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Description:

Additive manufacturing (AM) is a powerful approach in healthcare to augment the functionalities of patient-specific medical products and surgical tools. One such area of the healthcare industry is surgical planningand procedures, where the benefits of AM can revolutionize the industry. AM technologies, commonlyknown as three-dimensional (3D) printing, can change the conventional surgical methodology from the‘‘open-detect–operate-close’’ mode to the ‘‘detect-open–operate-close’’ mode. However, the use of 3Dprinting in surgical planning has been hampered by the limited availability of literature reports thoroughlyexamining the advantages and drawbacks of this technology in clinical settings. Hence, this review exploresthe widespread use of additive manufacturing, multi-materials, metamaterials, 4D printing, and artificialintelligence in surgical planning for complex surgical procedures of the spine and in orthopedics, dentistry,cardiology, gynecology, and neurology. This review focuses on meticulously adjusting the lattice structureof metamaterials during 3D printing to achieve specific mechanical properties. It further delves into 4Dprinting to achieve dynamic capabilities in 3D printed models for better integration with the host tissue.Furthermore, it highlights the key aspects of combining AM with artificial intelligence/machine learning (AI/ML) models in healthcare to automate 3D model production and thereby reduce human intervention. Thiscomprehensive review offers bioengineers, clinical scientists, and clinicians a platform to explore AM and itspotential for addressing pre- and post-surgical operation challenges, providing valuable insights forbiomedical engineering and healthcare advancements

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• In Copyright
  

Keyword: 3D printing, additive manufacturing

Date published: 2025-06-11

Publisher: Royal Society of Chemistry (RSC)

Journal:

• Materials Horizons (ISSN: 20516347) vol. 12 issue. 19 p. 7814-7864

Funding:

• Department of Higher Education, India
• Science and Engineering Research Board SRG/2019/001504
• Science and Engineering Research Board SRG/2021/000859
• Prince Sultan University

Manuscript type: Author's version (Accepted manuscript)

MDR DOI: https://doi.org/10.48505/nims.5960

First published URL: https://doi.org/10.1039/d5mh00501a

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Updated at: 2025-12-04 17:56:26 +0900

Published on MDR: 2026-06-11 08:30:59 +0900