Vectors through a cross-sectional image (VCI): A visualization method for four-dimensional motion analysis for cardiac computed tomography

Abstract

BackgroundCardiac computed tomography (CT) has the potential for fully four-dimensional (4D for 3D plus time) motion analysis of the heart. We aimed at developing a method for assessment and presentation of the 4D motion for multi-phase, contrast-enhanced cardiac CT data sets and demonstrating its clinical applicability. MethodsFour patients with normal cardiac function, old myocardial infarction (OMI), takotsubo cardiomyopathy, and hypertrophic cardiomyopathy (HCM) underwent contrast-enhanced cardiac CT for one heartbeat using a 320-row CT scanner with no tube current modulation. CT images for 10 cardiac phases (with a 10%-increment of the R-R interval) were reconstructed with the isotropic effective resolution of (0.5 mm)3 An image-based motion-estimation (iME) algorithm, developed previously, has been used to estimate a time series of 3D cardiac motion, from the end-systole to the other nine phases. The iME uses down-sampled images with a resolution of (1.0 mm)3 deforms the end-systole images non-rigidly to match images at other phases. Once the agreement is maximized, iME outputs a 3D motion vector defined for each voxel for each phase, that smoothly changes over voxels and phases. The proposed visualization method, which is called “vectors through a cross-sectional image (VCI),” presents 3D vectors from the end-diastole to the end-systole as arrows with an end-diastole CT slice. We performed visual assessment of the VCI with calculated the mean vector lengths to evaluate regional left ventricular (LV) contraction. ResultsThe VCI images showed the magnitude and direction of systolic 3D vectors, including the through-plane motion, and successfully visualized the relations of LV wall segments and abnormal regional wall motion. Decreased regional motion and asymmetric motion due to hypokinetic infarct segment, takotsubo cardiomyopathy, and hyper trophic cardiomyopathy was clearly observed. It was easy to appreciate the relation of the abnormal regional wall motion to the affected LV wall segments. The mean vector lengths of the affected segments with pathologies were clearly smaller than the other unaffected segments (1.2–1.7 mm versus 2.5–4.7 mm). ConclusionsVCI images could capture the magnitude and direction of through-plane motion and show the relations of LV wall segments and abnormal wall motion.