Feasibility and accuracy of printed models of complex cardiac defects in small infants from cardiac computed tomography

Evaluation of the Efficacy and Accuracy of Super-Flexible Three-Dimensional Heart Models of Congenital Heart Disease Made via Stereolithography Printing and Vacuum Casting: A Multicenter Clinical Trial

Three-dimensional (3D) printing is an advanced technology for accurately understanding anatomy and supporting the successful surgical management of complex congenital heart disease (CHD). We aimed to evaluate whether our super-flexible 3D heart models could facilitate preoperative decision-making and surgical simulation for complex CHD. The super-flexible heart models were fabricated by stereolithography 3D printing of the internal and external contours of the heart from cardiac computed tomography (CT) data, followed by vacuum casting with a polyurethane material similar in elasticity to a child's heart. Nineteen pediatric patients with complex CHD were enrolled (median age, 10 months). The primary endpoint was defined as the percentage of patients rated as "essential" on the surgeons' postoperative 5-point Likert scale. The accuracy of the models was validated by a non-destructive method using industrial CT. The super-flexible heart models allowed detailed anatomical diagnosis and simulated surgery with incisions and sutures. Thirteen patients (68.4%) were classified as "essential" by the primary surgeons after surgery, with a 95% confidence interval of 43.4-87.4%, meeting the primary endpoint. The product error within 90% of the total external and internal surfaces was 0.54 ± 0.21 mm. The super-flexible 3D heart models are accurate, reliable, and useful tools to assist surgeons in decision-making and allow for preoperative simulation in CHD.

Impact of 3D-printed models in meetings with parents of children undergoing interventional cardiac catheterisation

Background

Paediatric interventional catheterisation has consistently improved in recent decades, with often highly successful outcomes. However, progress is still required in terms of the information delivered to parents and how parental anxiety is managed.

Aim

To investigate the impact of cardiac printed models on improving parental understanding and alleviating anxiety before interventional catheterisation.

Methods

The parents of children undergoing interventional cardiac catheterisation were prospectively enrolled in the study. A questionnaire highlighting knowledge and understanding of the condition and cardiac catheterisation per se was scored on a scale of 1-30. The State-Trait Anxiety Inventory (STAI), which generates current anxiety scores, was also used before and after the pre-catheterisation meeting. The "printing group" received an explanation of catheterisation using the device and a three-dimensional (3D) model, while the "control group" received an explanation using only the device and a manual drawing.

Results

In total, 76 parents of 50 children were randomly assigned to a "control group" (n = 38) or "printing group" (n = 38). The groups were comparable at baseline. The level of understanding and knowledge improved after the "control group" and "printing group" meetings (+5.5±0.8 and +10.2±0.8; p < 0.0001 and p < 0.0001, respectively). A greater improvement was documented in the "printing group" compared to the "control group" (p < 0.0001). The STAI score also improved after the explanation was given to both groups (-1.8±0.6 and -5.6±1.0; p < 0.0001 and p < 0.0001). The greatest improvement was noted in the "printing group" (p = 0.0025). Most of the parents (35/38 from the "printing group") found the models to be extremely useful.

Conclusion

3D-printed models improve parental knowledge and understanding of paediatric cardiac catheterisation, thereby reducing anxiety levels.

HEARTBEAT4D: An Open-source Toolbox for Turning 4D Cardiac CT into VR/AR

Four-dimensional data sets are increasingly common in MRI and CT. While clinical visualization often focuses on individual temporal phases capturing the tissue(s) of interest, it may be possible to gain additional insight through exploring animated 3D reconstructions of physiological motion made possible by augmented or virtual reality representations of 4D patient imaging. Cardiac CT acquisitions can provide sufficient spatial resolution and temporal data to support advanced visualization, however, there are no open-source tools readily available to facilitate the transformation from raw medical images to dynamic and interactive augmented or virtual reality representations. To address this gap, we developed a workflow using free and open-source tools to process 4D cardiac CT imaging starting from raw DICOM data and ending with dynamic AR representations viewable on a phone, tablet, or computer. In addition to assembling the workflow using existing platforms (3D Slicer and Unity), we also contribute two new features: 1. custom software which can propagate a segmentation created for one cardiac phase to all others and export to surface files in a fully automated fashion, and 2. a user interface and linked code for the animation and interactive review of the surfaces in augmented reality. Validation of the surface-based areas demonstrated excellent correlation with radiologists' image-based areas (R > 0.99). While our tools were developed specifically for 4D cardiac CT, the open framework will allow it to serve as a blueprint for similar applications applied to 4D imaging of other tissues and using other modalities. We anticipate this and related workflows will be useful both clinically and for educational purposes.