Facial Prediction Technology for Edentulous Patients

NCT06080633 | Recruiting

• 1 other identifier: S20230825
• Study Type: observational
• Target: 24
• Locations: 1 country
• Sites: 1

Brief Summary

According to data from the World Health Organization, approximately 160 million people worldwide are edentulous. The incidence increases with age, and the proportion of edentulous patients is higher in the population aged 60 and above. Loss of teeth or edentulism can affect facial appearance, causing people to feel self-conscious and loss confidence in social situations, and even lead to psychological illnesses. Therefore, edentulous patients not only pay close attention to the recovery of oral function but also attach great importance to facial contour improvement. For a long time, due to technological limitations, clinicians have been unable to depict the changes in facial contour after implant placement for patients before surgery. However, with the development of artificial intelligence technology, deep learning-based methods for predicting soft tissue facial deformation have made this mission a possibility. This study established a multi-modal dataset for edentulous patients before and after implant restoration to lay the foundation for predicting facial contour changes after implant treatment. A graph generative adversarial network based on multi-modal data was proposed to achieve fast and high-precision facial contour prediction. To address the common challenges of slow computation and excessive computational resource consumption in current triangular mesh deformation simulation methods, this project innovatively proposed a graph generative adversarial network that uses multi-modal data and incorporates self-attention mechanisms to achieve fast and high-precision facial contour prediction for edentulous patients after implant restoration.

Conditions

Edentulous Jaw

Keywords

Edentulous Jaw; deep learning; oral implantology; facial prediction

Outcome Measures

Primary Outcomes (1)

• Changes in Soft Tissue Volume in the Lip Region after Implant Dentistry

  Quantitative analysis of lip volume changes in patients after oral implant surgery using facial scanning equipment

  Between pre-operation and after Implant-Supported Fixed Prostheses up to 3 months

Eligibility Criteria

• Age: 50 Years - 100 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Patient with Edentulous Maxilla after Implant Prosthetic Restoration

You may qualify if:

• Patients with complete edentulism,
• aged 50 years or above,
• in good physical health,

You may not qualify if:

• patients who refuse to participate in the study，
• patients who cannot undergo facial scanning.

Sponsors & Collaborators

• KU Leuven: lead

Study Sites (1)

Hongyang Ma

Leuven, Heverlee, 3000, Belgium

RECRUITING

MeSH Terms

Conditions

Jaw, Edentulous

Condition Hierarchy (Ancestors)

Jaw Diseases; Musculoskeletal Diseases; Stomatognathic Diseases; Mouth, Edentulous; Mouth Diseases; Tooth Diseases

Study Design

• Study Type: observational
• Observational Model: CASE ONLY
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Research Associate

Study Record Dates

• First Submitted: August 29, 2023
• First Posted: October 12, 2023
• Study Start: June 1, 2023
• Primary Completion: December 1, 2025
• Study Completion (Estimated): December 1, 2026
• Last Updated: June 13, 2024

Record last verified: 2024-06

Locations

BE (1)