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Tredway et al. Mini-invasive Surg 2020;4:78  I  http://dx.doi.org/10.20517/2574-1225.2020.77                                  Page 7 of 11


























































               Figure 4. Echocardiography-based 3D printing of patient-specific models. Segmentation of LAA (shaded area) from 3D TEE data (A, D)
               is turned into a digital object (B, E), and printed using tissue-mimicking material (C, F). The major and minor ostial diameters and depth
               of the LAA are measured. Arrows denote pulmonary vein ridge; stars denote appendicular trabeculations. Closure devices are then sized
               and placed within the 3D model (G-I), and device compression and (H) protrusion are measured using a digital caliper. Device stability
               is assessed using the tug-test (I). Device placement visualized on TEE (J-L), and color Doppler assessment showing no peri-device leak
               (M). Reprinted with permission from Fan et al. [20] . LAA: left atrial appendage; TEE: trans-esophageal echocardiogram; CT: computed
               tomography; 3D: three-dimensional


               LIMITATIONS
               There are numerous limitations to creating and using 3D printed models that have prevented widespread
                                       [8]
               adoption in most programs . A major consideration is that the creation of 3D models is a time-intensive
               process requiring familiarity with segmentation and computer automated design software, as well as an in-
                                                     [5]
               depth understanding of cardiac morphology . There is no standardized approach to creating these models,
               which can ultimately result in a wide variation in the quality of models produced . This was evidenced
                                                                                      [7]
                                [24]
               by Burkhardt et al.  in an article evaluating the inter-operator variability in modeling the RVOT based
               on the threshold chosen for the initial segmentation. Another limitation is that rigid, or even flexible, 3D
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