DeciFace: Decipher the Influence of Ethnic Backgrounds on the Facial Dysmorphic Features of Rare Mendelian Disorders

NCT05913843 | Recruiting

• 1 other identifier: 202302053RIND
• Study Type: observational
• Target: 100
• Locations: 1 country
• Sites: 1

Brief Summary

There are more than 7000 known genetic disorders, and the number of affected is estimated to be about 6-10% of the population. Around 30 to 40% of genetic disorders have physical changes in the face and skull such as Down's syndrome or Fragile X syndrome. Therefore, the known facial phenotype of many genetic disorders is highly informative to clinical diagnosis. Since a large number of genetic diseases are associated with special facial phenotypes that are difficult to remember, automated facial analysis such as Face2Gene and GestaltMatcher can assist in the identification and diagnosis of facial phenotypes related to various genetic diseases. Although the current advances in whole exome sequencing (whole exome sequencing) or whole genome sequencing (whole genome sequencing) have greatly improved the diagnostic rate of genetic diseases, about half of the patients are still undiagnosed. For patients with special facial phenotypes, the investigators believe that by combining automated facial analysis and whole exome sequencing data, it should be possible to provide a fast and accurate diagnostic model of genetic mutations for genetic diseases. GestaltMatcher Database is a medical imaging database of rare diseases developed by Professor Peter Krawitz of the University of Bonn, Germany. The database's artificial intelligence module will infer a patient's possible diagnosis based on the patient's photo, age, gender, race, and clinical description. The database will be open to medical researchers in related fields to improve the diagnosis of rare diseases. The investigators will use GestaltMatcher to assist in the diagnosis of patients, and compare the accuracy and significant differences in facial deformities between Taiwanese patients and patients from different countries. And use Eye Tracker to analyze how doctors diagnose patients through facial photos, and compare whether there are significant differences between foreign patients and Taiwanese patients in the diagnosis literature of Taiwanese doctors. The project will also analyze how genetic doctors at the University of Bonn in Germany diagnose patients, and compare it with Taiwanese doctors to better understand the differences in the process of doctors diagnosing patients and ethnic backgrounds.

Conditions

Rare Diseases

Keywords

Automated facial analysis

Outcome Measures

Primary Outcomes (2)

• The diagnosis accuracy rate of use GestaltMatcher to analysis participant facial features in rare diseases

  GestaltMatcher is a automated facial analysis software, which utilized deep convolutional neural networks trained on patients' photos as an encoder to convert facial photos into feature vectors to form a Clinical Face Phenotype Space (CFPS). And quantified the similarity among patients by the cosine distance of two vectors in CFPS. With this approach, the investigators can support the ultra-rare syndromes that lack images to be trained and push the supported syndromes. Base on on this technology, the investigators use GestaltMatcher to analysis participant facial features and compare those vectors which are similar to patients to find possible syndromes. The investigators will verify more clinical phenotype and genetic data of the participants for verification.

  1 month

• The significant difference in facial deformities between Taiwan participant and participant from different countries by GestaltMatcher

  The investigators will ues those facial feature vectors from GestaltMatcher Database to compare with Taiwan participants in the research platform within the GestaltMatcher Database to find the facial differences between Taiwan and other different countries participants by pairwise matrix. To find out where is the difference between Taiwan and different countries participants, improving the diagnostic perspectives in Taiwanese groups.

  3 years

Secondary Outcomes (2)

• Criteria for doctors to diagnose participants from facial features assessed by eye trackers

  3 years

• Diagnosis differences between Taiwan and Bonn University genetics doctors

  3 years

Interventions

Take photo DEVICE

We will use the camera to take 2 front and side images of the participant, and select one of the better images to upload to the facial analysis system (GestaltMatcher Database) for analysis.

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Cases with abnormal appearance of clinical symptoms and suspected genetic diseases at National Taiwan University Hospital

You may qualify if:

• Cases with abnormal appearance of clinical symptoms and suspected genetic diseases

You may not qualify if:

• Unable to cooperate with the examiner

Sponsors & Collaborators

• National Taiwan University Hospital: lead
• University of Bonn: collaborator

Study Sites (1)

National Taiwan University Hospital

Taipei, 10041, Taiwan

RECRUITING

MeSH Terms

Conditions

Rare Diseases

Condition Hierarchy (Ancestors)

Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Officials

• Ni-Chung Lee, M.D., Ph.D.

  National Taiwan University Hospital

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Ni-Chung Lee, M.D., Ph.D.

CONTACT

886-2-23123456; ncleentu@ntu.edu.tw

Study Design

• Study Type: observational
• Observational Model: CASE ONLY
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: May 23, 2023
• First Posted: June 22, 2023
• Study Start: July 30, 2024
• Primary Completion (Estimated): June 30, 2026
• Study Completion (Estimated): June 30, 2026
• Last Updated: August 20, 2025

Record last verified: 2025-08

Data Sharing

• IPD Sharing: Will not share

Locations

TW (1)