Introduction

In the last decade, there has been an increasing interest in the field of three-dimensional (3D) printing for manufacturing of models, which are able to reproduce complex anomalies of the heart and great vessels [1–18]. Congenital heart disease (CHD), with its diverse and often complex pathology, the need for complete representation of anatomy and personalized treatment approaches, [1, 2, 10, 18] represent an ideal field to test the potential, accuracy, and clinical effectiveness of this technology. Management of CHD is challenging due to the broad spectrum of conditions and high variability between individual patients. Optimal surgical outcome is related to a thorough understanding of the complex spatial relationships between anatomical structures in order to avoid unexpected findings at surgical repair, and thereby reduce operative time and mortality. Visualization using conventional 3D imaging techniques is limited due to presentation on a flat screen, which may not allow full comprehension of complex intracardiac anatomy. The purpose of this paper is to provide an overview of 3D printing in CHD, focusing on strengths, weaknesses and technical considerations.

Strengths of 3D printed models

Multiple studies have demonstrated the feasibility and accuracy of 3D printed models for the reconstruction of complex cardiac [2] and extra-cardiac anatomy. These include visualization of aortic arch anomalies [11], pulmonary branches [7], and major aorto-pulmonary collaterals [4]. Printing of 3D models was feasible at all ages, with different imaging techniques including CT, MRI and more recently 3-D echocardiography (Figs. 1, 2). Advantages of 3D models in the understanding of complex anatomy and in the planning of surgical and percutaneous interventions have been highlighted.

Fig. 1
figure 1

The 3D printing process. a Radiological image. b Segmentation. c 3D volume render. d Computer aided design. e 3D printing by fused deposition modeling. f Final 3D printed model

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Fig. 2
figure 2

3D printed model of the myocardium (grey) and blood pool (orange)

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The diagnostic accuracy of 3D models has been evaluated in different ways. Most of the current work [3, 5, 10–12] describes similarities of 3D models with cardiac anatomy, and the satisfaction of the surgeon or interventionist. Others have used [2, 4, 7, 18] a more systematic approach and explored correlations of the 3D reconstructions with anatomical details visualized at MRI, angiography or surgery [4, 7, 18]. The 3D printed models were able to correctly reproduce anatomical details within a few millimetres. For example, Schievano et al. [7] found very limited operator error in data reconstruction (3.4 %, corresponding to errors of ±0.75 mm) and excellent correlations between the 3D images and printed models. Similar accuracy was shown by Olivieri et al. for 3D printed models of ventricular septal defects [2]. Others have [4] demonstrated that the models could accurately reproduce 93–96 % of major aorto-pulmonary collaterals (MAPCAs) identified during surgery or angiography. Valverde et al. [18] recently used a 3D printed model for simulation of endovascular stenting of a hypoplastic arch, with good agreement shown between aortic luminal diameters of the model and those obtained by MRI and angiography, assisting with pre-procedural device selection. These models also have excellent potential for teaching purposes (Table 1). Another interesting area is application for doctor-patient communication, as it has been shown to improve overall patient satisfaction.

Table 1 Overview of major published studies on 3D printing application in CHD
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Limitations of 3D printed models

At the present time, there are limitations to a widespread use of 3D printing in the management of patients with CHD. Major issues are the lack of standardized approaches, long processing times, and high costs. The current model is a rigid or flexible ‘static’ reproduction of cardiac anatomy, and does not allow reproduction of physiologic changes occurring during the cardiac cycles. To overcome this limitation, ‘dynamic’ models have been proposed [20].

Because this is a relatively new and experimental field, there is lack of standardization in the procedures and materials employed. Imaging techniques and acquisition modalities within each technique varied. The segmentation processes were also greatly different due to differences in software and automation. Furthermore, there were differences in printing related material and printers, producing changes in the physical properties of the models.

