Publicação
Transforming surgical planning and procedures through the synergistic use of additive manufacturing, advanced materials and artificial intelligence: challenges and opportunities
| Resumo: | 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 planning and procedures, where the benefits of AM can revolutionize the industry. AM technologies, commonly known 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 3D printing in surgical planning has been hampered by the limited availability of literature reports thoroughly examining the advantages and drawbacks of this technology in clinical settings. Hence, this review explores the widespread use of additive manufacturing, multi-materials, metamaterials, 4D printing, and artificial intelligence 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 structure of metamaterials during 3D printing to achieve specific mechanical properties. It further delves into 4D printing 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. This comprehensive review offers bioengineers, clinical scientists, and clinicians a platform to explore AM and its potential for addressing pre- and post-surgical operation challenges, providing valuable insights for biomedical engineering and healthcare advancements. |
|---|---|
| Autores principais: | Tripathi, S. |
| Outros Autores: | Ansari, A. A.; Singh, M.; Dash, M.; Kumar, P.; Singh, H.; Panda, B.; Nukavarapu, S.; Camci-Unal, G.; Li, B.; Jain, P. K.; Jayaganthan, R.; Mehboob, H.; Junaedi, H.; Nanda, H. S.; Chen, G.; Kundu, Subhas C |
| Assunto: | additive manufacturing biomedical engineering healthcare industry |
| Ano: | 2025 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso restrito |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| _version_ | 1867439876639555584 |
|---|---|
| author | Tripathi, S. |
| author2 | Ansari, A. A. Singh, M. Dash, M. Kumar, P. Singh, H. Panda, B. Nukavarapu, S. Camci-Unal, G. Li, B. Jain, P. K. Jayaganthan, R. Mehboob, H. Junaedi, H. Nanda, H. S. Chen, G. Kundu, Subhas C |
| author2_role | author author author author author author author author author author author author author author author author |
| author_facet | Tripathi, S. Ansari, A. A. Singh, M. Dash, M. Kumar, P. Singh, H. Panda, B. Nukavarapu, S. Camci-Unal, G. Li, B. Jain, P. K. Jayaganthan, R. Mehboob, H. Junaedi, H. Nanda, H. S. Chen, G. Kundu, Subhas C |
| author_role | author |
| contributor_name_str_mv | RepositóriUM - Universidade do Minho |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Tripathi, S.\"},{\"Person.name\":\"Ansari, A. A.\"},{\"Person.name\":\"Singh, M.\"},{\"Person.name\":\"Dash, M.\"},{\"Person.name\":\"Kumar, P.\"},{\"Person.name\":\"Singh, H.\"},{\"Person.name\":\"Panda, B.\"},{\"Person.name\":\"Nukavarapu, S.\"},{\"Person.name\":\"Camci-Unal, G.\"},{\"Person.name\":\"Li, B.\"},{\"Person.name\":\"Jain, P. K.\"},{\"Person.name\":\"Jayaganthan, R.\"},{\"Person.name\":\"Mehboob, H.\"},{\"Person.name\":\"Junaedi, H.\"},{\"Person.name\":\"Nanda, H. S.\"},{\"Person.name\":\"Chen, G.\"},{\"Person.name\":\"Kundu, Subhas C\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | RepositóriUM - Universidade do Minho |
| datacite.creators.creator.creatorName.fl_str_mv | Tripathi, S. Ansari, A. A. Singh, M. Dash, M. Kumar, P. Singh, H. Panda, B. Nukavarapu, S. Camci-Unal, G. Li, B. Jain, P. K. Jayaganthan, R. Mehboob, H. Junaedi, H. Nanda, H. S. Chen, G. Kundu, Subhas C |
| datacite.date.Accepted.fl_str_mv | 2025-06-01T00:00:00Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_16ec |
| datacite.subjects.subject.fl_str_mv | additive manufacturing biomedical engineering healthcare industry |
| datacite.titles.title.fl_str_mv | Transforming surgical planning and procedures through the synergistic use of additive manufacturing, advanced materials and artificial intelligence: challenges and opportunities |
| dc.contributor.none.fl_str_mv | RepositóriUM - Universidade do Minho |
| dc.creator.none.fl_str_mv | Tripathi, S. Ansari, A. A. Singh, M. Dash, M. Kumar, P. Singh, H. Panda, B. Nukavarapu, S. Camci-Unal, G. Li, B. Jain, P. K. Jayaganthan, R. Mehboob, H. Junaedi, H. Nanda, H. S. Chen, G. Kundu, Subhas C |
| dc.date.Accepted.fl_str_mv | 2025-06-01T00:00:00Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | https://hdl.handle.net/1822/98420 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | Royal Society of Chemistry |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_16ec |
| dc.rights.rights.copyright.fl_str_mv | restrictedAccess |
| dc.subject.none.fl_str_mv | additive manufacturing biomedical engineering healthcare industry |
| dc.title.fl_str_mv | Transforming surgical planning and procedures through the synergistic use of additive manufacturing, advanced materials and artificial intelligence: challenges and opportunities |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_6501 |
| 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 planning and procedures, where the benefits of AM can revolutionize the industry. AM technologies, commonly known 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 3D printing in surgical planning has been hampered by the limited availability of literature reports thoroughly examining the advantages and drawbacks of this technology in clinical settings. Hence, this review explores the widespread use of additive manufacturing, multi-materials, metamaterials, 4D printing, and artificial intelligence 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 structure of metamaterials during 3D printing to achieve specific mechanical properties. It further delves into 4D printing 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. This comprehensive review offers bioengineers, clinical scientists, and clinicians a platform to explore AM and its potential for addressing pre- and post-surgical operation challenges, providing valuable insights for biomedical engineering and healthcare advancements. |
