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3D printing for congenital heart disease: a single site’s initial three-yearexperience

BACKGROUND: 3D printing is an ideal manufacturing process for creating patient-matched models (anatomical models) for surgical and interventional planning. Cardiac anatomical models have been described in numerous case studies and journal publications. However, few studies attempt to describe wider...

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Autores principales: Ryan, Justin, Plasencia, Jonathan, Richardson, Randy, Velez, Daniel, Nigro, John J., Pophal, Stephen, Frakes, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6223396/
https://www.ncbi.nlm.nih.gov/pubmed/30649650
http://dx.doi.org/10.1186/s41205-018-0033-8
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author Ryan, Justin
Plasencia, Jonathan
Richardson, Randy
Velez, Daniel
Nigro, John J.
Pophal, Stephen
Frakes, David
author_facet Ryan, Justin
Plasencia, Jonathan
Richardson, Randy
Velez, Daniel
Nigro, John J.
Pophal, Stephen
Frakes, David
author_sort Ryan, Justin
collection PubMed
description BACKGROUND: 3D printing is an ideal manufacturing process for creating patient-matched models (anatomical models) for surgical and interventional planning. Cardiac anatomical models have been described in numerous case studies and journal publications. However, few studies attempt to describe wider impact of the novel planning augmentation tool. The work here presents the evolution of an institution’s first 3 full years of 3D prints following consistent integration of the technology into clinical workflow (2012–2014) - a center which produced 79 models for surgical planning (within that time frame). Patient outcomes and technology acceptance following implementation of 3D printing were reviewed. METHODS: A retrospective analysis was designed to investigate the anatomical model’s impact on time-based surgical metrics. A contemporaneous cohort of standard-of-care pre-procedural planning (no anatomical models) was identified for comparative analysis. A post-surgery technology acceptance assessment was also employed in a smaller subset to measure perceived efficacy of the anatomical models. The data was examined. RESULTS: Within the timeframe of the study, 928 primary-case cardiothoracic surgeries (encompassing both CHD and non-CHD surgeries) took place at the practicing pediatric hospital. One hundred sixty four anatomical models had been generated for various purposes. An inclusion criterion based on lesion type limited those with anatomic models to 33; there were 113 cases matching the same criterion that received no anatomical model. Time-based metrics such as case length-of-time showed a mean reduction in overall time for anatomical models. These reductions were not statistically significant. The technology acceptance survey did demonstrate strong perceived efficacy. Anecdotal vignettes further support the technology acceptance. DISCUSSION & CONCLUSION: The anatomical models demonstrate trends for reduced operating room and case length of time when compared with similar surgeries in the same time-period; in turn, these reductions could have significant impact on patient outcomes and operating room economics. While analysis did not yield robust statistical powering, strong Cohen’s d values suggest poor powering may be more related to sample size than non-ideal outcomes. The utility of planning with an anatomical model is further supported by the technology acceptance study which demonstrated that surgeons perceive the anatomical models to be an effective tool in surgical planning for a complex CHD repair. A prospective multi-center trial is currently in progress to further validate or reject these findings.
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spelling pubmed-62233962018-11-26 3D printing for congenital heart disease: a single site’s initial three-yearexperience Ryan, Justin Plasencia, Jonathan Richardson, Randy Velez, Daniel Nigro, John J. Pophal, Stephen Frakes, David 3D Print Med Research BACKGROUND: 3D printing is an ideal manufacturing process for creating patient-matched models (anatomical models) for surgical and interventional planning. Cardiac anatomical models have been described in numerous case studies and journal publications. However, few studies attempt to describe wider impact of the novel planning augmentation tool. The work here presents the evolution of an institution’s first 3 full years of 3D prints following consistent integration of the technology into clinical workflow (2012–2014) - a center which produced 79 models for surgical planning (within that time frame). Patient outcomes and technology acceptance following implementation of 3D printing were reviewed. METHODS: A retrospective analysis was designed to investigate the anatomical model’s impact on time-based surgical metrics. A contemporaneous cohort of standard-of-care pre-procedural planning (no anatomical models) was identified for comparative analysis. A post-surgery technology acceptance assessment was also employed in a smaller subset to measure perceived efficacy of the anatomical models. The data was examined. RESULTS: Within the timeframe of the study, 928 primary-case cardiothoracic surgeries (encompassing both CHD and non-CHD surgeries) took place at the practicing pediatric hospital. One hundred sixty four anatomical models had been generated for various purposes. An inclusion criterion based on lesion type limited those with anatomic models to 33; there were 113 cases matching the same criterion that received no anatomical model. Time-based metrics such as case length-of-time showed a mean reduction in overall time for anatomical models. These reductions were not statistically significant. The technology acceptance survey did demonstrate strong perceived efficacy. Anecdotal vignettes further support the technology acceptance. DISCUSSION & CONCLUSION: The anatomical models demonstrate trends for reduced operating room and case length of time when compared with similar surgeries in the same time-period; in turn, these reductions could have significant impact on patient outcomes and operating room economics. While analysis did not yield robust statistical powering, strong Cohen’s d values suggest poor powering may be more related to sample size than non-ideal outcomes. The utility of planning with an anatomical model is further supported by the technology acceptance study which demonstrated that surgeons perceive the anatomical models to be an effective tool in surgical planning for a complex CHD repair. A prospective multi-center trial is currently in progress to further validate or reject these findings. Springer International Publishing 2018-11-08 /pmc/articles/PMC6223396/ /pubmed/30649650 http://dx.doi.org/10.1186/s41205-018-0033-8 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Ryan, Justin
Plasencia, Jonathan
Richardson, Randy
Velez, Daniel
Nigro, John J.
Pophal, Stephen
Frakes, David
3D printing for congenital heart disease: a single site’s initial three-yearexperience
title 3D printing for congenital heart disease: a single site’s initial three-yearexperience
title_full 3D printing for congenital heart disease: a single site’s initial three-yearexperience
title_fullStr 3D printing for congenital heart disease: a single site’s initial three-yearexperience
title_full_unstemmed 3D printing for congenital heart disease: a single site’s initial three-yearexperience
title_short 3D printing for congenital heart disease: a single site’s initial three-yearexperience
title_sort 3d printing for congenital heart disease: a single site’s initial three-yearexperience
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6223396/
https://www.ncbi.nlm.nih.gov/pubmed/30649650
http://dx.doi.org/10.1186/s41205-018-0033-8
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