Introduction and Objective: In recent years, 3D (three-dimensional) modeling has been added to traditional and effective diagnostic methods such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and Echocardiography. The purpose of this study is to determine the effectiveness of models created from patients' own radiological images using 3D printing technology in the clinical setting to simulate surgery in the preoperative period and provide preoperative parental education to improve family quality of life and positively influence patient outcomes.

Methods: The study is a two-group pretest-posttest randomized controlled study. The children who come to the outpatient clinic examination in a private hospital and who are subjected to Computed Tomography (CT) examination for diagnostic procedures will be modeled in the experimental group, pre-tests will be applied, and the model will be 3D printed after it is approved by the radiologist who is among the researchers. The sample size is 15 experimental group and 15 control group. After the radiologist's approval, surgical simulation and preoperative education will be applied to the experimental group. The control group will receive the same parent education as the standard model. Both groups will complete the Sociodemographic Information Form, Surgical Simulation Evaluation Form - Part I, and Pediatric Quality of Life Inventory (PedsQL) Family Impacts Module one week prior to hospitalization. Surgical simulation and preoperative education will be completed on the same day. On postoperative day 0, only the Surgical Simulation Evaluation Form - Part II will be applied and on postoperative day 15, the Surgical Simulation Evaluation Form - Part II and the Pediatric Quality of Life Inventory (PedsQL) Family Impacts Module will be applied to both groups as a posttest.

Pilot Study and Results: Modeling and 3D printing studies were conducted to carry out the study. A total of four diagnosed and treated patients were retrospectively analyzed. An intracardiac anomaly was detected in the patient data taken for the first model. It was decided to model the extracardiac structures since the inside of the heart was filled with blood, and the blood could not be ruled out as a solid structure. Finally, aortic coarctation was modeled clearly from the images taken and completed.

The most common congenital malformation of childhood is congenital heart disease (CHD). The degree to which the defect deviates from normal anatomy determines the severity of symptoms. Globally, between 0.8% and 1.2% of all live births are affected by CHD. While it occurs in 1% of 40,000 live births in the US, Asian countries have been reported to have the highest rate at 9.3 per 1000 live births. In Turkey, the rate has been reported to be between 0.6 and 1% per 100 live births. Between 25 % and 50 % of the children born with CHD have defects that will require open heart surgery. Reliable diagnostic methods provide much better treatment options, leading to a significant reduction in mortality. In addition to imaging methods such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and Echocardiography (ECHO), 3D modeling and printing technologies have been added to these methods in recent years. There are differences and benefits among the different imaging methods. The most recent and rapidly developing method among them is 3D printing technologies.

It is predicted that 3D cardiac models obtained from patients' radiological images can be used for various purposes. It is stated that beneficial results can be obtained for multiple purposes, from planning and simulation before the definitive surgical procedure to patient-specific preoperative education. There are several techniques for modeling organs using 3D printing technology, which has developed rapidly in recent years. For the heart, two types of cardiac modeling are performed. These are filled solid models (blood pool) and hollow models. The hollow models are obtained from signals sent in a way that limits the perimeter of the area where the blood pool is located. These models are printed as a cross-section and show the intracardiac structure. However, technically, the peak heart rate of children is higher than that of adults, so the images may lose clarity, require more time and effort, and may not be as useful. Solid models have filled models of the atria and ventricles. They are typically modeled and printed from contrast-enhanced CT or MR images. Noncardiac structures can be added to these models (e.g., aorta, pulmonary artery, extracardiac vessels, trachea, and esophagus) with the goal of delineating large vessel abnormalities in the model. Extracardiac structures are very guiding in surgical simulation with easier and faster modeling than intracardiac structures. In particular, recurrent pulmonary artery stenosis and aortic coarctation can be successfully treated, and positive outcomes can be achieved with fast and patient-specific models. The operating time of surgically simulated patients is reduced, and procedures can be completed with less cost and fewer complications.

Targeted patient outcomes can be achieved by managing a multidisciplinary team that includes the patient and family and by using surgical simulation. In life-threatening diseases such as CHD, diagnosis, treatment, and surgical planning are long-term processes. This process causes serious psychological distress in parents, such as post-traumatic stress disorder. Parental/caregiver stress increases and the family's quality of life deteriorates, especially when the surgical procedure and interventions are not clearly understood. This situation negatively affects the postoperative recovery process of patients. A surgical procedure performed with good technique followed by poor postoperative management renders many interventions ineffective. Understanding the severity of the disease from the perspective of the parents can improve both the health-related quality of life of the child and the quality of life of the family, leading to more positive patient outcomes. Patient-specific modeling using 3D printing technology with images obtained through traditional methods is believed to eliminate all of these issues.

Inclusion Criteria:

• The participant has a congenital heart disease between the ages of 0-18 years, the congenital defect has extracardiac structure malformations (This is because the modeling is to be done before the operation is done in a shorter time, and it is desired to be trained for preoperative education). Hollow modeling requires more detailed technique and time (Bhatla et al., 2017). In addition, the difficulty of 3D printing the hollow model made in the pilot study was also effective in this decision),
• Being a candidate for elective surgery,
• Having a contrast-enhanced CT image taken during and before the patient's routine diagnostic procedure outside the scope of the study,
• Having at least 15 days between the imaging and the surgical procedure plan,
• The parents/legal guardians who gave permission to participate in the study were the inclusion criteria of the study.

Exclusion Criteria:

• Patients who do not require CT for diagnosis or treatment (no patient will undergo CT imaging within the scope of the study unless necessary for this study only),
• Emergency surgical procedures, heart defects involving intracardiac structures (Atrial Septal Defect, Ventricular Septal Defect, Tetralogy of Fallot),
• Additional anomalies/syndromes,
• Chronic diseases (such as neurodevelopmental disorders, bleeding disorders, asthma, or Down syndrome),
• History of cardiac arrest, contrast agent reflection in the images,
• Image quality preventing modeling.

Researchers will ensure that all data are accurately and completely coded and consistently entered into the statistical analysis software. The researchers will keep all original documents including medical records, questionnaires, informed consent forms, and other relevant records obtained during the study and will keep them confidential. Data will be retained for five years after the completion of the study.