Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Jacobson, Nicholas, Carerra, Erik, Smith, Lawrence, Browne, Lorna, Stence, Nicholas, Sheridan, Alison, MacCurdy, Robert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Mary Ann Liebert, Inc., publishers 2022
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
_version_ 1784863233833697280
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
work_keys_str_mv AT jacobsonnicholas definingsofttissuebitmapprintingofsofttissueforsurgicalplanning
AT carerraerik definingsofttissuebitmapprintingofsofttissueforsurgicalplanning
AT smithlawrence definingsofttissuebitmapprintingofsofttissueforsurgicalplanning
AT brownelorna definingsofttissuebitmapprintingofsofttissueforsurgicalplanning
AT stencenicholas definingsofttissuebitmapprintingofsofttissueforsurgicalplanning
AT sheridanalison definingsofttissuebitmapprintingofsofttissueforsurgicalplanning
AT maccurdyrobert definingsofttissuebitmapprintingofsofttissueforsurgicalplanning