3D Printing and Artificial Intelligence as an aid in therapeutic strategies for cardiovascular diseases in adults: A systematic review

Authors

DOI:

https://doi.org/10.33448/rsd-v15i3.50806

Keywords:

3D Printing, Artificial Intelligence (AI), Cardiovascular Diseases.

Abstract

The advancement of Artificial Intelligence (AI) and 3D Printing enables innovations in the treatment of cardiovascular diseases. These technological tools play a fundamental role in producing individualized 3D models and simulating techniques during surgical procedures. The objective of this study is to analyze the role of Artificial Intelligence and 3D Printing in creating personalized therapeutic planning for cardiovascular diseases. This is an Integrative Review, using data from the National Library of Medicine (PubMed) and the Scientific Electronic Library Online (SciELO), covering the years 2019 to 2024. The descriptors applied were: Artificial Intelligence AND Printing Three-Dimensional AND (Cardiovascular Surgical Procedures OR Cardiovascular). These descriptors are aligned with the Health Sciences Descriptors (DeCS). The use of 3D printing and Artificial Intelligence in the cardiovascular field has provided greater precision in diagnoses, surgical planning, and therapeutic personalization. Imaging exams such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are essential for creating three-dimensional models, supported by specific algorithms and software. These technologies benefit cases such as congenital heart diseases, aortic dissections, and valve replacements, for example, by enabling better anatomical visualization, enhancing medical training, and improving communication with the patient. 3D printing and Artificial Intelligence contribute to the personalized treatment of cardiovascular diseases. However, as this is an evolving field, there is still a lack of information and a need for further studies.

References

An, J., Chua, C. K., & Mironov, V. (2021). Application of Machine Learning in 3D Bioprinting: Focus on Development of Big Data and Digital Twin. International journal of bioprinting, 7(1), 342. https://doi.org/10.18063/ijb.v7i1.342

Baggiano, A., Mushtaq, S., Fusini, L., Muratori, M., Pontone, G., & Pepi, M. (2025). Artificial Intelligence in Cardiovascular Imaging: Current Applications and New Horizons. Journal of cardiovascular echography, 35(2), 97–107. https://doi.org/10.4103/jcecho.jcecho_62_25

Chessa, M., Van De Bruaene, A., Farooqi, K., Valverde, I., Jung, C., Votta, E., Sturla, F., Diller, G. P., Brida, M., Sun, Z., Little, S. H., & Gatzoulis, M. A. (2022). Three-dimensional printing, holograms, computational modelling, and artificial intelligence for adult congenital heart disease care: an exciting future. European Heart Journal, 43(28), 2672–2684. https://doi.org/10.1093/eurheartj/ehac266

Crossetti, M. G. O. (2012). Revisão integrativa de pesquisa na enfermagem o rigor cientifico que lhe é exigido. Rev Gaúcha Enferm. 33(2):8-9.

Dey, D., Slomka, P. J., Leeson, P., Comaniciu, D., Shrestha, S., Sengupta, P. P., & Marwick, T. H. (2019). Artificial intelligence in cardiovascular imaging: JACC state-of-the-art review. Journal of the American College of Cardiology, 73(11), 1317–1335. https://doi.org/10.1016/j.jacc.2018.12.054

Doenças Cardiovasculares. OPAS/OMS | Organização Pan-Americana da Saúde. (n.d.). https://www.paho.org/pt/topicos/doencas-cardiovasculares

Litjens, G., Kooi, T., Bejnordi, B. E., Setio, A. A. A., Ciompi, F., Ghafoorian, M., van der Laak, J. A. W. M., van Ginneken, B., & Sánchez, C. I. (2017). A survey on deep learning in medical image analysis. Medical image analysis, 42, 60–88. https://doi.org/10.1016/j.media.2017.07.005

Mensah, G. A., Fuster, V., Murray, C. J. L., & Roth, G. A. (2023). Global burden of cardiovascular diseases and risks, 1990-2022. Journal of the American College of Cardiology, 82(25), 2350–2473. https://doi.org/10.1016/j.jacc.2023.11.007

Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & The PRISMA Group. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Medicine, 6(7), e1000097. https://doi.org/10.1371/journal.pmed.1000097

Pereira, A. S. et al. (2018). Metodologia da pesquisa científica. [free ebook]. Santa Maria: Editora da UFSM.

