Haghiashtiani, GhazalehQiu, KaiyanSanchez, Jorge D ZhingreFuenning, Zachary JNair, PriyaAhlberg, Sarah EIaizzo, Paul AMcAlpine, Michael C2020-06-092020-06-092020-06-09https://hdl.handle.net/11299/213919The data set includes the experimental data and the code files for 3D printed patient-specific aortic root models with internal sensors for minimally invasive applications.Minimally invasive surgeries have numerous advantages, yet complications may arise from limited knowledge about the anatomical site targeted for the delivery of therapy. Transcatheter aortic valve replacement (TAVR) is a minimally invasive procedure for treating aortic stenosis. Here, we demonstrate multi-material 3D printing of patient-specific soft aortic root models with internally-integrated electronic sensor arrays that can augment testing for TAVR preprocedural planning. We evaluated the efficacies of the models by comparing their geometric fidelities with postoperative data from patients, as well as their in vitro hemodynamic performances in cases with and without leaflet calcifications. Furthermore, we uniquely demonstrated that internal sensor arrays can facilitate the optimization of bioprosthetic valve selections and in vitro placements via mapping of the pressures applied on the critical regions of the aortic anatomies. Such models may pave new avenues for mitigating the risks of postoperative complications, as well as facilitating the development of next-generation medical devices.Attribution-NonCommercial 3.0 United States3D printingPatient-specific organ modelsSensorsDatasethttps://doi.org/10.13020/xjv7-s394