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| institution | Universidade do Minho |
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| language | eng |
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| network_name_str | RepositóriUM - Universidade do Minho |
| oai_identifier_str | oai:repositorium.uminho.pt:1822/98420 |
| organization_str_mv | urn:organizationAcronym:repositorium |
| person_str_mv | Tripathi, S. Ansari, A. A. Singh, M. Dash, M. Kumar, P. Singh, H. Panda, B. Nukavarapu, S. Camci-Unal, G. Li, B. Jain, P. K. Jayaganthan, R. Mehboob, H. Junaedi, H. Nanda, H. S. Chen, G. Kundu, Subhas C |
| publishDate | 2025 |
| publisher.none.fl_str_mv | Royal Society of Chemistry |
| reponame_str | RepositóriUM - Universidade do Minho |
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| spelling | engRoyal Society of ChemistryporAdditive 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 planning and procedures, where the benefits of AM can revolutionize the industry. AM technologies, commonly known 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 3D printing in surgical planning has been hampered by the limited availability of literature reports thoroughly examining the advantages and drawbacks of this technology in clinical settings. Hence, this review explores the widespread use of additive manufacturing, multi-materials, metamaterials, 4D printing, and artificial intelligence 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 structure of metamaterials during 3D printing to achieve specific mechanical properties. It further delves into 4D printing 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. This comprehensive review offers bioengineers, clinical scientists, and clinicians a platform to explore AM and its potential for addressing pre- and post-surgical operation challenges, providing valuable insights for biomedical engineering and healthcare advancements.application/pdfengTransforming surgical planning and procedures through the synergistic use of additive manufacturing, advanced materials and artificial intelligence: challenges and opportunitiesTripathi, S.Ansari, A. A.Singh, M.Dash, M.Kumar, P.Singh, H.Panda, B.Nukavarapu, S.Camci-Unal, G.Li, B.Jain, P. K.Jayaganthan, R.Mehboob, H.Junaedi, H.Nanda, H. S.Chen, G.Kundu, Subhas CHostingInstitutionOrganizationalRepositóriUM - Universidade do Minhoe-mailmailto:repositorium@usdb.uminho.ptrepositorium@usdb.uminho.ptCITATIONTripathi, S., Ansari, A. A., Singh, M., Dash, M., Kumar, P., Singh, H., Panda, B., Nukavarapu, S., Camci-Unal, G., Li, B., Jain, P. K., Jayaganthan, R., Mehboob, H., Junaedi, H., Nanda, H. S., Chen, G., & Kundu, S. C. (2025). Transforming surgical planning and procedures through the synergistic use of additive manufacturing, advanced materials and artificial intelligence: challenges and opportunities. Materials Horizons, 12(19), 7814–7864. https://doi.org/10.1039/d5mh00501aISSNIsPartOf2051-6355DOIIsPartOf10.1039/D5MH00501AURLHasVersionhttps://pubs.rsc.org/en/content/articlelanding/2025/mh/d5mh00501a2025-062025-102025-11-17T16:53:12Z2025-06-01T00:00:00ZHandlehttps://hdl.handle.net/1822/98420http://purl.org/coar/access_right/c_16ecrestricted accessadditive manufacturingbiomedical engineeringhealthcare industry20257854 bytesliteraturehttp://purl.org/coar/resource_type/c_6501journal article2025-06N/ArestrictedAccesshttp://purl.org/coar/access_right/c_16ecapplication/pdffulltexthttps://repositorium.uminho.pt/bitstreams/ef8934c4-c95e-4cbb-b2fa-d57fda9ced82/download |
| spellingShingle | Transforming surgical planning and procedures through the synergistic use of additive manufacturing, advanced materials and artificial intelligence: challenges and opportunities Tripathi, S. additive manufacturing biomedical engineering healthcare industry |
| status | SINGLETON |
| subject.fl_str_mv | additive manufacturing biomedical engineering healthcare industry |
| title | Transforming surgical planning and procedures through the synergistic use of additive manufacturing, advanced materials and artificial intelligence: challenges and opportunities |
| title_full | Transforming surgical planning and procedures through the synergistic use of additive manufacturing, advanced materials and artificial intelligence: challenges and opportunities |
| title_fullStr | Transforming surgical planning and procedures through the synergistic use of additive manufacturing, advanced materials and artificial intelligence: challenges and opportunities |
| title_full_unstemmed | Transforming surgical planning and procedures through the synergistic use of additive manufacturing, advanced materials and artificial intelligence: challenges and opportunities |
| title_short | Transforming surgical planning and procedures through the synergistic use of additive manufacturing, advanced materials and artificial intelligence: challenges and opportunities |
| title_sort | Transforming surgical planning and procedures through the synergistic use of additive manufacturing, advanced materials and artificial intelligence: challenges and opportunities |
| topic | additive manufacturing biomedical engineering healthcare industry |
| topic_facet | additive manufacturing biomedical engineering healthcare industry |
| url | https://hdl.handle.net/1822/98420 |
| visible | 1 |