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When 3D Printing Technology meets Coarctation of the Aorta: surgical efficiency is increased

Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing which is supported by NNU has made a breakthrough in coarctation of the aorta (CoA) treatment with 3D printing technology. The application of it would help save time on the surgical process modeling and increase the efficiency of the surgery.

CoA is a narrowing segment from the outlet of left ventricle to the aorta which falls into three categories namely valvular stenosis, supravalvular stenosis and subvalvular stenosis. From the infancy to the old age, CoA could happen among any life periods.

Eight infants diagnosed with CoA were enrolled and scanned with magnetic resonance angiography (MRA) by the scientific research team. The eight infants are equally divided into two groups, one is the test group with 3D printing technology employed, the other the control group. As for the former, post-processing of images was performed to remove noises and upgrade the smoothness. Then, region-of-interest were selected. Mimics v14.01 was used on modeling. With all the preparation done, the heart model was printed out and presented to the surgeon as well as infants’ family members. As for the latter, the heart model was displayed on the pictorial display solely. It is found that the surgeon in the test group could make surgery plans within much shorter needed time with the help of 3D printed model. As for the quickest, 2 hours is enough, while it took the surgeon in the control group 3-7days on average to do the same. For the parents, those in the test group appraised the 3D printed heart model as a catalyst for a closer doctor-patient relationship, while others complained about the stereoscopic effect of the pictorial display. 

The paper titled “GW27-e0246 3D printing for coarctation of the aorta” was published in the Journal of the American College of Cardiology (Impact Factor:17.759). The first author of this paper is Yudong Zhang, professor of NNU’s School of Computer Science and Technology, and the second and corresponding author is Jiquan Yang, professor of NNU’s School of Electrical and Automation Engineering. Other participants include NNU Dr. Shuihua Wang, Columbia University professor Zhengchao Dong, and Ming Yang, the director of the Radiology Department in Nanjing Children’s Hospital.