We aim to improve the residuum health of individuals suffering from lower-limb loss through ‘digital twin’ computational simulations for the creation of optimized 3D-printed prosthetic attachments. Our objective is to utilize 4D tracking data of various tissue interfaces as a primary input into the digital twin. Dynamic anatomical ultrasonography (DAU) is a novel technique in which synchronized individual transducers are positioned at known locations utilizing a 3D-printed holder. Pulse-echo ultrasound data are recorded and subsequently analyzed, providing plots of tissue interface depths versus recording time. For the scientific validation of the DAU technique, a bespoke 3D-printed phantom twin has been created incorporating replica compartments of soft-tissue interfaces and bone tissue of a healthy thigh. To demonstrate its utility, a preliminary experiment was performed in which the phantom twin was positioned within the DAU device and the replica bone manually traversed randomly; subsequent DAU analysis provided a plot of interface depth versus recording time.

Objective: The purpose of this study was to assess the impact of photopolymer resin type, arch location, and post-processing techniques on the trueness and precision of three-dimensionally printed (3DP) full-arch surgical implant guides. Methods: Stereolithography reference images of an upper and lower surgical guide with six drill holes from a full-mouth rehabilitation clinical case were used. The files were imported into the Asiga MAX UV slicing software (Asiga Composer) where build orientation, print resolution, and support structures were added. A digital light processing 3D printer (MAX UV, Asiga Max) was used for printing the samples. The samples assessed were printed using two different, manufacturer-validated resins, DentaGuide (n = 35) and DentaClear (n = 20). The samples were subdivided and measured based on the post-processing technique used: handwashing (n = 20), sonication (n = 25), a mix of handwashing and sonication (n = 10), and post-curing using 385 nm UVA light with nitrogen (n = 50) or without nitrogen (n = 5). The diameter of each drill hole per guide was measured using a coordinate measuring machine (Absolute Arm 7-Axis, Hexagon) and compared with the reference STL to calculate each sample’s trueness (median error) and precision (interquartile range). The Mann–Whitney and Kruskal–Wallis tests were used for statistical analyses. Results: All samples demonstrated a dimensional error of <70 µm. No significant differences (p > 0.05) were observed between upper and lower arches and between post-processing techniques using nitrogen, irrespective of the use of hand- or ultrasonic washing. In contrast, DentaClear resin was significantly (p < 0.001) more accurate with a trueness of 26 µm and precision of 12 to 34 µm versus the DentaGuide at −31 µm and −54 to −17 µm, respectively. The samples post-cured without nitrogen were significantly (p < 0.05) the least accurate of all surgical guides, with a trueness of −42 µm and precision of −68 to −39 µm. Conclusion: The resin type and nitrogen post-processing are parameters that can significantly impact the accuracy of surgical guides. The tolerance of 3DP surgical guides needs to account for the dimensional changes occurring during the manufacturing process to minimise implant positioning errors.

The objective of this study was to assess the effect of stacking on the dimensional and full-arch accuracy of 3D-printed models, utilising a standardised assessment methodology. A previously validated methodology involving a standard tessellation language image (STL) reference model, comprising seven spheres on a horseshoe base resembling a dental arch, was used. Six 3D-designed STL models were prepared, optimised, and stacked horizontally using 3D Sprint software. The stacking file was transferred to the NextDent 5100 printer to build the physical models. To assess accuracy, a coordinate measuring machine (CMM) measured the diameter of the spheres n=210, and twenty-one vectors extended between the centres of each of the seven spheres (n = 630). When compared to the reference model, significant differences were observed for dimensional (p = 0.006) and full-arch accuracy (p = 0.006) for all stacked models. Additionally, significant differences were observed between the stacked models for the dimensional accuracy between the posterior (p = 0.015), left posterior (p = 0.005) and anteroposterior (p = 0.002). The maximum contraction was observed in the fourth stacked model, which demonstrated the highest median deviation and least precision within the full-arch (MD = 666 μm, IQR = 55 μm), left posterior (MD = 136 μm, IQR = 12 μm), posterior (MD = 177 μm, IQR = 14 μm) and anteroposterior (MD = 179 μm, IQR = 16 μm) arch segments. In general, the anterior and left posterior arch segments recorded the highest contractions with a median deviation of 34 μm and 29 μm, and precision of 32 μm and 22 μm, respectively. Statistically significant differences were observed between the stacked models in terms of dimensional accuracy that were within clinically acceptable thresholds. The greatest contraction was noted in the fourth model, displaying the least full-arch accuracy compared to the other models. Stacked, additively manufactured, full arch models are a viable alternative for diagnostic, orthodontic, and single-unit prosthodontic applications. In contrast, caution should be exercised when utilising stacked models for full arch high accuracy prosthodontic applications. Further research is needed to assess the impact of additional variables including different printers and resins.