Volume 18 Supplement 1
Visualization and Quantification of Regional Ventricular Wall and Blood Velocities by 3T 4D PC-MRI
© Samnøy et al. 2016
Published: 27 January 2016
Wall motion together with the development of intra-cavity pressure and inside shear stress cause synchronous myocardial contraction and relaxation, as well as blood flow. These variables are related to cardiovascular function and disease. Assessing regional wall velocities and blood flow may therefore provide quantitative information regarding abnormalities in wall contractility and alterations in blood flow patterns. By using a retrospective 4D PC-MRI technique, this study aimed to develop a tool to simultaneously visualize and quantify both regional ventricular wall velocity and the intra-cavity blood flow pattern.
Consecutive 2D short-axis slices with three orthogonal velocity components covering the whole heart throughout the cardiac cycle were collected using a retrospective 4D PC-MRI, ECG gated CINE imaging technique during breath-hold. The scanner for the acquisitions was a 3.0T GE Signa Excite scanner (Milwaukee, WI, USA), and sequence parameters were TR = 11 ms, TE = 4 ms, Flip Angle = 20°, Matrix = 256 × 256, Slice Thickness = 8 mm, Slice Resolution = 1.25 mm per pixel, VENC = 150 cm/s, Field of View = 320 × 320 mm.
Ventricular walls were extracted from the temporal images in all slices and pixel positions of the time dependent walls formed the basis for a surface model of the ventricles. The wall-surface was colored according to the resultant velocities. The intra-cavity blood flow was visualized using 3D vectors in each pixel position. Both the wall and blood flow pattern were studied simultaneously in a fully rotatable and scalable 3D frame.
This method improves the ability to simultaneously study global and regional velocity patterns of the ventricular walls and the corresponding blood velocity pattern. This technique may reveal hypokinetic and akinetic contractions, as well as asynchronous and paradox wall movements and abnormal velocity flow patterns.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.