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Artificial intelligence for treatment planning and soft tissue outcome prediction of orthognathic treatment: A
Daisy Salazar1, Paul Emile Rossouw1, Fawad Javed1
1Department of Orthodontics and Dentofacial Orthopedics, Eastman Institute for Oral Health, University of Rochester, Rochester, NY, USA.
Background:
The accuracy of artificial intelligence (AI) in treatment planning and outcome prediction in orthognathic treatment (OGT) has not been systematically reviewed.
Objectives:
To determine the accuracy of AI in treatment planning and soft tissue outcome prediction in OGT.
Design:
Systematic review.
Data Sources:
Unrestricted search of indexed databases and reference lists of included studies.
Data Selection:
Clinical studies that addressed the focused question 'Is AI useful for treatment planning and soft tissue outcome prediction in OGT?' were included.
Data Extraction:
Study screening, selection and data extraction were performed independently by two authors. The risk of bias (RoB) was assessed using the Cochrane Collaboration's RoB and ROBINS-I tools for randomised and non-randomised clinical studies, respectively.
Data Synthesis:
Eight clinical studies (seven retrospective cohort studies and one randomised controlled study) were included. Four studies assessed the role of AI for treatment decision making; and four studies assessed the accuracy of AI in soft tissue outcome prediction after OGT. In four studies, the level of agreement between AI and non-AI decision making was found to be clinically acceptable (at least 90%). In four studies, it was shown that AI can be used for soft tissue outcome prediction after OGT; however, predictions were not clinically acceptable for the lip and chin areas. All studies had a low to moderate RoB.
Limitations:
Due to high methodological inconsistencies among the included studies, it was not possible to conduct a meta-analysis and reporting biases assessment.
Conclusion:
AI can be a useful aid to traditional treatment planning by facilitating clinical treatment decision making and providing a visualisation tool for soft tissue outcome prediction in OGT.
Registration:
PROSPERO CRD42022366864.
