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A Postoperative Evaluation Guideline for Computer-Assisted Reconstruction of the Mandible

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Published on: January 28, 2020

Machine-learning-based approach for predicting postoperative skeletal changes for orthognathic surgical planning.

Qingchuan Ma^1,2, Etsuko Kobayashi³, Bowen Fan³

¹Department of Oral-Maxillofacial Surgery and Orthodontics, The University of Tokyo Hospital, Tokyo, Japan.

The International Journal of Medical Robotics + Computer Assisted Surgery : MRCAS

|February 8, 2022

Summary

This study presents a machine learning approach to aid orthognathic surgery planning. The AI model predicts postoperative skeletal changes, potentially reducing surgeon workload.

Keywords:

3D cephalometry automatic landmarking machine learning orthognathic surgery surgical planning

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Last Updated: Oct 4, 2025

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Area of Science:

Medical Imaging
Artificial Intelligence
Surgical Planning

Background:

Increasing patient populations are augmenting surgeons' workload in manual orthognathic surgical planning.
A novel machine learning (ML) approach is introduced to streamline surgical planning for orthognathic procedures.

Purpose of the Study:

To develop and evaluate an ML-based system for predicting postoperative skeletal changes in orthognathic surgery.
To assess the accuracy and efficiency of the ML model in comparison to human surgeons.

Main Methods:

Utilized preoperative and 1-year postoperative CT images from 56 patients.
Developed a 12-layer cascaded deep neural network with two successive models for end-to-end prediction.
The first model identifies 2D landmarks from 3D volumes; the second predicts skeletal changes.

Main Results:

The ML model achieved a prediction accuracy of 5.4 mm at the landmark level within 42.9 seconds.
The model successfully represented 74.4% of 3D regions at the volume level against surgeon-defined ground truth.

Conclusions:

Demonstrated the feasibility of using ML for predicting postoperative skeletal changes in orthognathic surgery.
The proposed ML approach shows significant potential to alleviate the workload of surgeons involved in orthognathic procedures.