Artificial intelligence for treatment planning and soft tissue outcome prediction of orthognathic treatment: A systematic review

Abstract

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.