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.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
OTHER
Masking
SINGLE
Enrollment
30
The first step in the modeling process is masking. For this study, the average minimum value for masking ventricles and large vessels was set between 80 and 200 HU (Brüning et al., 2022). Threshold values of min 216 HU - max 1502 HU are used. At these HU values, the blood in the heart and great vessels is masked and the outline of the heart is revealed. Lowering the minimum HU value is necessary to make the heart walls more visible. However, this results in masking unwanted soft tissues other than the heart, such as muscle and fat. The masked unnecessary surrounding tissues are removed first with the cropping mask and then manually by marking along the contours of the heart and great vessels. Thus, a model containing only the heart and the desired large vessels will be created and cleaned from the surrounding tissues. With this mask, 3D reconstruction will be performed, and the model will be ready for printing.
Yeditepe University
Istanbul, Turkey (Türkiye)
Pretest-Family Impacts Module of the Pediatric Quality of Life Inventory PedsQL
The Turkish validity and reliability study of this scale, first developed by Varni et al. in 2004, was conducted and published by Gürkan et al. in 2019 (Gürkan, Bahar, Çapık, Aydoğdu, \& Beşer, 2020; Varni, Sherman, Burwinkle, Dickinson, \& Dixon, 2004). The data on the sub-dimensions and Cronbach alpha values of this scale, which has 8 sub-dimensions in total, are as follows; physical (0.85), emotional (0.83), social (0.82), cognitive (0.86), communication (0.51), anxiety (0.79) activities of daily living (0.89), family relationships (0.95). A total score of 0.92 was reported. In addition, Cronbach alpha values for all subscales were also included in the original study. The scale does not have a cut-off point. A high score indicates a good family quality of life functioning, while a low score indicates a negative family quality of life. Within the scope of this study, a comparison between mean scores will be made.
Time frame: 1 week prior to surgery
Posttest-Family Impacts Module of the Pediatric Quality of Life Inventory PedsQL
The Turkish validity and reliability study of this scale, first developed by Varni et al. in 2004, was conducted and published by Gürkan et al. in 2019 (Gürkan, Bahar, Çapık, Aydoğdu, \& Beşer, 2020; Varni, Sherman, Burwinkle, Dickinson, \& Dixon, 2004). The data on the sub-dimensions and Cronbach alpha values of this scale, which has 8 sub-dimensions in total, are as follows; physical (0.85), emotional (0.83), social (0.82), cognitive (0.86), communication (0.51), anxiety (0.79) activities of daily living (0.89), family relationships (0.95). A total score of 0.92 was reported. In addition, Cronbach alpha values for all subscales were also included in the original study. The scale does not have a cut-off point. A high score indicates a good family quality of life functioning, while a low score indicates a negative family quality of life. Within the scope of this study, a comparison between mean scores will be made.
Time frame: 15 days later to surgery
Posttest-Surgical Simulation Questionnaire Part II
It has 7 questions prepared according the literature. Effects of 3D modeling on surgical complications, duration of the operation, duration of the hospitalization, duration of the intensive care unit, need of recurrent surgery, Unusual complications (except for pain, cardiopulmonary resuscitation, need for ECMO (Extracorporeal Membrane Oxygenation), Seizure, rhythm changes, etc.)
Time frame: First post operative day
Posttest-Surgical Simulation Questionnaire Part II
It has 7 questions prepared according the literature. Effects of 3D modeling on surgical complications, duration of the operation, duration of the hospitalization, duration of the intensive care unit, need of recurrent surgery, Unusual complications (except for pain, cardiopulmonary resuscitation, need for ECMO (Extracorporeal Membrane Oxygenation), Seizure, rhythm changes, etc.)
Time frame: 15 days later to surgery
Pretest Surgical Simulation Questionnaire Part I
Surgeon's professional experience and age, opinions about 3D Heart Modeling (surgical simulation evaluations such as effectiveness on techniques of the operations, opinions about strong and week sides of 3D modeling)
Time frame: 1 week prior to surgery
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