Usage of 3D models of tetralogy of Fallot for medical education: impact on learning congenital heart disease

Abstract

BackgroundCongenital heart disease (CHD) is the most common human birth defect, and clinicians need to understand the anatomy to effectively care for patients with CHD. However, standard two-dimensional (2D) display methods do not adequately carry the critical spatial information to reflect CHD anatomy. Three-dimensional (3D) models may be useful in improving the understanding of CHD, without requiring a mastery of cardiac imaging. The study aimed to evaluate the impact of 3D models on how pediatric residents understand and learn about tetralogy of Fallot following a teaching session.MethodsPediatric residents rotating through an inpatient Cardiology rotation were recruited. The sessions were randomized into using either conventional 2D drawings of tetralogy of Fallot or physical 3D models printed from 3D cardiac imaging data sets (cardiac MR, CT, and 3D echocardiogram). Knowledge acquisition was measured by comparing pre-session and post-session knowledge test scores. Learner satisfaction and self-efficacy ratings were measured with questionnaires filled out by the residents after the teaching sessions. Comparisons between the test scores, learner satisfaction and self-efficacy questionnaires for the two groups were assessed with paired t-test.ResultsThirty-five pediatric residents enrolled into the study, with no significant differences in background characteristics, including previous clinical exposure to tetralogy of Fallot. The 2D image group (n = 17) and 3D model group (n = 18) demonstrated similar knowledge acquisition in post-test scores. Residents who were taught with 3D models gave a higher composite learner satisfaction scores (P = 0.03). The 3D model group also had higher self-efficacy aggregate scores, but the difference was not statistically significant (P = 0.39).ConclusionPhysical 3D models enhance resident education around the topic of tetralogy of Fallot by improving learner satisfaction. Future studies should examine the impact of models on teaching CHD that are more complex and elaborate.

Three‐dimensional printing in congenital heart disease: A systematic review

“…Three‐dimensional printed heart models are also shown to be a novel teaching approach in medical education for clinicians, cardiac nurses, and students according to this reported review . Until now, teaching of CHD has been based on pictorial images, diagrams, 2D echocardiography images and cardiac specimens.…”

“…Of the 28 articles, 17 of them (61%) were case reports and case series, based on number of cases ranging from 1 to 12 cases with different CHD and cardiovascular diseases. Ten of them (36%) were cross‐sectional studies, mainly surveying the healthcare professionals, parents, parents of patients and medical students; and 3 of which were randomised controlled trials.…”

“…Due to these limitations, 3D printed CHD models were used in teaching and training of medical staff and medical students. Several studies reported the use of 3D printed models has improved acquisition of pathological knowledge in paediatric residents and students as well as residents’ confidence level when managing patients with CHD . Additionally, positive results were also reported when incorporating 3D printed models in medical staff training …”

“…Image segmentation for 3D printing in CHD is exceptionally challenging and time‐consuming . The segmentation process involves isolating the congenitally malformed heart from its surrounding soft tissues using thresholding technique .…”

Low-field magnetic resonance imaging for 3D volume rendering of canine stifle joint pathologies: a case report

“…High-field MRI data were also used in a stereo 3D reconstruction of the anatomical structures of a normal human ankle and knee, which supported accurate evaluations of tendons, muscles, bones and cartilages (Anastasi et al 2007;Anastasi et al 2009). Three-dimensional reconstruction has evolved into 3D geometrical modelling as an accurate method for simulating and planning or training for computer-aided surgery (Krupa et al 2007;Loke et al 2017;Oshiro and Ohkohchi 2017). For a better understanding or for analysis, the obtained model could be rotated, and the superimposed objects could be switched on and off and cropped.…”