Predict Tooth Wear
Public ClinicalTrials.gov record NCT06681844. Field values are reproduced from the official study page; the official ClinicalTrials.gov record remains the source of truth for eligibility, enrollment, and contact information.
Data is sourced from official ClinicalTrials.gov public API records. Always review the official ClinicalTrials.gov record for the latest information.
Official title
Prediction of the Tooth Wear Index Based on a Dataset of Dental Shapes:a Retrospective Study
Brief summary
Reproduced verbatim from the official ClinicalTrials.gov record. Not medical advice.
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
Study identification
- NCT ID
- NCT06681844
- Recruitment status
- Recruiting
- Study type
- Observational
- Phase
- Not listed
- Enrollment
- 1,000 participants
Conditions and interventions
Conditions
Eligibility (public fields only)
- Age range
- 18 Years to 80 Years
- Sex
- All
- Healthy volunteers
- Healthy volunteers not accepted
This page does not interpret eligibility. Detailed inclusion and exclusion criteria are on the official ClinicalTrials.gov record.
Study timeline
- Start date
- Dec 11, 2023
- Primary completion
- Dec 11, 2025
- Completion
- Nov 30, 2027
- Last update posted
- Nov 7, 2024
2023 – 2027
United States locations
- U.S. sites
- 1
- U.S. states
- 1
- U.S. cities
- 1
| Facility | City | State | ZIP | Site status |
|---|---|---|---|---|
| Indiana University Hospital | Indianapolis | Indiana | 46202 | Recruiting |
Site contact phone numbers, emails, and investigator names are intentionally not displayed here. Open the official ClinicalTrials.gov record for site contact information.
Non-U.S. locations
This page focuses on the U.S. directory. The official record also lists 4 non-U.S. sites.
About this trial record page
- What this page shows
- Public field values for ClinicalTrials.gov record NCT06681844, including study identification, conditions, interventions, eligibility (age, sex, healthy volunteer), timeline, and U.S. site list.
- What this page does not do
- No medical advice, eligibility judgments, treatment recommendations, study quality scoring, or AI-generated medical summaries. No site contact phone numbers, emails, or investigator names.
- Where the data comes from
- Sourced from the official ClinicalTrials.gov public API. The official record is the source of truth.
- Last refresh
- Last update posted Nov 7, 2024 · Synced Sep 4, 2026
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Open the official record
The complete protocol, eligibility criteria, and contact information for NCT06681844 live on ClinicalTrials.gov.