2, Piedmont Heart Institute, Atlanta, Georgia, United States
Patient-specific phantoms have a wide range of biomedical applications including validation of computational models and imaging techniques, medical device testing, surgery planning, medical education, doctor-patient interaction, etc. Although additive manufacturing technologies have demonstrated great potential in fabricating patient-specific phantoms, current 3D printed phantoms are usually only geometrically accurate. Mechanical properties of soft tissues can merely be mimicked at small strain situations, such as ultrasonic induced vibration. Under large deformation, the soft tissues and the 3D printed phantoms behave differently. The essential barrier is the inherent difference in the stress-strain curves of soft tissues and 3D printable polymers. This study investigated the feasibility of mimicking the strain-stiffening behavior of soft tissues using dual-material 3D printed metamaterials with micro-structured reinforcement embedded in soft polymeric matrix. Three types of metamaterials were designed and tested: sinusoidal wave, double helix, and interlocking chains. Even though the two base materials were strain-softening polymers, both finite element analysis and uniaxial tension tests indicated that two of those dual-material designs were able to exhibit strain-stiffening effects as a metamaterial. The effects of the design parameters on the mechanical behavior of the metamaterials were also studied. The results suggested that metamaterial 3D printing technique can be used to create patient-specific phantoms that mimic the mechanical properties of biological tissues. As a proof-of-concept study, we used the 3D printed tissue-mimicking phantoms to quantitatively assess the post-transcatheter aortic valve replacement (TAVR) aortic root strain in vitro. A novel indicator of the post-TAVR annular strain unevenness, the annular bulge index, outperformed the other established variables and achieved a high level of accuracy in predicting post-TAVR paravalvular leak, in terms of its occurrence, severity, and location. This work has promising applications in procedural planning for cardiovascular interventions.
 Zhen Qian, Changsheng Wu, et al. Rapid prototyping of the aortic root in severe aortic stenosis for pre-TAVR planning, Circulation (2014) 130:A20259
 Kan Wang, Changsheng Wu (co-first author), et al. Dual-material 3D printed metamaterials with tunable mechanical properties for patient-specific tissue-mimicking phantoms, Additive Manufacturing 12 (2016) 31-37
 Zhen Qian, Kan Wang, Changsheng Wu, et al. Quantitative prediction of paravalvular leak in transcatheter aortic valve replacement based on tissue-mimicking 3D printing, JACC: Cardiovascular Imaging 10 (2017) 719-731