Clinical Applications of Mixed Reality and 3D Printing in Congenital Heart Disease - Lau, Ivan; Gupta, A.; Ihdayhid, Abdul; Sun, Zhonghua (MDPI AG, 2022)
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.