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.
Daniel P Walsh, Kadhiresan R Murugappan, Achikam Oren-Grinberg, Vanessa T Wong, John D Mitchell and Robina Matyal
Interactive online learning tools have revolutionized graduate medical education and can impart echocardiographic image interpretive skills. We created self-paced, interactive online training modules using a repository of echocardiography videos of normal and various degrees of abnormal left ventricles. In this study, we tested the feasibility of this learning tool. Thirteen anesthesia interns took a pre-test and then had 3 weeks to complete the training modules on their own time before taking a post-test. The average score on the post-test (74.6% ± 11.08%) was higher than the average score on the pre-test (57.7% ± 9.27%) (P < 0.001). Scores did not differ between extreme function (severe dysfunction or hyperdynamic function) and non-extreme function (normal function or mild or moderate dysfunction) questions on both the pre-test (P = 0.278) and post-test (P = 0.093). The interns scored higher on the post-test than the pre-test on both extreme (P = 0.0062) and non-extreme (P = 0.0083) questions. After using an online educational tool that allowed learning on their own time and pace, trainees improved their ability to correctly categorize left ventricular systolic function. Left ventricular systolic function is often a key echocardiographic question that can be difficult to master. The promising performance of this educational resource may lead to more time- and cost-effective methods for improving diagnostic accuracy among learners.
Andaleeb A Ahmed, Robina Matyal, Feroze Mahmood, Ruby Feng, Graham B Berry, Scott Gilleland and Kamal R Khabbaz
Due to its circular shape, the area of the proximal left ventricular tract (PLVOT) adjacent to aortic valve can be derived from a single linear diameter. This is also the location of flow acceleration (FA) during systole, and pulse wave Doppler (PWD) sample volume in the PLVOT can lead to overestimation of velocity (V1) and the aortic valve area (AVA). Therefore, it is recommended to derive V1 from a region of laminar flow in the elliptical shaped distal LVOT (away from the annulus). Besides being inconsistent with the assumptions of continuity equation (CE), spatial difference in the location of flow and area measurement can result in inaccurate AVA calculation. We evaluated the impact of FA in the PLVOT on the accuracy of AVA by continuity equation (CE) in patients with aortic stenosis (AS).
CE-based AVA calculations were performed in patients with AS once with PWD-derived velocity time integral (VTI) in the distal LVOT (VTILVOT) and then in the PLVOT to obtain a FA velocity profile (FA-VTILVOT) for each patient. A paired sample t-test (P < 0.05) was conducted to compare the impact of FA-VTILVOT and VTILVOT on the calculation of AVA.
There were 46 patients in the study. There was a 30.3% increase in the peak FA-VTILVOT as compared to the peak VTILVOT and AVA obtained by FA-VTILVOT was 29.1% higher than obtained by VTILVOT.
Accuracy of AVA can be significantly impacted by FA in the PLVOT. LVOT area should be measured with 3D imaging in the distal LVOT.