the amount of fibrosis. The fully automatic FWHM analysis technique is the preferred method to detect myocardial fibrosis.

KEYWORDS:

Cardiovascular magnetic resonance; Fibrosis; Late gadolinium enhancement; Mixed model; Myocardial infarction; Strain

PMID:
28616762
PMCID:
PMC5682871
DOI:
10.1007/s10554-017-1187-y
[Indexed for MEDLINE]
Free PMC Article

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