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8. Artificial Intelligence Used for Diagnosis in Facial Deformities: A Systematic Review.

Author

Ravelo, Victor, Acero, Julio, Fuentes-Zambrano, Jorge, García Guevara, Henry, and Olate, Sergio

Subjects
ARTIFICIAL intelligence, ORTHOGNATHIC surgery, HUMAN abnormalities, DIAGNOSIS, THREE-dimensional imaging
Abstract

AI is included in a lot of different systems. In facial surgery, there are some AI-based software programs oriented to diagnosis in facial surgery. This study aims to evaluate the capacity and training of models for diagnosis of dentofacial deformities in class II and class III patients using artificial intelligence and the potential use for indicating orthognathic surgery. The search strategy is from 1943 to April 2024 in PubMed, Embase, Scopus, Lilacs, and Web of Science. Studies that used imaging to assess anatomical structures, airway volume, and craniofacial positions using the AI algorithm in the human population were included. The methodological quality of the studies was assessed using the Effective Public Health Practice Project instrument. The systematic search identified 697 articles. Eight studies were obtained for descriptive analysis after exclusion according to our inclusion and exclusion criteria. All studies were retrospective in design. A total of 5552 subjects with an age range between 14.7 and 56 years were obtained; 2474 (44.56%) subjects were male, and 3078 (55.43%) were female. Six studies were analyzed using 2D imaging and obtained highly accurate results in diagnosing skeletal features and determining the need for orthognathic surgery, and two studies used 3D imaging for measurement and diagnosis. Limitations of the studies such as age, diagnosis in facial deformity, and the included variables were observed. Concerning the overall analysis bias, six studies were at moderate risk due to weak study designs, while two were at high risk of bias. We can conclude that, with the few articles included, using AI-based software allows for some craniometric recognition and measurements to determine the diagnosis of facial deformities using mainly 2D analysis. However, it is necessary to perform studies based on three-dimensional images, increase the sample size, and train models in different populations to ensure accuracy of AI applications in this field. After that, the models can be trained for dentofacial diagnosis [ABSTRACT FROM AUTHOR]

Published
2024
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46. Horizontal Bone Augmentation in the Posterior Atrophic Mandible and Dental Implant Stability Using the Tenting Screw Technique.

Author

Farias, Daniel, Caceres, Felipe, Sanz, Antonio, and Olate, Sergio

Subjects
BONE grafting, DENTAL implants, BONE screws, OPERATIVE dentistry, TORQUE, MANDIBLE, BIOMEDICAL materials, COMPUTED tomography
Abstract

The aim of this study was to analyze horizontal bone augmentation using the tenting screw technique in the posterior mandible. Included subjects had a 3-mm bone width and 9-mm bone height, measured by CBCT. After the surgical approach, two to four screws were inserted, leaving 4 mm of extraosseous space; reconstruction was achieved using allogeneic biomaterial and leukocyte- and platelet-rich fibrin together with an absorbable membrane. After 4 months, a new CBCT scan was obtained to compare the bone gain and implant placement. Early and secondary stability were measured by the implant stability quotient (ISQ); prosthetic load was performed 16 weeks later. Student t test was used to compare bone gains and implant stability, with significance set at P < .05. Fourteen subjects and 27 surgical sites initially exhibited a mean bone width of 2.95 ± 0.75 mm. Four months after augmentation, the bone width was 7.15 ± 1.87 mm, confirming a significant bone gain (4.2 ± 1.26 mm). Twenty-seven implants were placed with a minimum insertion torque of 35 Ncm; the primary stability was 69.3 ± 7.16 ISQ, and the secondary stability was 75.9 ± 3.29 ISQ (P > .05). It may be concluded that the tenting screw technique is predictable in terms of bone gain and that it facilitates implant stability. [ABSTRACT FROM AUTHOR]

Published
2021
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