NCT04377217: CV4DIAGNOSIS

Computerized Facial Recognition for Automated Diagnosis of the Facio-Scapulo-Humeral Muscular Dystrophy (FSMHD)

Completed NA Last updated 15 November 2023

What this trial tests

NA trial testing Video recording in Facio-Scapulo-Humeral Dystrophy in 17 participants. Completed in 25 July 2019.

Timeline

5 March 2019

Primary endpoint
25 July 2019

25 July 2019

Quick facts

Lead sponsor	Centre Hospitalier Universitaire de Nice
Phase	NA
Status	Completed
Study type	INTERVENTIONAL
Allocation	na
Design	single group
Masking	none
Primary purpose	diagnostic
Enrollment	17
Start date	5 March 2019
Primary completion	25 July 2019
Estimated completion	25 July 2019
Sites	1 location across France

Drugs / interventions tested

• Video recording

Conditions studied

• Facio-Scapulo-Humeral Dystrophy — all drugs for Facio-Scapulo-Humeral Dystrophy →

Sponsor

Centre Hospitalier Universitaire de Nice

Who can join

18 and older, any sex, with Facio-Scapulo-Humeral Dystrophy. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

The clinical diagnosis of Facio-Scapulo-Humeral Muscular Dystrophy (FSHMD) requires the movement of patients to a medical centre and a lengthy examination involving medical personnel, and may be underestimated in the most moderate cases. Thus, it requires costly and burdensome logistics both for patients living in remote areas and having to undertake long and expensive travel, and for clinical staff. This is an obstacle to large-scale diagnosis. The investigators plan to alleviate these limitations through the use of digital facial analysis technology that would enable large-scale diagnosis of patients through telemedicine.

Motivated by the reasons described above and by preliminary results, the goal of this project is to develop methods to automatically detect and monitor the progression of this disease using computer vision algorithms. In order to do this, the investigators will first build up a bank of images and videos of patients with moderate to severe FSHMD, patients with other muscular dystrophies causing facial muscle asymmetry, as well as control subjects without facial involvement. Each of these subjects will be characterized clinically and genetically.

The investigators will then develop computer tools using video and audio sensors capable of detecting facial muscle damage in patients with FSHMD and differentiating them from control subjects on the one hand and patients with other muscular dystrophies on the other hand. The investigators wish to use the most recent advances in terms of "deep-learning" and improve their architecture in order to achieve our objectives.

In addition to this holistic approach, the investigators will study facial recognition approaches capable of accurately identifying different facial areas on images, as well as the relevance of different statistical properties of facial dynamics (duration and intensity). These algorithms will also be useful for monitoring the evolution of facial damage in order to develop a specific measurement tool that could be used in patient follow-up and in clinical trials on early stages of the disease.

Publications & conference data

No peer-reviewed publications indexed yet for this trial. Completed trials usually publish results within 12-18 months.