Interstudy Reproducibility of Quantitative Perfusion Cardiovascular Magnetic Resonance.

Autor: Andrew G. Elkington, Gatehouse, Peter D., Ablitt, Nicholas A., Guang-Zhong Yang, Firmin, David N., Pennell, Dudley J.
Předmět:
Zdroj: Journal of Cardiovascular Magnetic Resonance (Taylor & Francis Ltd); Dec2005, Vol. 7 Issue 5, p815-822, 8p, 1 Black and White Photograph, 3 Charts, 4 Graphs
Abstrakt: Purpose. To determine the interstudy reproducibility of quantitative first-pass perfusion cardiovascular magnetic resonance with comparison of 2 previously described analysis techniques. There is no published data on the interstudy reproducibility of perfusion cardiovascular magnetic resonance which can be used to determine the significance of longitudinal changes in myocardial perfusion after pharmacologic or therapeutic interventions with defined sample sizes. Methods. Sixteen subjects (7 normal volunteers, 9 patients with coronary artery disease) had rest and adenosine stress perfusion cardiovascular magnetic resonance studies on two separate visits. A short axis slice was studied on each visit using a fast low-angle shot sequence. The global and regional myocardial perfusion reserve indices were calculated using 2 methods: model based constrained deconvolution with the Fermi function, and normalized upslopes. Reproducibility was defined as the standard deviation of the measurement differences, divided by the mean (coefficient of variation). Results. The reproducibility of global myocardial perfusion reserve indices was 21% in normal volunteers, which was similar to that in patients with coronary artery disease (CAD) (23%, p = .88). The reproducibility of regional myocardial perfusion reserve indices was 28% (p = .45 vs. global analysis). The reproducibility of global MPRi was superior with Fermi deconvolution compared with normalized upslopes (21% vs. 41%, p = .02). Conclusion. At this stage of clinical development, the reproducibility of quantitative perfusion cardiovascular magnetic resonance is good, and superior using Fermi deconvolution in preference to upslope analysis. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index