Noninvasive hemodynamic assessment, treatment outcome prediction and follow-up of aortic coarctation from MR imaging.

Coarctation of the aorta (CoA) is a congenital heart disease characterized by an abnormal narrowing of the proximal descending aorta. Severity of this pathology is quantified by the blood pressure drop (△P) across the stenotic coarctation lesion. In order to evaluate the physiological significance of the preoperative coarctation and to assess the postoperative results, the hemodynamic analysis is routinely performed by measuring the △P across the coarctation site via invasive cardiac catheterization. The focus of this work is to present an alternative, noninvasive measurement of blood pressure drop △P through the introduction of a fast, image-based workflow for personalized computational modeling of the CoA hemodynamics. The authors propose an end-to-end system comprised of shape and computational models, their personalization setup using MR imaging, and a fast, noninvasive method based on computational fluid dynamics (CFD) to estimate the pre- and postoperative hemodynamics for coarctation patients. A virtual treatment method is investigated to assess the predictive power of our approach. Automatic thoracic aorta segmentation was applied on a population of 212 3D MR volumes, with mean symmetric point-to-mesh error of 3.00 ± 1.58 mm and average computation time of 8 s. Through quantitative evaluation of 6 CoA patients, good agreement between computed blood pressure drop and catheter measurements is shown: average differences are 2.38 ± 0.82 mm Hg (pre-), 1.10 ± 0.63 mm Hg (postoperative), and 4.99 ± 3.00 mm Hg (virtual stenting), respectively. The complete workflow is realized in a fast, mostly-automated system that is integrable in the clinical setting. To the best of our knowledge, this is the first time that three different settings (preoperative--severity assessment, poststenting--follow-up, and virtual stenting--treatment outcome prediction) of CoA are investigated on multiple subjects. We believe that in future-given wider clinical validation-our noninvasive in-silico method could replace invasive pressure catheterization for CoA.