Three-dimensional (3D) printing is a rapidly evolving technology with several potential applications in the diagnosis and management of cardiac disease. Recently, 3D printing (i.e. rapid prototyping) derived from 3D transesophageal echocardiography (TEE) has become possible. Due to the multiple steps involved and the specific equipment required for each step, it might be difficult to start implementing echocardiography-derived 3D printing in a clinical setting. In this review, we provide an overview of this process, including its logistics and organization of tools and materials, 3D TEE image acquisition strategies, data export, format conversion, segmentation, and printing. Generation of patient-specific models of cardiac anatomy from echocardiographic data is a feasible, practical application of 3D printing technology.
Azad Mashari, Mario Montealegre-Gallegos, Ziyad Knio, Lu Yeh, Jelliffe Jeganathan, Robina Matyal, Kamal R Khabbaz and Feroze Mahmood
Robina Matyal, Faraz Mahmood, Ziyad Omar Knio, Stephanie B Jones, Lu Yeh, Rabia Amir, Ruma Bose and John D Mitchell
Various metrics have been used in curriculum-based transesophageal echocardiography (TEE) training programs to evaluate acquisition of proficiency. However, the quality of task completion, that is the final image quality, was subjectively evaluated in these studies. Ideally, the endpoint metric should be an objective comparison of the trainee-acquired image with a reference ideal image. Therefore, we developed a simulator-based methodology of preclinical verification of proficiency (VOP) in trainees by tracking objective evaluation of the final acquired images. We utilized geometric data from the simulator probes to compare image acquisition of anesthesia residents who participated in our structured longitudinal simulator-based TEE educational program vs ideal image planes determined from a panel of experts. Thirty-three participants completed the study (15 experts, 7 postgraduate year (PGY)-1 and 11 PGY-4). The results of our study demonstrated a significant difference in image capture success rates between learners and experts (χ 2 = 14.716, df = 2, P < 0.001) with the difference between learners (PGY-1 and PGY-4) not being statistically significant (χ 2 = 0, df = 1, P = 1.000). Therefore, our results suggest that novices (i.e. PGY-1 residents) are capable of attaining a level of proficiency comparable to those with modest training (i.e. PGY-4 residents) after completion of a simulation-based training curriculum. However, professionals with years of clinical training (i.e. attending physicians) exhibit a superior mastery of such skills. It is hence feasible to develop a simulator-based VOP program in performance of TEE for junior anesthesia residents.