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Defining Soft Tissue: Bitmap Printing of Soft Tissue for Surgical Planning
Nearly all applications of 3D printing for surgical planning have been limited to bony structures and simple morphological descriptions of complex organs due to the fundamental limitations in accuracy, quality, and efficiency of the current modeling paradigms and technologies. Current approaches hav...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Mary Ann Liebert, Inc., publishers
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9809978/ https://www.ncbi.nlm.nih.gov/pubmed/36654967 http://dx.doi.org/10.1089/3dp.2021.0141 |
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author | Jacobson, Nicholas Carerra, Erik Smith, Lawrence Browne, Lorna Stence, Nicholas Sheridan, Alison MacCurdy, Robert |
author_facet | Jacobson, Nicholas Carerra, Erik Smith, Lawrence Browne, Lorna Stence, Nicholas Sheridan, Alison MacCurdy, Robert |
author_sort | Jacobson, Nicholas |
collection | PubMed |
description | Nearly all applications of 3D printing for surgical planning have been limited to bony structures and simple morphological descriptions of complex organs due to the fundamental limitations in accuracy, quality, and efficiency of the current modeling paradigms and technologies. Current approaches have largely ignored the constitution of soft tissue critical to most surgical specialties where multiple high-resolution variations transition gradually across the interior of the volume. Differences in the scales of organization related to unique organs require special attention to capture fine features critical to surgical procedures. We present a six-material bitmap printing technique for creating 3D models directly from medical images, which are superior in spatial and contrast resolution to current 3D modeling methods, and contain previously unachievable spatial fidelity for soft tissue differentiation. A retrospective exempt IRB was obtained for all data through the Colorado Multiple Institution Review Board #21-3128. |
format | Online Article Text |
id | pubmed-9809978 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Mary Ann Liebert, Inc., publishers |
record_format | MEDLINE/PubMed |
spelling | pubmed-98099782023-01-17 Defining Soft Tissue: Bitmap Printing of Soft Tissue for Surgical Planning Jacobson, Nicholas Carerra, Erik Smith, Lawrence Browne, Lorna Stence, Nicholas Sheridan, Alison MacCurdy, Robert 3D Print Addit Manuf Original Articles Nearly all applications of 3D printing for surgical planning have been limited to bony structures and simple morphological descriptions of complex organs due to the fundamental limitations in accuracy, quality, and efficiency of the current modeling paradigms and technologies. Current approaches have largely ignored the constitution of soft tissue critical to most surgical specialties where multiple high-resolution variations transition gradually across the interior of the volume. Differences in the scales of organization related to unique organs require special attention to capture fine features critical to surgical procedures. We present a six-material bitmap printing technique for creating 3D models directly from medical images, which are superior in spatial and contrast resolution to current 3D modeling methods, and contain previously unachievable spatial fidelity for soft tissue differentiation. A retrospective exempt IRB was obtained for all data through the Colorado Multiple Institution Review Board #21-3128. Mary Ann Liebert, Inc., publishers 2022-12-01 2022-12-13 /pmc/articles/PMC9809978/ /pubmed/36654967 http://dx.doi.org/10.1089/3dp.2021.0141 Text en © Nicholas Jacobson, et al. 2022; Published by Mary Ann Liebert, Inc. https://creativecommons.org/licenses/by/4.0/This Open Access article is distributed under the terms of the Creative Commons License [CC-BY] (http://creativecommons.org/licenses/by/4.0 (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Jacobson, Nicholas Carerra, Erik Smith, Lawrence Browne, Lorna Stence, Nicholas Sheridan, Alison MacCurdy, Robert Defining Soft Tissue: Bitmap Printing of Soft Tissue for Surgical Planning |
title | Defining Soft Tissue: Bitmap Printing of Soft Tissue for Surgical Planning |
title_full | Defining Soft Tissue: Bitmap Printing of Soft Tissue for Surgical Planning |
title_fullStr | Defining Soft Tissue: Bitmap Printing of Soft Tissue for Surgical Planning |
title_full_unstemmed | Defining Soft Tissue: Bitmap Printing of Soft Tissue for Surgical Planning |
title_short | Defining Soft Tissue: Bitmap Printing of Soft Tissue for Surgical Planning |
title_sort | defining soft tissue: bitmap printing of soft tissue for surgical planning |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9809978/ https://www.ncbi.nlm.nih.gov/pubmed/36654967 http://dx.doi.org/10.1089/3dp.2021.0141 |
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