BackgroundPreoperative anxiety in cardiac surgery can lead to prolonged hospital stays and negative postoperative outcomes. An improved patient education using 3D models may reduce preoperative anxiety and risks associated with it.MethodsPatient education was performed with standardized paper-based methods (n = 34), 3D-printed models (n = 34) or virtual reality models (n = 31). Anxiety and procedural understanding were evaluated using questionnaires prior to and after the patient education. Additionally, time spent for the education and overall quality were evaluated among further basic characteristics (age, gender, medical expertise, previous non-cardiac surgery and previously informed patients). Included surgeries were coronary artery bypass graft, surgical aortic valve replacement and thoracic aortic aneurysm surgery.ResultsA significant reduction in anxiety measured by Visual Analog Scale was achieved after patient education with virtual reality models (5.00 to 4.32, Δ-0.68, p < 0.001). Procedural knowledge significantly increased for every group after the patient education while the visualization and satisfaction were best rated for patient education with virtual reality. Patients rated the quality of the patient education using both visualization methods individually [3D and virtual reality (VR) models] higher compared to the control group of conventional paper-sheets (control paper-sheets: 86.32 ± 11.89%, 3D: 94.12 ± 9.25%, p < 0.0095, VR: 92.90 ± 11.01%, p < 0.0412).ConclusionRoutine patient education with additional 3D models can significantly improve the patients' satisfaction and reduce subjective preoperative anxiety effectively.
Background 3D printed models of pediatric hearts with congenital heart disease have been proven helpful in simulation training of diagnostic and interventional catheterization. However, anatomically accurate 3D printed models are traditionally based on real scans of clinical patients requiring specific imaging techniques, i.e., CT or MRI. In small children both imaging technologies are rare as minimization of radiation and sedation is key. 3D sonography does not (yet) allow adequate imaging of the entire heart for 3D printing. Therefore, an alternative solution to create variant 3D printed heart models for teaching and hands-on training has been established. Methods In this study different methods utilizing image processing and computer aided design software have been established to overcome this shortage and to allow unlimited variations of 3D heart models based on single patient scans. Patient-specific models based on a CT or MRI image stack were digitally modified to alter the original shape and structure of the heart. Thereby, 3D hearts showing various pathologies were created. Training models were adapted to training level and aims of hands-on workshops, particularly for interventional cardiology. Results By changing the shape and structure of the original anatomy, various training models were created of which four examples are presented in this paper: 1. Design of perimembranous and muscular ventricular septal defect on a heart model with patent ductus arteriosus, 2. Series of heart models with atrial septal defect showing the long-term hemodynamic effect of the congenital heart defect on the right atrial and ventricular wall, 3. Implementation of simplified heart valves and addition of the myocardium to a right heart model with pulmonary valve stenosis, 4. Integration of a constructed 3D model of the aortic valve into a pulsatile left heart model with coarctation of the aorta. All presented models have been successfully utilized and evaluated in teaching or hands-on training courses. Conclusions It has been demonstrated that non-patient-specific anatomical variants can be created by modifying existing patient-specific 3D heart models. This way, a range of pathologies can be modeled based on a single CT or MRI dataset. Benefits of designed 3D models for education and training purposes have been successfully applied in pediatric cardiology but can potentially be transferred to simulation training in other medical fields as well.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.