Digital Dysmorphology Project
Down Syndrome Detection From Facial Photographs Using Machine Learning Techniques
1 other identifier
interventional
750
1 country
1
Brief Summary
In this study, the investigators propose a novel method to detect Down syndrome using photography for facial dysmorphology, a tool called computer-aided diagnosis (CAD). After validating the method, this technology will be expanded to perform similar functions to assist in the detection of other dysmorphic syndromes. By using photography and image analysis this automated assessment tool would have the potential to improve the diagnosis rate and allow for remote, non-invasive diagnostic evaluation for dysmorphologists in a timely manner.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Feb 2013
Longer than P75 for not_applicable
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
February 1, 2013
CompletedFirst Submitted
Initial submission to the registry
October 22, 2015
CompletedFirst Posted
Study publicly available on registry
January 11, 2016
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 1, 2023
CompletedStudy Completion
Last participant's last visit for all outcomes
December 1, 2023
CompletedFebruary 1, 2023
January 1, 2023
10.8 years
October 22, 2015
January 31, 2023
Conditions
Outcome Measures
Primary Outcomes (2)
Number of participants with Down syndrome accurately assessed by computer-aided detection (CADe) tool
The study will enroll and analyze photographic data from syndromic and non-syndromic cases to investigate the parameters required to achieve an accuracy of the computer-aided detection (CADe) tool for children with genetic syndromes at a level of 90% accuracy.
5 years
Number of participants with Down syndrome accurately assessed by computer-aided detection (CADe) tool
The study will enroll and analyze photographic data from syndromic and non-syndromic cases to investigate the parameters required to achieve an accuracy of the computer-aided detection (CADe) tool for children with genetic syndromes at a level of 95% accuracy.
5 years
Secondary Outcomes (2)
Number of participants with other dysmorphic syndromes accurately assessed by computer-aided detection (CADe) tool
5 years
Number of participants with other dysmorphic syndromes accurately assessed by computer-aided detection (CADe) tool
5 years
Study Arms (2)
Down syndrome
ACTIVE COMPARATORphotographs of individuals less than 18 yo with Down syndrome
Control group
ACTIVE COMPARATORphotographs of individuals less than 18 yo with a genetic referral (not Down syndrome) or a healthy sibling to a child with Down syndrome
Interventions
computer based program to analyze photographs (computer-aided diagnosis (CAD) software)
Eligibility Criteria
You may qualify if:
- Pediatric subject with Down syndrome.
- Healthy pediatric siblings of a subject with Down syndrome and/or other individuals with another genetic referral to serve as a control group.
- Subject must be less than 18 years old.
You may not qualify if:
- Subjects 18 years or older.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Kevin Clearylead
- Children's National Research Institutecollaborator
- George Washington Universitycollaborator
- Chiang Mai Universitycollaborator
Study Sites (1)
Children's National
Washington D.C., District of Columbia, 20010, United States
MeSH Terms
Conditions
Interventions
Condition Hierarchy (Ancestors)
Intervention Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Kevin Cleary, PhD
Children's National Research Institute
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- NON RANDOMIZED
- Masking
- NONE
- Purpose
- HEALTH SERVICES RESEARCH
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR INVESTIGATOR
- PI Title
- PhD
Study Record Dates
First Submitted
October 22, 2015
First Posted
January 11, 2016
Study Start
February 1, 2013
Primary Completion
December 1, 2023
Study Completion
December 1, 2023
Last Updated
February 1, 2023
Record last verified: 2023-01