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.

ObjectiveCurrent diagnostic assessment tools remain suboptimal in demonstrating complex morphology of congenital heart disease (CHD). This limitation has posed several challenges in preoperative planning, communication in medical practice, and medical education. This study aims to investigate the dimensional accuracy and the clinical value of 3D printed model of CHD in the above three areas.MethodsUsing cardiac computed tomography angiography (CCTA) data, a patient-specific 3D model of a 20-month-old boy with double outlet right ventricle was printed in Tango Plus material. Pearson correlation coefficient was used to evaluate correlation of the quantitative measurements taken at analogous anatomical locations between the CCTA images pre- and post-3D printing. Qualitative analysis was conducted by distributing surveys to six health professionals (two radiologists, two cardiologists and two cardiac surgeons) and three medical academics to assess the clinical value of the 3D printed model in these three areas.ResultsExcellent correlation (r = 0.99) was noted in the measurements between CCTA and 3D printed model, with a mean difference of 0.23 mm. Four out of six health professionals found the model to be useful in facilitating preoperative planning, while all of them thought that the model would be invaluable in enhancing patient-doctor communication. All three medical academics found the model to be helpful in teaching, and thought that the students will be able to learn the pathology quicker with better understanding.ConclusionThe complex cardiac anatomy can be accurately replicated in flexible material using 3D printing technology. 3D printed heart models could serve as an excellent tool in facilitating preoperative planning, communication in medical practice, and medical education, although further studies with inclusion of more clinical cases are needed.

Patient-specific three-dimensional (3D) printed models have been increasingly used in cardiology and cardiac surgery, in particular, showing great value in the domain of congenital heart disease (CHD). CHD is characterized by complex cardiac anomalies with disease variations between individuals; thus, it is difficult to obtain comprehensive spatial conceptualization of the cardiac structures based on the current imaging visualizations. 3D printed models derived from patient’s cardiac imaging data overcome this limitation by creating personalized 3D heart models, which not only improve spatial visualization, but also assist preoperative planning and simulation of cardiac procedures, serve as a useful tool in medical education and training, and improve doctor–patient communication. This review article provides an overall view of the clinical applications and usefulness of 3D printed models in CHD. Current limitations and future research directions of 3D printed heart models are highlighted.

The aim of this paper is to summarize and evaluate results from existing studies on accuracy and clinical value of three-dimensional printed heart models (3DPHM) for determining whether 3D printing can significantly improve on how the congenital heart disease (CHD) is managed in current clinical practice. Proquest, Google Scholar, Scopus, PubMed, and Medline were searched for relevant studies until April 2019. Two independent reviewers performed manual data extraction and assessed the risk of bias of the studies using the tools published on National Institutes of Health (NIH) website. The following data were extracted from the studies: author, year of publication, study design, imaging modality, segmentation software, utility of 3DPHM, CHD types, and dimensional accuracy. R software was used for the meta-analysis. Twenty-four articles met the inclusion criteria and were included in the systematic review. However, only 7 studies met the statistical requirements and were eligible for meta-analysis. Cochran’s Q test demonstrated significant variation among the studies for both of the meta-analyses of accuracy of 3DPHM and the utility of 3DPHM in medical education. Analysis of all included studies reported the mean deviation between the 3DPHM and the medical images is not significant, implying that 3DPHM are highly accurate. As for the utility of the 3DPHM, it is reported in all relevant studies that the 3DPHM improve the learning experience and satisfaction among the users, and play a critical role in facilitating surgical planning of complex CHD cases. 3DPHM have the potential to enhance communication in medical practice, however their clinical value remains debatable. More studies are required to yield a more meaningful meta-analysis.

Current visualization techniques of complex congenital heart disease (CHD) are unable to provide comprehensive visualization of the anomalous cardiac anatomy as the medical datasets can essentially only be viewed from a flat, two-dimensional (2D) screen. Three-dimensional (3D) printing has therefore been used to replicate patient-specific hearts in 3D views based on medical imaging datasets. This technique has been shown to have a positive impact on the preoperative planning of corrective surgery, patient-doctor communication, and the learning experience of medical students. However, 3D printing is often costly, and this impedes the routine application of this technology in clinical practice. This technical note aims to investigate whether reducing 3D printing costs can have any impact on the clinical value of the 3D-printed heart models. Low-cost and a high-cost 3D-printed models based on a selected case of CHD were generated with materials of differing cost. Quantitative assessment of dimensional accuracy of the cardiac anatomy and pathology was compared between the 3D-printed models and the original cardiac computed tomography (CT) images with excellent correlation (r=0.99). Qualitative evaluation of model usefulness showed no difference between the two models in medical applications.

