Clinical trial NCT02651493: Digital Dysmorphology Project
Official title: Down Syndrome Detection From Facial Photographs Using Machine Learning Techniques
Study type: INTERVENTIONAL
Overall status: UNKNOWN
Phase: NA
Conditions: Down Syndrome
Lead sponsor: Children's National Research Institute
Sponsor class: OTHER
Collaborators: name: Children's National Research Institute
name: George Washington University
name: Chiang Mai University
First posted: 2016-01-11
Enrollment: 750
Sex: ALL
Maximum age (years): 18
Standard ages: CHILD
ADULT
Accepts healthy volunteers: yes
Allocation: NON_RANDOMIZED
Intervention model: PARALLEL
Primary purpose: HEALTH_SERVICES_RESEARCH

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.

Detailed description: In this study, investigators propose a novel method to detect Down syndrome using photography for facial dysmorphology, a tool called computer-aided diagnosis (CAD) . Local texture features based on Contourlet transform and local binary pattern are investigated to represent the facial characteristics. A support vector machine classifier is then used to discriminate between normal and abnormal cases. Accuracy, precision and recall are used to evaluate the method. After validating the method, this technology will then 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.

Eligibility criteria: Inclusion Criteria:

* 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.

Exclusion Criteria:

* Subjects 18 years or older.

Primary outcomes:
measure: Number of participants with Down syndrome accurately assessed by computer-aided detection (CADe) tool
timeFrame: 5 years
measure: Number of participants with Down syndrome accurately assessed by computer-aided detection (CADe) tool
timeFrame: 5 years
Secondary outcomes:
measure: Number of participants with other dysmorphic syndromes accurately assessed by computer-aided detection (CADe) tool
timeFrame: 5 years
measure: Number of participants with other dysmorphic syndromes accurately assessed by computer-aided detection (CADe) tool
timeFrame: 5 years
Other outcomes:
Locations:
city: Washington
country: United States
facility: Children's National
state: District of Columbia
Study officials:
affiliation: Children's National
name: Kevin Cleary, PhD
role: PRINCIPAL_INVESTIGATOR
References: