Replicating Patient-Specific Severe Aortic Valve Stenosis with Functional 3D Modeling

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Abstract

3D stereolithographic printing can be used to convert high-resolution computed tomography images into life-size physical models. We sought to apply 3D printing technologies to develop patient-specific models of the anatomic and functional characteristics of severe aortic valve stenosis. Methods and Results-Eight patient-specific models of severe aortic stenosis (6 tricuspid and 2 bicuspid) were created using dual-material fused 3D printing. Tissue types were identified and segmented from clinical computed tomography image data. A rigid material was used for printing calcific regions, and a rubber-like material was used for soft tissue structures of the outflow tract, aortic root, and noncalcified valve cusps. Each model was evaluated for its geometric valve orifice area, echocardiographic image quality, and aortic stenosis severity by Doppler and Gorlin methods under 7 different in vitro stroke volume conditions. Fused multimaterial 3D printed models replicated the focal calcific structures of aortic stenosis. Doppler-derived measures of peak and mean transvalvular gradient correlated well with reference standard pressure catheters across a range of flow conditions (r=0.988 and r=0.978 respectively, P<0.001). Aortic valve orifice area by Gorlin and Doppler methods correlated well (r=0.985, P<0.001). Calculated aortic valve area increased a small amount for both methods with increasing flow (P=0.002). Conclusions-By combing the technologies of high-spatial resolution computed tomography, computer-aided design software, and fused dual-material 3D printing, we demonstrate that patient-specific models can replicate both the anatomic and functional properties of severe degenerative aortic valve stenosis.

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Maragiannis, D., Jackson, M. S., Igo, S. R., Schutt, R. C., Connell, P., Grande-Allen, J., … Little, S. H. (2015). Replicating Patient-Specific Severe Aortic Valve Stenosis with Functional 3D Modeling. Circulation: Cardiovascular Imaging, 8(10). https://doi.org/10.1161/CIRCIMAGING.115.003626

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