METHODS: An online REDCap questionnaire was circulated to surgeons in the Asia-Pacific region during the period of July 2019 to September 2019 to inquire about various components of nonoperative treatment for AIS. Aspects under study included access to screening, when MRIs were obtained, quality-of-life assessments used, role of scoliosis-specific exercises, bracing criteria, type of brace used, maturity parameters used, brace wear regimen, follow-up criteria, and how braces were weaned. Comparisons were made between middle-high income and low-income countries, and experience with nonoperative treatment.
RESULTS: A total of 103 responses were collected. About half (52.4%) of the responders had scoliosis screening programs and were particularly situated in middle-high income countries. Up to 34% obtained MRIs for all cases, while most would obtain MRIs for neurological problems. The brace criteria were highly variable and was usually based on menarche status (74.7%), age (59%), and Risser staging (92.8%). Up to 52.4% of surgeons elected to brace patients with large curves before offering surgery. Only 28% of responders utilized CAD-CAM techniques for brace fabrication and most (76.8%) still utilized negative molds. There were no standardized criteria for brace weaning.
CONCLUSION: There are highly variable practices related to nonoperative treatment for AIS and may be related to availability of resources in certain countries. Relative consensus was achieved for when MRI should be obtained and an acceptable brace compliance should be more than 16 hours a day.
MATERIALS AND METHODS: An auricular prosthesis, a complete denture, and anterior and posterior crowns were constructed using conventional methods and laser scanned to create computerized 3D meshes. The meshes were optimized independently by four computer-aided design software (Meshmixer, Meshlab, Blender, and SculptGL) to 100%, 90%, 75%, 50%, and 25% levels of original file size. Upon optimization, the following parameters were virtually evaluated and compared; mesh vertices, file size, mesh surface area (SA), mesh volume (V), interpoint discrepancies (geometric similarity based on virtual point overlapping), and spatial similarity (volumetric similarity based on shape overlapping). The influence of software and optimization on surface area and volume of each prosthesis was evaluated independently using multiple linear regression.
RESULTS: There were clear observable differences in vertices, file size, surface area, and volume. The choice of software significantly influenced the overall virtual parameters of auricular prosthesis [SA: F(4,15) = 12.93, R2 = 0.67, p < 0.001. V: F(4,15) = 9.33, R2 = 0.64, p < 0.001] and complete denture [SA: F(4,15) = 10.81, R2 = 0.67, p < 0.001. V: F(4,15) = 3.50, R2 = 0.34, p = 0.030] across optimization levels. Interpoint discrepancies were however limited to <0.1mm and volumetric similarity was >97%.
CONCLUSION: Open-source mesh optimization of smaller dental prostheses in this study produced minimal loss of geometric and volumetric details. SculptGL models were most influenced by the amount of optimization performed.