ABSTRACT
The treatment of osseous defects around teeth is a fundamental concern within the field of periodontology. Over the years, the method of grafting has been employed to treat bone defects, underscoring the necessity for custom-designed scaffolds that precisely match the anatomical intricacies of the bone cavity to be filled, preventing the formation of gaps that could allow the regeneration of soft tissues. In order to create such a patient-specific scaffold (bone graft), it is imperative to have a highly detailed 3D representation of the bone defect, so that the resulting scaffold aligns with the ideal anatomical characteristics of the bone defect. In this context, this article implements a workflow for designing 3D models out of patient-specific tissue defects, fabricated as scaffolds with 3D-printing technology and bioabsorbable materials, for the personalized treatment of periodontitis. The workflow is based on 3D modeling of the hard tissues around the periodontal defect (alveolar bone and teeth), scanned from patients with periodontitis. Specifically, cone beam computed tomography (CBCT) data were acquired from patients and were used for the reconstruction of the 3D model of the periodontal defect. The final step encompasses the 3D printing of these scaffolds, employing Fused Deposition Modeling (FDM) technology and 3D-bioprinting, with the aim of verifying the design accuracy of the developed methodοlogy. Unlike most existing 3D-printed scaffolds reported in the literature, which are either pre-designed or have a standard structure, this method leads to the creation of highly detailed patient-specific grafts. Greater accuracy and resolution in the macroarchitecture of the scaffolds were achieved during FDM printing compared to bioprinting, with the standard FDM printing profile identified as more suitable in terms of both time and precision. It is easy to follow and has been successfully employed to create 3D models of periodontal defects and 3D-printed scaffolds for three cases of patients, proving its applicability and efficiency in designing and fabricating personalized 3D-printed bone grafts using CBCT data.
ABSTRACT
In the context of web augmented reality (AR), 3D rendering that maintains visual quality and frame rate requirements remains a challenge. The lack of a dedicated and efficient 3D format often results in the degraded visual quality of the original data and compromises the user experience. This paper examines the integration of web-streamable view-dependent representations of large-sized and high-resolution 3D models in web AR applications. The developed cross-platform prototype exploits the batched multi-resolution structures of the Nexus.js library as a dedicated lightweight web AR format and tests it against common formats and compression techniques. Built with AR.js and Three.js open-source libraries, it allows the overlay of the multi-resolution models by interactively adjusting the position, rotation and scale parameters. The proposed method includes real-time view-dependent rendering, geometric instancing and 3D pose regression for two types of AR: natural feature tracking (NFT) and location-based positioning for large and textured 3D overlays. The prototype achieves up to a 46% speedup in rendering time compared to optimized glTF models, while a 34 M vertices 3D model is visible in less than 4 s without degraded visual quality in slow 3D networks. The evaluation under various scenes and devices offers insights into how a multi-resolution scheme can be adopted in web AR for high-quality visualization and real-time performance.