Both three-dimensional (3D) printing and virtual reality (VR) are reported as being superior to the current visualization techniques in conveying more comprehensive visualization of congenital heart disease (CHD). However, little is known in terms of their clinical value in diagnostic assessment, medical education, and preoperative planning of CHD. This cross-sectional study aims to address these by involving 35 medical practitioners to subjectively evaluate VR visualization of four selected CHD cases in comparison with the corresponding 3D printed heart models (3DPHM). Six questionnaires were excluded due to incomplete sections, hence a total of 29 records were included for the analysis. The results showed both VR and 3D printed heart models were comparable in terms of the degree of realism. VR was perceived as more useful in medical education and preoperative planning compared to 3D printed heart models, although there was no significant difference in the ratings (p = 0.54 and 0.35, respectively). Twenty-one participants (72%) indicated both the VR and 3DPHM provided additional benefits compared to the conventional medical imaging visualizations. This study concludes the similar clinical value of both VR and 3DPHM in CHD, although further research is needed to involve more cardiac specialists for their views on the usefulness of these tools.

Background:The long-term effect of three-dimensional printed heart model (3DPHM) on knowledge acquisition of congenital heart disease (CHD) remains unknown. This prospective cohort study aims to investigate the role of 3DPHM in improving immediate knowledge gain and long-term knowledge retention on CHD among the medical students. Methods: Fifty-three second and third year medical students were assigned into two groups to compare their immediate knowledge acquisition and knowledge retention after an education session on anatomy and pathophysiology of CHD. During the 1.5 hour-long education session, both the control (n = 25) and study groups (n = 28) had access to identical teaching materials: digital 3D heart models, 2D diagrams, and medical images, except for 3DPHM which were only used in the study group. The immediate knowledge gain was assessed via an online quiz, whereas the long-term knowledge retention was assessed using another quiz in 6-weeks' time post-intervention. A survey was also conducted to evaluate the participants' learning experience. Results: There is no significant difference in the immediate knowledge acquisition and long-term knowledge retention between the groups (U = 272, p = 0.16 and r = -0.143, p = 0.15 respectively). Majority of the students (96% in control group and 85% in 3DPHM group) responded that the 3DPHM would have/had improved their learning experience. Despite that, there is no significant difference in the self-perceived knowledge improvement between the groups. Conclusions: This study concludes that the 3DPHM do not significantly improve both immediate knowledge acquisition and knowledge retention among the medical students. However, further research with larger sample size, as well as categorizing the type of questions in the quiz, is needed to better assess the role of 3DPHM in different educational components.

Understanding the anatomical features and generation of realistic three-dimensional (3D) visualization of congenital heart disease (CHD) is always challenging due to the complexity and wide spectrum of CHD. Emerging technologies, including 3D printing and mixed reality (MR), have the potential to overcome these limitations based on 2D and 3D reconstructions of the standard DICOM (Digital Imaging and Communications in Medicine) images. However, very little research has been conducted with regard to the clinical value of these two novel technologies in CHD. This study aims to investigate the usefulness and clinical value of MR and 3D printing in assisting diagnosis, medical education, pre-operative planning, and intraoperative guidance of CHD surgeries through evaluations from a group of cardiac specialists and physicians. Two cardiac computed tomography angiography scans that demonstrate CHD of different complexities (atrial septal defect and double outlet right ventricle) were selected and converted into 3D-printed heart models (3DPHM) and MR models. Thirty-four cardiac specialists and physicians were recruited. The results showed that the MR models were ranked as the best modality amongst the three, and were significantly better than DICOM images in demonstrating complex CHD lesions (mean difference (MD) = 0.76, p = 0.01), in enhancing depth perception (MD = 1.09, p = 0.00), in portraying spatial relationship between cardiac structures (MD = 1.15, p = 0.00), as a learning tool of the pathology (MD = 0.91, p = 0.00), and in facilitating pre-operative planning (MD = 0.87, p = 0.02). The 3DPHM were ranked as the best modality and significantly better than DICOM images in facilitating communication with patients (MD = 0.99, p = 0.00). In conclusion, both MR models and 3DPHM have their own strengths in different aspects, and they are superior to standard DICOM images in the visualization and management of CHD.