Browsing by Author "Zhong, Xiaodong"

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    Comparison of SNR efficiencies and strain for cine DENSE using conventional EPI, flyback EPI and spiral k-space trajectories
    (BioMed Central Ltd, 2011) Zhong, Xiaodong; Spottiswoode, Bruce; Meyer, Craig; Epstein, Frederick
    The original implementation of 2D cine DENSE (displacement encoding with stimulated echoes) employed a conventional EPI k-space trajectory for rapid data sampling. Follow-up studies used flyback EPI to reduce image artifacts. More recently a spiral k-space trajectory was utilized for improved SNR.
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    Comprehensive Cardiovascular magnetic resonance of myocardial mechanics in mice using three-dimensional cine DENSE
    (BioMed Central Ltd, 2011) Zhong, Xiaodong; Gibberman, Lauren; Spottiswoode, Bruce; Gilliam, Andrew; Meyer, Craig; French, Brent; Epstein, Frederick
    BACKGROUND: Quantitative noninvasive imaging of myocardial mechanics in mice enables studies of the roles of individual genes in cardiac function. We sought to develop comprehensive three-dimensional methods for imaging myocardial mechanics in mice. METHODS: A 3D cine DENSE pulse sequence was implemented on a 7T small-bore scanner. The sequence used three-point phase cycling for artifact suppression and a stack-of-spirals k-space trajectory for efficient data acquisition. A semi-automatic 2D method was adapted for 3D image segmentation, and automated 3D methods to calculate strain, twist, and torsion were employed. A scan protocol that covered the majority of the left ventricle in a scan time of less than 25 minutes was developed, and seven healthy C57Bl/6 mice were studied. RESULTS: Using these methods, multiphase normal and shear strains were measured, as were myocardial twist and torsion. Peak end-systolic values for the normal strains at the mid-ventricular level were 0.29 +/- 0.17, -0.13 +/- 0.03, and -0.18 +/- 0.14 for Err, Ecc, and Ell, respectively. Peak end-systolic values for the shear strains were 0.00 +/- 0.08, 0.04 +/- 0.12, and 0.03 +/- 0.07 for Erc, Erl, and Ecl, respectively. The peak end-systolic normalized torsion was 5.6 +/- 0.9degrees. CONCLUSIONS: Using a 3D cine DENSE sequence tailored for cardiac imaging in mice at 7 T, a comprehensive assessment of 3D myocardial mechanics can be achieved with a scan time of less than 25 minutes and an image analysis time of approximately 1 hour.
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    Mapping right ventricular myocardial mechanics using 3D cine DENSE cardiovascular magnetic resonance
    (BioMed Central Ltd, 2012) Auger, Daniel; Zhong, Xiaodong; Epstein, Frederick; Spottiswoode, Bruce
    BACKGROUND: The mechanics of the right ventricle (RV) are not well understood as studies of the RV have been limited. This is, in part, due to the RV's thin wall, asymmetric geometry and irregular motion. However, the RV plays an important role in cardiovascular function. This study aims to describe the complex mechanics of the healthy RV using three dimensional (3D) cine displacement encoding with stimulated echoes (DENSE) cardiovascular magnetic resonance (CMR). METHODS: Whole heart 3D cine DENSE data were acquired from five healthy volunteers. Tailored post-processing algorithms for RV mid-wall tissue tracking and strain estimation are presented. A method for sub-dividing the RV into four regions according to anatomical land marks is proposed, and the temporal evolution of strain was assessed in these regions. RESULTS: The 3D cine DENSE tissue tracking methods successfully capture the motion and deformation of the RV at a high spatial resolution in all volunteers. The regional Lagrangian peak surface strain and time to peak values correspond with previous studies using myocardial tagging, DENSE and strain encoded CMR. The inflow region consistently displays lower peak strains than the apical and outflow regions, and the time to peak strains suggest RV mechanical activation in the following order: inflow, outflow, mid, then apex. CONCLUSIONS: Model-free techniques have been developed to study the myocardial mechanics of the RV at a high spatial resolution using 3D cine DENSE CMR. The consistency of the regional RV strain patterns across healthy subjects is encouraging and the techniques may have clinical utility in assessing disrupted RV mechanics in the diseased heart.
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    Quantifying right ventricular motion and strain using 3D cine DENSE MRI
    (BioMed Central Ltd, 2011) Auger, Daniel; Zhong, Xiaodong; Meintjes, Ernesta M; Epstein, Frederick H; Spottiswoode, Bruce S
    Background: The RV is difficult to image because of its thin wall, asymmetric geometry and complex motion. DENSE is a quantitative MRI technique for measuring myocardial displacement and strain at high spatial and temporal resolutions [1,2]. DENSE encodes tissue displacement directly into the image phase, allowing for the direct extraction of motion data at a pixel resolution. A free-breathing navigator-gated spiral 3D cine DENSE sequence was recently developed [3], providing an MRI technique which is well suited to quantifying RV mechanics. Methods: Whole heart 3D cine DENSE data were acquired from two normal volunteers, after informed consent was obtained and in accordance with protocols approved by the University of Virginia institutional review board. The endocardial and epicardial contours were manually delineated to identify the myocardium from surrounding anatomical structures. A 3D spatiotemporal phase unwrapping algorithm was used to remove phase aliasing [4], and 3D Lagrangian displacement fields were derived for all cardiac phases. Midline contours were calculated from the epicardial and endocardial contours, and tissue tracking seed points were defined at pixel spaced intervals. A 3D tracking algorithm was implemented as a direct extension of the 2D tracking algorithm presented in [4], producing midline motion trajectories from which strain was calculated. Tangential 1D strain was calculated in the longitudinal and circumferential cardiac directions. Strain time curves are computed representing the free wall of the RV. Results: Figure 1 illustrates the RV free wall mean tangential 1D strain time curves for approximately 3/4 of the cardiac cycle over the apical-mid section of the heart for one volunteer. Results show measurements ranging between -0.1 and -0.25, and further illustrate a greater displacement in the longitudinal direction. Results compare favorably with studies using myocardial tagging and DENSE[5,6].
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    Semi-automated left ventricular segmentation based on a guide point model approach for 3D cine DENSE cardiovascular magnetic resonance
    (2014-01-14) Auger, Daniel A; Zhong, Xiaodong; Epstein, Frederick H; Meintjes, Ernesta M; Spottiswoode, Bruce S
    Abstract Background The most time consuming and limiting step in three dimensional (3D) cine displacement encoding with stimulated echoes (DENSE) MR image analysis is the demarcation of the left ventricle (LV) from its surrounding anatomical structures. The aim of this study is to implement a semi-automated segmentation algorithm for 3D cine DENSE CMR using a guide point model approach. Methods A 3D mathematical model is fitted to guide points which were interactively placed along the LV borders at a single time frame. An algorithm is presented to robustly propagate LV epicardial and endocardial surfaces of the model using the displacement information encoded in the phase images of DENSE data. The accuracy, precision and efficiency of the algorithm are tested. Results The model-defined contours show good accuracy when compared to the corresponding manually defined contours as similarity coefficients Dice and Jaccard consist of values above 0.7, while false positive and false negative measures show low percentage values. This is based on a measure of segmentation error on intra- and inter-observer spatial overlap variability. The segmentation algorithm offers a 10-fold reduction in the time required to identify LV epicardial and endocardial borders for a single 3D DENSE data set. Conclusion A semi-automated segmentation method has been developed for 3D cine DENSE CMR. The algorithm allows for contouring of the first cardiac frame where blood-myocardium contrast is almost nonexistent and reduces the time required to segment a 3D DENSE data set significantly.