Development and Validation of an Automated Three-dimensional Cephalometry Method

Study Overview
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Brief Summary
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This study is aimed to develop and assess the validity of an algorithm for automated three-dimensional cephalometry.

Detailed Description
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Cephalometric analysis is a standardized diagnostic method used daily by orthodontists and maxillofacial surgeons. It is based on linear and angular measurements performed on radiographic images. This examination is traditionally done manually on two-dimensional radiographs, which does not allow to analyze finely the bilateral structures which are found superimposed. Cephalometric analysis of three-dimensional imaging (cone beam computed tomography (CBCT) or computed tomography scan (CT-Scan)) may provide additional diagnostic information, particularly for patients with maxillofacial abnormalities or marked asymmetries. One of the obstacle to the clinical use of three-dimensional cephalometric analysis is the time and expertise needed to manually place the landmarks. Automatic methods described in literature are preliminary and lack validation in a clinical context. Our retrospective observational study is aimed to develop and validate a new automated three-dimensional cephalometry method. This method will be based on a deep learning algorithm trained from a database of pre-surgery CT-Scans of patients with have undergone an orthognathic surgery. These CT-Scans will be manually annotated to provide a reference standard for the training of the algorithm and its evaluation. The validation of our results will focus on demonstrating the diagnostic effectiveness and robustness of three-dimensional cephalometric measurements obtained in this clinical context.

Official Title
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Development and Validation of an Automated Three-dimensional Cephalometry Method

Conditions
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Orthognathic Surgery, Dentofacial Deformities

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Patients followed in the maxillofacial surgery department of Pitie-Salpetriere hospital (AP-HP, Paris, France) since 2014; who underwent orthognathic surgery; who had, for surgery planning, a three-dimensional radiographic examination (CT-Scan) which has been segmented for the manufacture of a custom-made device; who did not object to the research.

Ages Eligible for Study
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Minimum Age: 15 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Average distances (in mm) between the points placed automatically and the points placed manually (reference). |  | through study completion, an average of 1 year | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Percentage of points placed automatically within 2 / 3 / 4 mm of the the points placed manually (reference) |  | through study completion, an average of 1 year | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Imaging, three-dimensional, Cephalometry, Anatomic Landmarks, Radiographic Image Interpretation, Deep Learning, Orthodontics