Three-dimensional printing in congenital heart disease: A systematic review

Abstract

Three-dimensional (3D) printing has shown great promise in medicine with increasing reports in congenital heart disease (CHD). This systematic review aims to analyse the main clinical applications and accuracy of 3D printing in CHD, as well as to provide an overview of the software tools, time and costs associated with the generation of 3D printed heart models. A search of different databases was conducted to identify studies investigating the application of 3D printing in CHD. Studies based on patient's medical imaging datasets were included for analysis, while reports on in vitro phantom or review articles were excluded from the analysis. A total of 28 studies met selection criteria for inclusion in the review. More than half of the studies were based on isolated case reports with inclusion of 1-12 cases (61%), while 10 studies (36%) focused on the survey of opinion on the usefulness of 3D printing by healthcare professionals, patients, parents of patients and medical students, and the remaining one involved a multicentre study about the clinical value of 3D printed models in surgical planning of CHD. The analysis shows that patient-specific 3D printed models accurately replicate complex cardiac anatomy, improve understanding and knowledge about congenital heart diseases and demonstrate value in preoperative planning and simulation of cardiac or interventional procedures, assist surgical decision-making and intra-operative orientation, and improve patient-doctor communication and medical education. The cost of 3D printing ranges from USD 55 to USD 810. This systematic review shows the usefulness of 3D printed models in congenital heart disease with applications ranging from accurate replication of complex cardiac anatomy and pathology to medical education, preoperative planning and simulation. The additional cost and time required to manufacture the 3D printed models represent the limitations which need to be addressed in future studies.

Keywords: 3D printing; congenital heart disease; model; simulation.

Figure 1

Flow chart showing search strategy to identify eligible studies.

Figure 2

Statistically significant changes were observed in confidence (A), knowledge (B) and satisfaction (C) amongst participants comparing responses before (“Pre”) and after (“Post”) their consultation. Note for a 1 = Not at all confident – 5 = Very confident; for b each point represents a point in knowledge, as marked according to the correct name of primary diagnosis, correctly identified keywords and correct use of diagrams; for c1 = Very dissatisfied – 5 = Very satisfied. The red lines indicate average score. Reprint with permission from Biglino et al.9

Figure 3

Summary of participants’ level of agreement to different statements on 3D models. Reprint with permission from Biglino et al.9

Figure 4

3D printed model of congenital heart disease in a 20‐month‐old boy. (A) 3D printed model which was created from cardiac CT images shows double outlet right ventricle with aorta and pulmonary trunk arising from the right ventricle (white arrows), and ventricular septal defect (black arrow). (B) 3D heart model is printed with use of photopolymer material showing the flexibility of the material.