Development and Validation of an Automated Three-dimensional Cephalometry Method (AutoCEPH-3D)

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

Study Overview

• Status: Completed
• Conditions: Orthognathic Surgery; Dentofacial Deformities

Detailed Description

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.

• Study Type: Observational
• Enrollment (Actual): 453

Contacts and Locations

Study Locations

• France
  • Paris, France, 75013
    • Service de Chirurgie Maxillo-Faciale, Service de Chirurgie Maxillo-Faciale

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 15 years and older (Child, Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Probability Sample

Study Population

Primary care hospital (hopital de la Pitié-Salpêtrière, AP-HP, Paris, France), maxillofacial surgery department

Description

Inclusion Criteria:

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

Study Plan

How is the study designed?

Design Details

• Observational Models: Cohort
• Time Perspectives: Retrospective

What is the study measuring?

Primary Outcome Measures

Outcome Measure	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	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

Collaborators and Investigators

• Sponsor: Assistance Publique - Hôpitaux de Paris
• Collaborators: Laboratoire de Biomécanique Georges Charpak

Study record dates

Study Major Dates

• Study Start (Actual): April 30, 2022
• Primary Completion (Actual): April 30, 2022
• Study Completion (Actual): April 30, 2022

Study Registration Dates

• First Submitted: June 17, 2020
• First Submitted That Met QC Criteria: July 8, 2020
• First Posted (Actual): July 9, 2020

Study Record Updates

• Last Update Posted (Actual): October 31, 2022
• Last Update Submitted That Met QC Criteria: October 28, 2022
• Last Verified: October 1, 2022

More Information

Terms related to this study

• Keywords: Deep Learning; Orthodontics; Imaging, three-dimensional; Cephalometry; Anatomic Landmarks; Radiographic Image Interpretation
• Additional Relevant MeSH Terms: Congenital Abnormalities; Musculoskeletal Diseases; Stomatognathic Diseases; Stomatognathic System Abnormalities; Maxillofacial Abnormalities; Craniofacial Abnormalities; Musculoskeletal Abnormalities; Dentofacial Deformities
• Other Study ID Numbers: APHP200215

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: No

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No