Evaluating Face-Recognition Technology in Syndrome Diagnosis

Evaluating the Clinical Utility of Face-Recognition Technology in Syndrome Diagnosis

Birth defects are relatively common, occurring in 1 in 40 live born babies. They can be single, or multiple. They may occur as part of multiple malformation syndromes, often in association with growth disturbance or intellectual disability. Over 7000 rare syndromes have been identified. Thus, though they are rare they are collectively important. Understanding how a multiple malformation syndrome came about, defining what investigations and health surveillance is needed for affected children and identifying whether there is a treatment is very important for parents and professionals caring for affected children and also for genetic counselling of their extended families, since the majority will have a genetic basis. Diagnosis of these rare disorders is therefore important,but as many syndromes are rare this can be extremely difficult and requires specialist knowledge, many investigations and many hospital appointments. This study aims to determine whether using face-recognition software can improve diagnosis of rare syndromes when used in addition to current routine practice.

Study Overview

• Status: Completed
• Conditions: Inborn Errors of Metabolism; Dysmorphic Features; Multiple Anomalies
• Intervention / Treatment: Diagnostic test: Face2Gene

Detailed Description

Clinicians see over 2000 patients per year who have rare syndromes in Manchester NHS clinics. In the majority of these individuals the cause is unknown. Many will have a genetic cause, but knowing which genes to test and being able to access these tests is difficult. When a patient comes to the clinic, details of their medical and developmental history are collected , and they are examined in detail to look at their investigation results. New tests may also be ordered for patients. In many cases, subtle differences in physical features, especially facial features may provide an important clue to the underlying diagnosis. However, because many of the conditions seen are so rare and doctors may not have seen that particular condition before, the diagnosis may not be made immediately at the appointment. In those cases, permission will be sought to take photographs so that further opinions can be sought within the department or by sharing with national and sometimes international colleagues. This is routine practice. Where consent has been obtained for photos, these are then first reviewed in a departmental case-review meeting. They may then also be presented at regional, national or even international meetings aimed at syndrome diagnosis with patient consent.

The study aims to recruit patients who are attending clinics for syndrome diagnosis, and who have differences in their facial features. Such patients will undergo a full routine diagnostic work-up as outlined above. Following that, if patients have consented to having photographs taken as part of standard care, they will be asked if they would consent to upload of the facial photographs to a digital face recognition system, along with upload of a list of key clinical features, to see which diagnoses are suggested by this software.

A group of Inherited Metabolic Disease patients with known diagnoses will be included under the Faces sub-study to establish whether the technology may help to define their phenotype. This group of patients would be asked to send photos to the research team either by email via a secure email address or by post. The study would request one facial photo of each of the biological parents (where applicable and available).

There will first of all be routine discussion of patients and photographs in a case review meeting as per standard practice. Differential diagnoses will be formulated and recorded based on this. Following this, the facial photo will be uploaded to a face recognition system and suggested diagnoses from this recorded. Any diagnostic suggestions considered worthy of investigation will be followed up in line with standard practice.

The investigators will then determine whether this was made a) in the standard way b) only suggested by the face recognition software or c) utilising the two methods together.

Patients will be followed up to see if a final diagnosis is confirmed. The patient/parents will also be sent a questionnaire by email or post 6 months after recruitment. The questionnaire will ask if they had any concerns about using FDNA, if they found it helpful and if so in what way. Another questionnaire to professionals will collect information on how easy they found it to use, how helpful they found it ranging 1-5, did it alter patient management, if so how, and other comments

. The investigators will document whether utilising the software helped to arrive at an earlier diagnosis, whether it impeded the diagnosis by providing misleading or incorrect guidance, whether parents and professionals found its use acceptable and whether it impacted on the patient's management.

• Study Type: Interventional
• Enrollment (Actual): 111
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United Kingdom
  • Greater Manchester
    • Manchester, Greater Manchester, United Kingdom, M13 9WL
      • Manchester University NHS Foundation Trust

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 2 years and older (Child, Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

Inclusion Criteria:

- Patients attending routine genetic clinic/paediatric clinic appointments for diagnosis of a multiple anomaly syndrome where distinctive facial features form part of their presenting pattern.

OR:

- Biochemically or genetically confirmed diagnosis of inborn disorder of metabolism where no well described dysmorphic facial features are known to be associated with disorder

Exclusion Criteria:

• Patients under 8 months of age where face-recognition technology has not been shown to be effective.
• Patients who decline clinical photography as part of standard care.
• Patients who do not wish to consent to participation in the study even though they consent to photos being taken for standard care.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Diagnostic
• Allocation: Non-Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Other: Main Study; Patients attending routine genetic clinic/paediatric clinic appointments for diagnosis of a multiple anomaly syndrome where distinctive facial features form part of their presenting pattern.	Diagnostic test: Face2Gene; This study investigates whether a new diagnostic intervention (Face2Gene facial recognition software) is better than using standard approach to diagnosis.
Other: Faces Sub Study; Patients eligible to be recruited to the Faces Sub Study will have biochemically or genetically confirmed diagnosis of inborn disorder of metabolism where no well described dysmorphic facial features are known to be associated with disorder.	Diagnostic test: Face2Gene; This study investigates whether a new diagnostic intervention (Face2Gene facial recognition software) is better than using standard approach to diagnosis.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Number of diagnoses	The number of diagnoses of rare syndrome disorders made, measured after standard practice	through study completion, an average of 2 years
Number of diagnoses	The number of diagnoses of rare syndrome disorders made, Measured after use of the Face2Gene app	through study completion, an average of 2 years

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Patient satisfaction	Level of satisfaction of parents with use of a face recognition system and with e-health approaches to genetic counselling and diagnosis in general. Measured via a patient experiences questionnaire that requires both quantitative and qualitative responses. The proportion of patients who found use of the software acceptable will be measured. There results will not be reported on a fixed scale.	6 months after recruitment.
Professional satisfaction	Level of satisfaction of professionals with use of a face recognition system. Measured via a colleagues experiences questionnaire that requires both quantitative and qualitative responses. The proportion of professionals who found using the software acceptable/helpful and would continue using the software in practice will be measured. There results will not be reported on a fixed scale.	24 months
Number of syndromes	Number of syndromes identified where face recognition software has facilitated genetic investigation.	24 months

Collaborators and Investigators

• Sponsor: Manchester University NHS Foundation Trust
• Collaborators: FDNA Inc.
• Investigators: Principal Investigator: Sofia Douzgou, MD PhD FRCP, Manchester University NHS Foundation Trust

Study record dates

Study Major Dates

• Study Start (Actual): January 30, 2018
• Primary Completion (Actual): November 25, 2020
• Study Completion (Actual): November 25, 2020

Study Registration Dates

• First Submitted: December 3, 2020
• First Submitted That Met QC Criteria: January 13, 2021
• First Posted (Actual): January 14, 2021

Study Record Updates

• Last Update Posted (Actual): January 14, 2021
• Last Update Submitted That Met QC Criteria: January 13, 2021
• Last Verified: January 1, 2021

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Metabolic Diseases; Genetic Diseases, Inborn; Metabolism, Inborn Errors
• Other Study ID Numbers: R04765

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: No

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No