Data set from Gorla R, De Marco F, Morganti S, Finotello A, Brambilla N, Testa L, Agnifili ML, Tusa M, Auricchio F, Bedogni F. Transcatheter aortic valve implantation with the Portico and Evolut R bioprostheses in patients with elliptic aortic annulus. EuroIntervention. 2020 Apr 3;15(18):e1588-e1591. doi: 10.4244/EIJ-D-19-00115. PMID: 31186219.

Data set from Gorla R, De Marco F, Morganti S, Finotello A, Brambilla N, Testa L, Agnifili ML, Tusa M, Auricchio F, Bedogni F. Transcatheter aortic valve implantation with the Portico and Evolut R bioprostheses in patients with elliptic aortic annulus. EuroIntervention. 2020 Apr 3;15(18):e1588-e1591. doi: 10.4244/EIJ-D-19-00115. PMID: 31186219.

Data set from Spinelli D, Marconi S, Caruso R, Conti M, Benedetto F, De Beaufort HW, Auricchio F, Trimarchi S. 3D printing of aortic models as a teaching tool for improving understanding of aortic disease. J Cardiovasc Surg (Torino). 2019 Oct;60(5):582-588. doi: 10.23736/S0021-9509.19.10841-5. Epub 2019 Jun 26. PMID: 31256581. This is the abstract: Background: A geometrical understanding of the individual patient's disease morphology is crucial in aortic surgery. The aim of our study was to validate a questionnaire addressing understanding of aortic disease and use this questionnaire to investigate the value of 3D printing as a teaching tool for surgical trainees. Methods: Anonymized CT-angiography images of six different patients were selected as didactic cases of aortic disease and made into 3D models of transparent rigid resin with the Vat-photopolymerization technique. The 3D aortic models, which could be disassembled and reassembled, were displayed to 37 surgical trainees, immediately after a seminar on aortic disease. A questionnaire was developed to compare the trainees' understanding before (T0) and after (T1) demonstration of the 3D printed models. Results: A panel of 15 experts participated in evaluating face and content validity of the questionnaire. The questionnaire validity was established and therefore the information investigated by the questionnaire could be synthetized using the mean of the items to indicate the understanding. The participants (mean age 28 years, range 26-34, male 59%) showed a significant improvement in understanding from T0 (median=7.25; IQR=1.50) to T1 (median=8.00; IQR=1.50; P=0.002). Conclusions: Preliminary data suggest that the use of 3D-printed aortic models as a teaching tool was feasible and improved the understanding of aortic disease among surgical trainees.

Data set from Spinelli D, Marconi S, Caruso R, Conti M, Benedetto F, De Beaufort HW, Auricchio F, Trimarchi S. 3D printing of aortic models as a teaching tool for improving understanding of aortic disease. J Cardiovasc Surg (Torino). 2019 Oct;60(5):582-588. doi: 10.23736/S0021-9509.19.10841-5. Epub 2019 Jun 26. PMID: 31256581. This is the abstract: Background: A geometrical understanding of the individual patient's disease morphology is crucial in aortic surgery. The aim of our study was to validate a questionnaire addressing understanding of aortic disease and use this questionnaire to investigate the value of 3D printing as a teaching tool for surgical trainees. Methods: Anonymized CT-angiography images of six different patients were selected as didactic cases of aortic disease and made into 3D models of transparent rigid resin with the Vat-photopolymerization technique. The 3D aortic models, which could be disassembled and reassembled, were displayed to 37 surgical trainees, immediately after a seminar on aortic disease. A questionnaire was developed to compare the trainees' understanding before (T0) and after (T1) demonstration of the 3D printed models. Results: A panel of 15 experts participated in evaluating face and content validity of the questionnaire. The questionnaire validity was established and therefore the information investigated by the questionnaire could be synthetized using the mean of the items to indicate the understanding. The participants (mean age 28 years, range 26-34, male 59%) showed a significant improvement in understanding from T0 (median=7.25; IQR=1.50) to T1 (median=8.00; IQR=1.50; P=0.002). Conclusions: Preliminary data suggest that the use of 3D-printed aortic models as a teaching tool was feasible and improved the understanding of aortic disease among surgical trainees.