| Literature DB >> 27796815 |
Dexiao Huang1, Takashi Muramatsu2, Yingguang Li3, Wenjie Yang4, Yasuomi Nagahara2, Miao Chu5, Pieter Kitslaar3, Masayoshi Sarai2, Yukio Ozaki2, Yiannis S Chatzizisis6, Fuhua Yan4, Johan H C Reiber3, Renhua Wu7, Jun Pu8, Shengxian Tu5.
Abstract
Characterization of endothelial shear stress (ESS) may allow for prediction of the progression of atherosclerosis. The aim of this investigation was to develop a non-invasive approach for in vivo assessment of ESS by coronary computed tomography angiography (CTA) and to compare it with ESS derived from invasive coronary angiography (ICA). A total of 41 patients with mild or intermediate coronary stenoses who underwent both CTA and ICA were included in the analysis. Two geometrical models of the interrogated vessels were reconstructed separately from CTA and ICA images. Subsequently, computational fluid dynamics were applied to calculate the ESS, from which ESSCTA and ESSICA were derived, respectively. Comparisons between ESSCTA and ESSICA were performed on 163 segments of 57 vessels in the CTA and ICA models. ESSCTA and ESSICA were similar: mean ESS: 4.97 (4.37-5.57) Pascal versus 4.86 (4.27-5.44) Pascal, p = 0.58; minimal ESS: 0.86 (0.67-1.05) Pascal versus 0.79 (0.63-0.95) Pascal, p = 0.37; and maximal ESS: 14.50 (12.62-16.38) Pascal versus 13.76 (11.44-16.08) Pascal, p = 0.44. Good correlations between the ESSCTA and the ESSICA were observed for the mean (r = 0.75, p < 0.001), minimal (r = 0.61, p < 0.001), and maximal (r = 0.62, p < 0.001) ESS values. In conclusion, geometrical reconstruction by CTA yields similar results to ICA in terms of segment-based ESS calculation in patients with low and intermediate stenoses. Thus, it has the potential of allowing combined local hemodynamic and plaque morphologic information for risk stratification in patients with coronary artery disease.Entities:
Keywords: Computational fluid dynamics; Coronary computed tomography angiography; Endothelial shear stress; Invasive coronary angiography
Mesh:
Year: 2016 PMID: 27796815 DOI: 10.1007/s10554-016-1003-0
Source DB: PubMed Journal: Int J Cardiovasc Imaging ISSN: 1569-5794 Impact factor: 2.357