Jia-Jun Xu1,2, Yu-Jia Luo1, Jin-Hua Wang1, Wei-Ze Xu1, Zhuo Shi1, Jian-Zhong Fu2, Qiang Shu3. 1. Department of Heart Center, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China. 2. School of Mechanical Engineering, Zhejiang University, Hangzhou, 310058, China. 3. Department of Heart Center, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China. shuqiang@zju.edu.cn.
Abstract
BACKGROUND: Preoperative planning for children with congenital heart diseases remains crucial and challenging. This study aimed to investigate the roles of three-dimensional printed patient-specific heart models in the presurgical planning for complex congenital heart disease. METHODS: From May 2017 to January 2018, 15 children diagnosed with complex congenital heart disease were included in this study. Heart models were printed based on computed tomography (CT) imaging reconstruction by a 3D printer with photosensitive resin using the stereolithography apparatus technology. Surgery options were first evaluated by a sophisticated cardiac surgery group using CT images only, and then surgical plans were also set up based on heart models. RESULTS: Fifteen 3D printed heart models were successfully generated. According to the decisions based on CT, 13 cases were consistent with real options, while the other 2 were not. According to 3D printed heart models, all the 15 cases were consistent with real options. Unfortunately, one child diagnosed with complete transposition of great arteries combined with interruption of aortic arch (type A) died 5 days after operation due to postoperative low cardiac output syndrome. The cardiologists, especially the younger ones, considered that these 3D printed heart models with tangible, physical and comprehensive illustrations were beneficial for preoperative planning of complex congenital heart diseases. CONCLUSION: 3D printed heart models are beneficial and promising in preoperative planning for complex congenital heart diseases, and are able to help conform or even improve the surgery options.
BACKGROUND: Preoperative planning for children with congenital heart diseases remains crucial and challenging. This study aimed to investigate the roles of three-dimensional printed patient-specific heart models in the presurgical planning for complex congenital heart disease. METHODS: From May 2017 to January 2018, 15 children diagnosed with complex congenital heart disease were included in this study. Heart models were printed based on computed tomography (CT) imaging reconstruction by a 3D printer with photosensitive resin using the stereolithography apparatus technology. Surgery options were first evaluated by a sophisticated cardiac surgery group using CT images only, and then surgical plans were also set up based on heart models. RESULTS: Fifteen 3D printed heart models were successfully generated. According to the decisions based on CT, 13 cases were consistent with real options, while the other 2 were not. According to 3D printed heart models, all the 15 cases were consistent with real options. Unfortunately, one child diagnosed with complete transposition of great arteries combined with interruption of aortic arch (type A) died 5 days after operation due to postoperative low cardiac output syndrome. The cardiologists, especially the younger ones, considered that these 3D printed heart models with tangible, physical and comprehensive illustrations were beneficial for preoperative planning of complex congenital heart diseases. CONCLUSION: 3D printed heart models are beneficial and promising in preoperative planning for complex congenital heart diseases, and are able to help conform or even improve the surgery options.
Authors: Pia Gehrsitz; Oliver Rompel; Martin Schöber; Robert Cesnjevar; Ariawan Purbojo; Michael Uder; Sven Dittrich; Muhannad Alkassar Journal: Front Cardiovasc Med Date: 2021-02-09
Authors: Anna Olejnik; Julia Anna Semba; Adam Kulpa; Aleksandra Dańczak-Pazdrowska; Jakub Dalibor Rybka; Justyna Gornowicz-Porowska Journal: ACS Synth Biol Date: 2021-12-30 Impact factor: 5.110