Development and Validation of an Automated Three-dimensional Cephalometry Method
NCT ID: NCT04464252
Last Updated: 2022-10-31
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
453 participants
OBSERVATIONAL
2022-04-30
2022-04-30
Brief Summary
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Detailed Description
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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.
Conditions
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Study Design
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COHORT
RETROSPECTIVE
Eligibility Criteria
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Inclusion Criteria
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.
15 Years
ALL
No
Sponsors
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Laboratoire de Biomécanique Georges Charpak
OTHER
Assistance Publique - Hôpitaux de Paris
OTHER
Responsible Party
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Locations
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Service de Chirurgie Maxillo-Faciale, Service de Chirurgie Maxillo-Faciale
Paris, , France
Countries
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Other Identifiers
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APHP200215
Identifier Type: -
Identifier Source: org_study_id
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