Post-mortem cardiac diffusion tensor imaging: detection of myocardial infarction and remodeling of myofiber architecture
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To investigate the accuracy of post-mortem diffusion tensor imaging (DTI) for the detection of myocardial infarction (MI) and to demonstrate the feasibility of helix angle (HA) calculation to study remodelling of myofibre architecture.
Cardiac DTI was performed in 26 deceased subjects prior to autopsy for medicolegal reasons. Fractional anisotropy (FA) and mean diffusivity (MD) were determined. Accuracy was calculated on per-segment (AHA classification), per-territory, and per-patient basis, with pathology as reference standard. HAs were calculated and compared between healthy segments and those with MI.
Autopsy demonstrated MI in 61/440 segments (13.9 %) in 12/26 deceased subjects. Healthy myocardial segments had significantly higher FA (p < 0.01) and lower MD (p < 0.001) compared to segments with MI. Multivariate logistic regression demonstrated that FA (p < 0.10) and MD (p = 0.01) with the covariate post-mortem time (p < 0.01) predicted MI with an accuracy of 0.73. Analysis of HA distribution demonstrated remodelling of myofibre architecture, with significant differences between healthy segments and segments with chronic (p < 0.001) but not with acute MI (p > 0.05).
Post-mortem cardiac DTI enablesdifferentiation between healthy and infarcted myocardial segments by means of FA and MD. HA assessment allows for the demonstration of remodelling of myofibre architecture following chronic MI.
• DTI enables post-mortem detection of myocardial infarction with good accuracy.
• A decrease in right-handed helical fibre indicates myofibre remodelling following chronic myocardial infarction.
• DTI allows for ruling out myocardial infarction by means of FA.
• Post-mortem DTI may represent a valuable screening tool in forensic investigations.
KeywordsMagnetic resonance imaging (MeSH) Diffusion tensor imaging Myocardial infarction Ventricular remodelling Autopsy
Diffusion tensor imaging
Hematoxylin and eosin
Intraclass correlation coefficients
Magnetic resonance imaging
Negative predictive value
Positive predictive value
Receiver operating characteristics
Region of interest
The scientific guarantor of this publication is Paul Stolzmann. The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article. The authors state that this work has not received any funding. One of the authors has significant statistical expertise. Institutional Review Board approval was obtained. Written informed consent was not required for this study, as informed consent was not applicable due to the post-mortem nature of the study. Methodology: prospective diagnostic or prognostic study, performed at one institution.
Conflict on interest
No conflict of interest declared.
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