Patient-specific 3D computational modeling of the pediatric pulmonary vasculature can predict hemodynamic changes following septal defect closure and reactivity testing, potentially aiding surgical planning.
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Supports computational modeling feasibility in pediatric pulmonary vasculature; leaves open human validation before surgical planning use.
Clinical imaging methods are highly effective in the diagnosis of vascular pathologies, but they do not currently provide enough detail to shed light on the cause or progression of such diseases, and would be hard pressed to foresee the outcome of surgical interventions. Greater detail of and prediction capabilities for vascular hemodynamics and arterial mechanics are obtained here through the coupling of clinical imaging methods with computational techniques. Three-dimensional, patient-specific geometric reconstructions of the pediatric proximal pulmonary vasculature were obtained from x-ray angiogram images and meshed for use with commercial computational software. Two such models from hypertensive patients, one with multiple septal defects, the other who underwent vascular reactivity testing, were each completed with two sets of suitable fluid and structural initial and boundary conditions and used to obtain detailed transient simulations of artery wall motion and hemodynamics in both clinically measured and predicted configurations. The simulation of septal defect closure, in which input flow and proximal vascular stiffness were decreased, exhibited substantial decreases in proximal velocity, wall shear stress (WSS), and pressure in the post-op state. The simulation of vascular reactivity, in which distal vascular resistance and proximal vascular stiffness were decreased, displayed negligible changes in velocity and WSS but a significant drop in proximal pressure in the reactive state. This new patient-specific technique provides much greater detail regarding the function of the pulmonary circuit than can be obtained with current medical imaging methods alone, and holds promise for enabling surgical planning.
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Hunter et al. (2006) studied this question.
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