Lack of standardization in any process could introduce bias, as well as result in operator dependency. With regard to 3D printing, operator dependency is relevant in all steps from image acquisition and selection to the choice of areas to be segmented. Selection of systole or diastole for segmentation remains arbitrary, which may introduce bias in the final model. For instance, a pulmonary artery branch segmented in diastole is significantly smaller than in systole. Only one report has thus far indicated the phase of cardiac cycle chosen [2]. The influence of other confounding variables including image quality, differences among imaging techniques, and operator variability in image acquisition have never been investigated. Studies using a multi-modality approach of CT, MR and 3D echocardiography for the printing of 3D models are needed. Finally, the pediatric age poses additional technical issues for 3D imaging related to high heart rates and small cardiac structures.

Technical considerations

Image acquisition

The choice of the imaging technique primarily depends on institutional preferences and availability. Most work in this field used CT [4, 6, 8, 11, 13, 15, 16] and MRI [6–8, 10, 17]. Both modalities have been used separately [4, 5, 10, 11, 13, 15] or interchangeably [6, 8, 16, 17] within the same study protocol. Issues related to image spatial resolution and motion artefacts in CT and MRI might hamper segmentation of thin intra-cardiac structures such as valves and papillary muscles [7]. One study [2] used data from 3D echocardiography. Table 2 outlines protocols of CT/MRI acquisition from published studies [7, 10, 13]. Slice thicknesses of images acquired were consistent, varying from 0.625 [4] to 2 mm [3, 6]. General anaesthesia [4] or sedation [13] was used in some studies, while others performed examinations in awake patients [7, 10]. MRI acquisitions employed free breathing or [10] breath holding [7]. For CT, electrocardiogram gated acquisition was reported in one study [10]. In our opinion, gated-CT might offer the best image spatial resolution, however in children MRI based sequences may be preferred due to the avoidance of ionising radiation. Diastolic acquisition could be advantageous for evaluation of cardiac chamber size and intra-cardiac structures such as ventricular septal defects. Systolic acquisition is preferred for evaluation of vascular structures as diameters may be larger.

Table 2 MRI/CT image acquisition for the building of 3D models
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Translation of DICOM files into printable formats

A key step in the process is the conversion of DICOM images files into printable formats. Software for conversion (example Mimics, Materialize, The Netherlands) are commercially available, but expensive. A version of the Osirix software (Pixmeo, Geneva, Switzerland) is available free of cost, but the free version has limitations compared to the standard commercial product. Some institutions have custom-built software, for example, AYRA [21]. Semi-automated segmentation methods are commonly used [2, 13, 22] while manual [7, 10], or a combination of manual, semi-automated and automated segmentation options are available [2]. An in-depth review of the segmentation methodologies is provided in recent publications [22, 23].

The printing process

Table 3 shows the variety of printers and materials that have been used. The available materials include solid acrylic or plastic [4], urethane [5, 6, 12–14], or thermoplastic resin [7]. The choice of material could have an impact on applications. Rigid models provide a static representation of anatomy, while flexible models may be more suitable for surgical simulation [13]. Cold gas has been used for sterilization of models for intra-operative use in the operating room [4, 14].

Table 3 Segmentation software, printers and materials for 3D printing
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Cost and times

Costs are related to [1] the software used to translate DICOM images, and [2] the process of printing itself. The combined cost has been estimated from 200 to 440 Euros [13, 14], up to 870 Euros [10]. Process time represents a limitation currently, because manual segmentation may take hours [7], and the entire process may take a few days [13]. Rapid segmentation process (<30 min) has been described [10]. A more widespread use of 3D models in multiple medical settings [24, 25] may help decrease costs related to software, printers, and materials. It may also implement more rapid semi-automated or automated processes [10]. The use of 3D models could also potentially reduce costs by diminishing operative times and improving outcomes [26, 27]. Superior procedural planning could result in savings derived from reduced interventional time, radiation time and optimal device selection. However, true cost-analysis assessment of 3-D models has not yet been performed [26, 27].

Conclusion

Recent technology allows good quality three-dimensional printing of models for CHD in all ages. These models could be used for planning of surgical or percutaneous management of CHD with satisfactory results. At the present time, experience with these models in CHD remain limited to case reports or small studies. More investigations into assessment of outcomes and cost-effectiveness of 3D printed models in endovascular and surgical management of CHD are warranted.