Browsing by Subject "orthodontics"

Now showing 1 - 4 of 4
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    Accuracy of 3D Reconstructed Orthodontic Models
    (2014) Stewart, Kelton; Chai, Billy; Liu, Sean; Ghoneima, Ahmed; Alford, Timothy
    Objective: To evaluate the accuracy of 3D reconstructed orthodontic models, derived by various digitization methods, as compared to conventional orthodontic plaster models. Materials and Methods: Twenty-five maxillary orthodontic plaster models were randomly selected from the Indiana University School of Dentistry Department of Orthodontics. Each plaster model was scanned with the Cadent iOC scanner and the digital data was used to print 3D reconstructed orthodontic models. The same 25 plaster models were duplicated using alginate and poured in plaster after two days. These duplicated plaster models were also scanned with the iOC scanner and 3D reconstructed. Next, the duplicate plaster models were sent to a lab, scanned with a 3Shape R700 scanner, and the digital data was 3D reconstructed. Digital calipers were used to obtain ten linear dimensional measurements on all plaster and 3D reconstructed models for comparisons. Equivalence testing was performed using 2 one-sided paired t-tests with a significance level of P <0.05. Results: Nine of the 10 linear measurements were statistically equivalent in all groups. Clinically insignificant, but statistically significant, measurement differences in maxillary central incisor height (P <0.05) were found on 3D reconstructed models derived from the 3Shape R700 desktop scanner. Conclusion: 3D reconstructed orthodontic models derived from alginate impressions, iOC scanners, and 3Shape R700 scanners are an accurate and reliable substitute for orthodontic plaster models.
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    Bimaxillary Protrusion with an Atrophic Alveolar Defect: Orthodontics, Autogenous Chin-Block Graft, Soft Tissue Augmentation, and an Implant
    (Elsevier, 2015-01) Chiu, Grace; Chang, Chris; Roberts, W. Eugene; Department of Orthodontics and Oral Facial Genetics
    Bimaxillary protrusion in a 28 yr female was complicated by multiple missing, restoratively compromised or hopeless teeth. The maxillary right central incisor (#8) had a history of avulsion and replantation, that subsequently evolved into generalized external root resorption with Class III mobility and a severe loss of supporting periodontium. This complex malocclusion had a Discrepancy Index (DI) of 21, and 8 additional points were scored for the atrophic dental implant site (#8). The comprehensive treatment plan was extraction of four teeth (# 5, 8, 12 & 30), orthodontic closure of all space except for the future implant site (#8), augmentation of the alveolar defect with a autogenous chin- block graft, enhancement of the gingival biotype with a connective tissue graft, and an implant-supported prosthesis. Orthodontists must understand the limitations of bone grafts. Augmented alveolar defects are slow to completely turn over to living bone, so they are usually good sites for implants, but respond poorly to orthodontic space closure. However, postsurgical orthodontics treatment is often indicated to optimally finish the esthetic zone prior to placing the final prosthesis. The latter was effectively performed for the present patient resulting in a total treatment time of ~36 months for comprehensive, interdisciplinary care. An excellent functional and esthetic result was achieved, as documented by a Cast-Radiograph Evaluation (CRE) score of 21 and a Pink & White dental esthetics score of 2.
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    Osteocytes and mechanical loading: The Wnt connection
    (Wiley, 2019-05) Bullock, Whitney A.; Pavalko, Frederick M.; Robling, Alexander G.; Anatomy and Cell Biology, School of Medicine
    Bone adapts to the mechanical forces that it experiences. Orthodontic tooth movement harnesses the cell‐ and tissue‐level properties of mechanotransduction to achieve alignment and reorganization of the dentition. However, the mechanisms of action that permit bone resorption and formation in response to loads placed on the teeth are incompletely elucidated, though several mechanisms have been identified. Wnt/Lrp5 signalling in osteocytes is a key pathway that modulates bone tissue's response to load. Numerous mouse models that harbour knock‐in, knockout and transgenic/overexpression alleles targeting genes related to Wnt signalling point to the necessity of Wnt/Lrp5, and its localization to osteocytes, for proper mechanotransduction in bone. Alveolar bone is rich in osteocytes and is a highly mechanoresponsive tissue in which components of the canonical Wnt signalling cascade have been identified. As Wnt‐based agents become clinically available in the next several years, the major challenge that lies ahead will be to gain a more complete understanding of Wnt biology in alveolar bone so that improved/expedited tooth movement becomes a possibility.
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    Precision and Accuracy Assessment of Cephalometric Analyses Performed by Deep Learning Artificial Intelligence with and without Human Augmentation
    (MDPI, 2023-06-08) Panesar, Sumer; Zhao , Alyssa; Hollensbe, Eric; Wong, Ariel; Bhamidipalli, Surya Sruthi; Eckert, George; Dutra, Vinicius; Turkkahraman, Hakan; Orthodontics and Oral Facial Genetics, School of Dentistry
    The aim was to assess the precision and accuracy of cephalometric analyses performed by artificial intelligence (AI) with and without human augmentation. Four dental professionals with varying experience levels identified 31 landmarks on 30 cephalometric radiographs twice. These landmarks were re-identified by all examiners with the aid of AI. Precision and accuracy were assessed by using intraclass correlation coefficients (ICCs) and mean absolute errors (MAEs). AI revealed the highest precision, with a mean ICC of 0.97, while the dental student had the lowest (mean ICC: 0.77). The AI/human augmentation method significantly improved the precision of the orthodontist, resident, dentist, and dental student by 3.26%, 2.17%, 19.75%, and 23.38%, respectively. The orthodontist demonstrated the highest accuracy with an MAE of 1.57 mm/°. The AI/human augmentation method improved the accuracy of the orthodontist, resident, dentist, and dental student by 12.74%, 19.10%, 35.69%, and 33.96%, respectively. AI demonstrated excellent precision and good accuracy in automated cephalometric analysis. The precision and accuracy of the examiners with the aid of AI improved by 10.47% and 27.27%, respectively. The AI/human augmentation method significantly improved the precision and accuracy of less experienced dental professionals to the level of an experienced orthodontist.