Application of an adaptive control grid interpolation technique to MR data set augmentation aimed at morphological vascular reconstruction

The total cavopulmonary connection (TCPC) is a palliative surgical repair performed on children with a single ventricle (SV) physiology. Much of the power produced by the resultant single ventricle pump is consumed in the systemic circulation. Consequently the minimization of power loss in the TCPC is imperative for optimal surgical outcome. Toward this end we have developed a method of vascular morphology reconstruction based on adaptive control grid interpolation (ACGI) to function as a precursor to computational fluid dynamics (CFD) analysis aimed at quantifying power loss. Our technique combines positive aspects of optical flow-based and block-based motion estimation algorithms to accurately augment insufficiently dense Magnetic Resonance (MR) data sets with a minimal degree of computational complexity. The resulting enhanced data sets are used to reconstruct vascular geometries, and the subsequent reconstructions can then be used in conjunction with CFD simulations to offer the pressure and velocity information necessary to quantify power loss in the TCPC. Collectively these steps form a tool that transforms conventional MR data into more powerful information allowing surgical planning aimed at producing optimal TCPC configurations for successful surgical outcomes.