19. Comparison of myocardial blood flow estimates from dynamic contrast-enhanced used in Cardiac Magnetic Resonance Imaging

• Published in: Physica medica 2018-12, Vol.56, p.72-72
• Main Authors: Carnı̀, M., Borrazzo, C., Galea, N., Vullo, F., Francone, M., Catalano, C., Carbone, I., Pacilio, M.
• Format: Article
• Language: English
• ISSN: 1120-1797; 1724-191X
• DOI: 10.1016/j.ejmp.2018.04.029

Dynamic Contrast-Enhanced Cardiovascuar Magnetic Resonance Imaging (DCE-CMRI) may quantitatively assess the Myocardial Blood Flow (MBF), recovering the tissue impulse-response function to transit of gadolinium bolus through myocardium. Several deconvolution techniques are available, using various models for the impulse-response [1]. The method choice may influence the results, producing differences that have not been deeply investigated yet. Three methods for quantifying myocardial perfusion were compared: Fermi Function Modeling, Tofts Model, and Gamma Function model, the latter traditionally used in brain perfusion. Thirty human subjects were studied at rest, and Cold Pressor Test stress, injecting a single-bolus of gadolinium of 0.1 mmol/kg. Perfusion estimate differences among methods were analysed by paired comparisons with Student’s t-test, linear regression analysis, and Bland-Altman plots, and using also the two-way ANOVA, considering the MBF values of all patients grouped according to two categories: calculation method and rest/stress conditions. Perfusion estimates obtained by various methods in both rest and stress conditions were not significantly different, and in agreement with the literature. Results obtained during the first-pass transit time (20 s) yielded p-values in the range 0.20–0.28 for the Student’s t-test, slopes from the linear regression analysis between 0.98–1.03, and R values between 0.92–1.01. With the two-way ANOVA, the results were p = 0.20 for the method effect (not significant), p