12 May 2004 3D heart motion from single-plane angiography of the coronary vasculature: a model-based approach
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Abstract
In order to complete a thorough examination of a patient heart muscle, physicians practice two common invasive procedures: the ventriculography, which allows the determination of the ejection fraction, and the coronarography, giving among other things, information on stenosis of arteries. We propose a method that allows the determination of a contraction index similar to ejection fraction, using only single-plane coronarography. Our method first reconstructs in 3D, selected points on the angiogram, using a 3D model devised from data published by Dodge ea. ['88, '92]. We then follow the point displacements through a complete heart contraction cycle. The objective function, minimizing the RMS distances between the angiogram and the model, relies on affine transformations, i.e. translation, rotation and isotropic scaling. We validate our method on simulated projections using cases from Dodge data. In order to avoid any bias, a leave-one-out strategy was used, which excludes the reference case when constructing the 3D coronary heart model. The simulated projections are created by transforming the reference case, with scaling, translation and rotation transformations, and by adding random 3D noise for each frame in the contraction cycle. Comparing the true scaling parameters to the reconstructed sequence, our method is quite robust (R2=96.6%, P<1%), even when noise error level is as high as 1 cm. Using 10 clinical cases we then proceeded to reconstruct the contraction sequence for a complete cardiac cycle starting at end-diastole. A simple heart contraction mathematical model permitted us to link the measured ejection fraction of the different cases to the maximum heart contraction amplitude (R2=57%, P<1%) determined by our method.
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Denis Sherknies, Denis Sherknies, Jean Meunier, Jean Meunier, Jean-Claude Tardif, Jean-Claude Tardif, } "3D heart motion from single-plane angiography of the coronary vasculature: a model-based approach", Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004); doi: 10.1117/12.534629; https://doi.org/10.1117/12.534629
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