Qiu, H., Wen, S., Ji, E., Chen, T., Liu, X., Li, X., Teng, Y., Zhang, Y., Liufu, R., Zhang, J., Xu, X., Chen, J., Huang, M., Cen, J., & Zhuang, J. (2022). A Novel 3D Visualized Operative Procedure in the Single-Stage Complete Repair With Unifocalization of Pulmonary Atresia With Ventricular Septal Defect and Major Aortopulmonary Collateral Arteries. Frontiers in Cardiovascular Medicine, 9, 836200. https://doi.org/10.3389/fcvm.2022.836200

Risemberg, R. I. C. et al. (2026). A importância da metodologia científica no desenvolvimento de artigos científicos. E-Acadêmica, 7(1), e0171675. https://eacademica.org/eacademica/article/view/675.

Roche, C. D., Brereton, R. J. L., Ashton, A. W., Jackson, C., & Gentile, C. (2020). Current challenges in three-dimensional bioprinting heart tissues for cardiac surgery. European journal of cardio-thoracic surgery: official journal of the European Association for Cardio-thoracic Surgery, 58(3), 500–510. https://doi.org/10.1093/ejcts/ezaa093

Silva, A. L., Moraes, J. A., Benitez, L. B., & Kaufmann, E. A. (2021). Impressão 3D: Análise da Evolução e Seus Impactos no Mundo Científico. Revista FSA, 18(11), 124–144. https://doi.org/10.12819/2021.18.11.6

Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research. 104, 333-9. https://doi.org/10.1016/j.jbusres.2019.07.039.

Souza, M. T., Silva, M. D., & Carvalho, R. (2010). Revisão integrativa: O que é e como fazer. Einstein (São Paulo), 8(1), 102–106. https://doi.org/10.1590/s1679-45082010rw1134

Stewart, C. E., Kan, C. F., Stewart, B. R., Sanicola, H. W., Jung, J. P., Sulaiman, O. A., & Wang, D. (2020). Machine Intelligence for Nerve Conduit Design and production. Journal of Biological Engineering, 14(1). https://doi.org/10.1186/s13036-020-00245-2

Sun, Z., Silberstein, J., & Vaccarezza, M. (2024). Cardiovascular Computed Tomography in the Diagnosis of Cardiovascular Disease: Beyond Lumen Assessment. Journal of Cardiovascular Development and Disease, 11(1), 22. https://doi.org/10.3390/jcdd11010022

Vaz Kochhann, E., Alencastro Costa Moreira, C., Miki Alves, G., Vilela Neves Júnior, A., Mattar Marangoni, M., Teixeira de Assis Carvalho, L., Teixeira de Assis Carvalho, G., Fellipe Santos Silva, D., Azara Oliveira, E., & Gonçalves Cherain, L. G. (2022). BIOIMPRESSÃO 3D DE TECIDOS CARDIOVASCULARES. RECIMA21 - Revista Científica Multidisciplinar - ISSN 2675-6218, 3(12), e3122409. https://doi.org/10.47820/recima21.v3i12.2409

Wang, D. D., Qian, Z., Vukicevic, M., Engelhardt, S., Kheradvar, A., Zhang, C., Little, S. H., Verjans, J., Comaniciu, D., O'Neill, W. W., & Vannan, M. A. (2021). 3D Printing, Computational Modeling, and Artificial Intelligence for Structural Heart Disease. JACC. Cardiovascular imaging, 14(1), 41–60. https://doi.org/10.1016/j.jcmg.2019.12.022

Wohlers, T., Gornet, T., Mostow, N., Campbell, I., Diegel, O., Kowen, J., Huff, R., Stucker, B., Fidan, I., Doukas, A., Drab, B., Drstvenšek, I., Eitsert, N., Espalin, D., Feldhausen, T., Ghany, K., Gillett-Crooks, M., Guo, D., Held, A., … Peels, J. (2023). History of additive manufacturing. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4474824

Yan, Y., Su, Y. Y., & Yan, Z. Y. (2022). Preservation of Autologous Brachiocephalic Vessels with Assistance of Three-Dimensional Printing Based on Convolutional Neural Networks. Computational and Mathematical Methods in Medicine, 2022, 6499461. https://doi.org/10.1155/2022/6499461

Published

2026-03-24

Issue

Section

Health Sciences

How to Cite

3D Printing and Artificial Intelligence as an aid in therapeutic strategies for cardiovascular diseases in adults: A systematic review. Research, Society and Development, [S. l.], v. 15, n. 3, p. e6815350806, 2026. DOI: 10.33448/rsd-v15i3.50806. Disponível em: https://rsdjournal.org/rsd/article/view/50806. Acesso em: 24 mar. 2026.