Key result
In a mini-pig model of myocardial infarction, phase bandwidth and standard deviation derived from 18F-FDG gated myocardial metabolic imaging showed significant positive correlation with those from gated myocardial perfusion imaging.
Why the study?
Does gated myocardial glucose metabolic imaging accurately assess left ventricular systolic dyssynchrony compared to gated myocardial perfusion imaging in a mini-pig model of myocardial infarction?
Does gated myocardial glucose metabolic imaging accurately assess left ventricular systolic dyssynchrony compared to gated myocardial perfusion imaging in a mini-pig model of myocardial infarction?
Effect estimate: rBW = 0.74, rSD = 0.84
p-value: p=<0.05
Gated myocardial glucose metabolic imaging phase analysis can accurately assess left ventricular systolic dyssynchrony after myocardial infarction, showing good consistency with perfusion imaging.
Supports metabolic-perfusion correlation for dyssynchrony in MI models; leaves open human validation.
In this study, we investigated the role of gated myocardial glucose metabolic imaging in assessing left ventricular (LV) systolic dyssynchrony after myocardial infarction (MI) and explored the influencing factors. Bama mini-pigs were divided into normal group and MI group and subjected to gated myocardial metabolic imaging (GMMI) and gated myocardial perfusion imaging (GMPI). The phase bandwidth (BW), standard deviation (SD) and the latest activation site of left ventricle were obtained using program Cedars QGS. The results showed that (1) BW and SD obtained in GMMI and GMPI showed significant correlation in pigs with MI, but not in the normal pigs, (2) BW and SD obtained in GMMI and GMPI had good consistency in both normal pigs and MI pigs, (3) GMMI and GMPI had a 66.7% identity in determining the latest activation site of left ventricle in the normal pigs and 77.8% identity in determining the latest activation site of left ventricle in pigs with MI. Multivariate stepwise regression analysis showed that total perfusion deficit and summed motion score were independent factors affecting BW and SD in GMMI. In conclusion, phase analysis of GMMI images could objectively reflect LV systolic dyssynchrony resulted from interactions of multiple factors.
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Shao et al. (2018) studied Myocardial Infarction (n=18). 18F-FDG gated myocardial metabolic imaging (GMMI) vs. 99mTc-MIBI gated myocardial perfusion imaging (GMPI) was evaluated on Correlation of phase bandwidth (BW) and standard deviation (SD) between GMMI and GMPI in MI pigs (rBW = 0.74, rSD = 0.84, p=<0.05). In a mini-pig model of myocardial infarction, phase bandwidth and standard deviation derived from 18F-FDG gated myocardial metabolic imaging showed significant positive correlation with those from gated myocardial perfusion imaging.
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