Extracellular volume quantification using synthetic haematocrit assessed from native and post-contrast longitudinal relaxation T1 times of a blood pool
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Rok publikování | 2021 |
Druh | Článek v odborném periodiku |
Časopis / Zdroj | BMC Cardiovascular Disorders |
Fakulta / Pracoviště MU | |
Citace | |
www | https://bmccardiovascdisord.biomedcentral.com/articles/10.1186/s12872-021-02179-z |
Doi | http://dx.doi.org/10.1186/s12872-021-02179-z |
Klíčová slova | Extracellular volume; ECV; Synthetic haematocrit; Cardiovascular magnetic resonance; CMR |
Popis | Background In terms of cardiovascular magnetic resonance are haematocrit values required for calculation of extracellular volume fraction (ECV). Previously published studies have hypothesized that haematocrit could be calculated from T1 blood pool relaxation time, however only native T1 relaxation time values have been used and the resulting formulae had been both in reciprocal and linear proportion. The aim of the study was to generate a synthetic haematocrit formula from only native relaxation time values first, calculate whether linear or reciprocal model is more precise in haematocrit estimation and then determine whether adding post-contrast values further improve its precision. Methods One hundred thirty-nine subjects underwent CMR examination. Haematocrit was measured using standard laboratory methods. Afterwards T1 relaxation times before and after the application of a contrast agent were measured and a statistical relationship between these values was calculated. Results Different linear and reciprocal models were created to estimate the value of synthetic haematocrit and ECV. The highest coefficient of determination was observed in the combined reciprocal model “-?0.047?+?(779/ blood native)?-?(11.36/ blood post-contrast)”. Conclusions This study provides more evidence that assessing synthetic haematocrit and synthetic ECV is feasible and statistically most accurate model to use is reciprocal. Adding post-contrast values to the calculation was proved to improve the precision of the formula statistically significantly. |
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