Predict Tooth Wear

Study Results

Results pending

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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Recruitment Status

RECRUITING

Total Enrollment

1000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2023-12-12

Study Completion Date

2027-12-31

Brief Summary

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Tooth wear, resulting from gradual loss of dental hard tissue due to mechanical and chemical factors, impacts tooth structure, texture, and function. It affects quality of life, with varying prevalence (26.9% to 90.0%), and is traditionally detected visually during check-ups, often at advanced stages. Monitoring alterations in tooth shape via intraoral scanners aids early detection, but restoration remains challenging. Prevention through early detection is vital, as patients may not fully comprehend tooth structure loss until visible. Recently, statistical shape analysis (SSA) used to learn the tooth anatomy and define a reference shape (biogeneric tooth) using. However, assuring landmark consistency is challenging mostly due to biases of the operator. Recently, a robust method called MEG-IsoQuad offered automated, isotopological remeshing. Combining this with SSA holds promise for diagnostic and simulation purposes. This study aims to assess the reliability of a remeshing-SSA approach for altered and intact premolar analysis and compare machine learning algorithms for simulating the shape of the initially intact tooth or future altered one.

The clinical perspective of the current work offers possibilities to:

* Prevent future tooth wear by detecting it at an early stage; and communicate better to the patient by presenting him/her potential future altered teeth
* Simulate the adapted reconstruction for the altered tooth by simulating the initially intact one

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Detailed Description

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Conditions

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Prediction of Tooth Wear

Study Design

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Observational Model Type

COHORT

Study Time Perspective

RETROSPECTIVE

Study Groups

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all mature teeth presenting a tooth wear intact or presenting a tooth wear altered

Scaling of the tooth before scanning by the operator Evaluation of the tooh wear index 0 or 1 (by 2 calibrated experts )

Tooth Shape assessed using an intraoral scanner one after avulsion

Intervention Type OTHER

* Tooth Shape assessed using an intraoral scanner one after avulsion and stored as StereoLithography (STL) file
* Age, gender, reason of avulsion, type of tooth taken from the database and stored in a google sheet

Interventions

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Tooth Shape assessed using an intraoral scanner one after avulsion

* Tooth Shape assessed using an intraoral scanner one after avulsion and stored as StereoLithography (STL) file
* Age, gender, reason of avulsion, type of tooth taken from the database and stored in a google sheet

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* teeth avulsed presenting a tooth wear index between 0 and 3
* mature incisor, canine, premolar or molars (1st and 2nd only)

Exclusion Criteria

* teeth avulsed presenting a tooth wear index over 3 (or presenting an oral rehabilitation representative of a similar wear)
* immature teeth or teeth without root edification
* wisdom teeth

Minimum Eligible Age

18 Years

Maximum Eligible Age

80 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No