3D printing of self-healing personalized liver models for surgical training and preoperative planning
Abstract 3D printing can produce intuitive, precise, and personalized anatomical models, providing invaluable support for precision medicine, particularly in areas like surgical training and preoperative planning. However, conventional 3D printed models are often significantly more rigid than human...
Main Authors: | , , , , , , |
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Format: | Article |
Language: | English |
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Nature Portfolio
2023-12-01
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Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-023-44324-6 |
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author | Yahui Lu Xing Chen Fang Han Qian Zhao Tao Xie Jingjun Wu Yuhua Zhang |
author_facet | Yahui Lu Xing Chen Fang Han Qian Zhao Tao Xie Jingjun Wu Yuhua Zhang |
author_sort | Yahui Lu |
collection | DOAJ |
description | Abstract 3D printing can produce intuitive, precise, and personalized anatomical models, providing invaluable support for precision medicine, particularly in areas like surgical training and preoperative planning. However, conventional 3D printed models are often significantly more rigid than human organs and cannot undergo repetitive resection, which severely restricts their clinical value. Here we report the stereolithographic 3D printing of personalized liver models based on physically crosslinked self-healing elastomers with liver-like softness. Benefiting from the short printing time, the highly individualized models can be fabricated immediately following enhanced CT examination. Leveraging the high-efficiency self-healing performance, these models support repetitive resection for optimal trace through a trial-and-error approach. At the preliminary explorative clinical trial (NCT06006338), a total of 5 participants are included for preoperative planning. The primary outcomes indicate that the negative surgery margins are achieved and the unforeseen injuries of vital vascular structures are avoided. The 3D printing of liver models can enhance the safety of hepatic surgery, demonstrating promising application value in clinical practice. |
first_indexed | 2024-03-08T19:45:09Z |
format | Article |
id | doaj.art-23447e20fa0440d38fe24d707c660470 |
institution | Directory Open Access Journal |
issn | 2041-1723 |
language | English |
last_indexed | 2024-03-08T19:45:09Z |
publishDate | 2023-12-01 |
publisher | Nature Portfolio |
record_format | Article |
series | Nature Communications |
spelling | doaj.art-23447e20fa0440d38fe24d707c6604702023-12-24T12:24:21ZengNature PortfolioNature Communications2041-17232023-12-011411810.1038/s41467-023-44324-63D printing of self-healing personalized liver models for surgical training and preoperative planningYahui Lu0Xing Chen1Fang Han2Qian Zhao3Tao Xie4Jingjun Wu5Yuhua Zhang6State Key Laboratory of Chemical Engineering, College of Chemical and Biological Engineering, Zhejiang UniversityZhejiang Cancer HospitalZhejiang Cancer HospitalState Key Laboratory of Chemical Engineering, College of Chemical and Biological Engineering, Zhejiang UniversityState Key Laboratory of Chemical Engineering, College of Chemical and Biological Engineering, Zhejiang UniversityState Key Laboratory of Chemical Engineering, College of Chemical and Biological Engineering, Zhejiang UniversityZhejiang Cancer HospitalAbstract 3D printing can produce intuitive, precise, and personalized anatomical models, providing invaluable support for precision medicine, particularly in areas like surgical training and preoperative planning. However, conventional 3D printed models are often significantly more rigid than human organs and cannot undergo repetitive resection, which severely restricts their clinical value. Here we report the stereolithographic 3D printing of personalized liver models based on physically crosslinked self-healing elastomers with liver-like softness. Benefiting from the short printing time, the highly individualized models can be fabricated immediately following enhanced CT examination. Leveraging the high-efficiency self-healing performance, these models support repetitive resection for optimal trace through a trial-and-error approach. At the preliminary explorative clinical trial (NCT06006338), a total of 5 participants are included for preoperative planning. The primary outcomes indicate that the negative surgery margins are achieved and the unforeseen injuries of vital vascular structures are avoided. The 3D printing of liver models can enhance the safety of hepatic surgery, demonstrating promising application value in clinical practice.https://doi.org/10.1038/s41467-023-44324-6 |
spellingShingle | Yahui Lu Xing Chen Fang Han Qian Zhao Tao Xie Jingjun Wu Yuhua Zhang 3D printing of self-healing personalized liver models for surgical training and preoperative planning Nature Communications |
title | 3D printing of self-healing personalized liver models for surgical training and preoperative planning |
title_full | 3D printing of self-healing personalized liver models for surgical training and preoperative planning |
title_fullStr | 3D printing of self-healing personalized liver models for surgical training and preoperative planning |
title_full_unstemmed | 3D printing of self-healing personalized liver models for surgical training and preoperative planning |
title_short | 3D printing of self-healing personalized liver models for surgical training and preoperative planning |
title_sort | 3d printing of self healing personalized liver models for surgical training and preoperative planning |
url | https://doi.org/10.1038/s41467-023-44324-6 |
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