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Morphology in Oral Rare Syndromes & Artificial Intelligence for Clinical Diagnosis

NCT07666269 · Status: NOT_YET_RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 240

Last updated 2026-06-24

No results posted yet for this study

Summary

MOSAIC aims to determine whether oro-dental morphological anomalies, particularly palatal morphology, associated with rare bone and cartilage diseases can be precisely characterized using 3D digital models analysed through geometric morphometrics. The study will also evaluate whether these morphological signatures can train an artificial intelligence (AI) algorithm to classify syndromes. A prospective monocentric case-control cohort will be constituted, including 3D intra-oral scans and associated clinical data. The final goal is to improve diagnostic accuracy and reduce diagnostic delay in rare bone disorders.

Conditions

  • Osteogenesis Imperfecta
  • Rare Bone Disorders
  • Hypophosphatemia
  • X-Linked
  • Mucopolysaccharidoses
  • Tooth Abnormalities
  • Palate; Deformity
  • Artificial Intelligence (AI)
  • Machine Learning

Interventions

OTHER

intra-oral 3D optical impression

Participants will undergo a single visit including an intra-oral 3D optical impression and collection of clinical/genetic data

Sponsors & Collaborators

  • UMR 1026 BioTis

    collaborator UNKNOWN

  • UMR 5199 PACEA

    collaborator UNKNOWN

  • UMR 5259 LAMCOS

    collaborator UNKNOWN

  • University Hospital, Bordeaux

    lead OTHER

Study Design

Allocation
NON_RANDOMIZED
Purpose
BASIC_SCIENCE
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2026-09-01
Primary Completion
2028-03-01
Completion
2028-03-01

Countries

  • France

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07666269 on ClinicalTrials.gov