Computerized Facial Recognition for Automated Diagnosis of the Facio-Scapulo-Humeral Muscular Dystrophy (FSMHD) (CV4DIAGNOSIS)
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|ClinicalTrials.gov Identifier: NCT04377217|
Recruitment Status : Unknown
Verified May 2020 by Centre Hospitalier Universitaire de Nice.
Recruitment status was: Recruiting
First Posted : May 6, 2020
Last Update Posted : August 27, 2020
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.
|Condition or disease||Intervention/treatment||Phase|
|Facio-Scapulo-Humeral Dystrophy||Other: Video recording||Not Applicable|
|Study Type :||Interventional (Clinical Trial)|
|Estimated Enrollment :||100 participants|
|Intervention Model:||Single Group Assignment|
|Masking:||None (Open Label)|
|Official Title:||Computerized Facial Recognition for Automated Diagnosis of the Facio-Scapulo-Humeral Muscular Dystrophy (FSMHD): Pilot Study|
|Estimated Study Start Date :||September 2020|
|Estimated Primary Completion Date :||March 2021|
|Estimated Study Completion Date :||March 2021|
Experimental: Video recording
The experimenter will make a standardized video of the patient during the inclusion process, and a second one after 18 months.
Other: Video recording
The experimenter will make a standardized video of the patient during the inclusion process, and a second one after 18 months, in order to evaluate the evolution of facial damage. Then algorithms will be developped to be able of differentiating FSHMD patients with facial damage from control subjects using video and audio recordings.
- Video recording [ Time Frame: fisrt day ]Sensitivity and specificity of the algorithm to differentiate FSMHD patients with moderate and severe facial impairment from control subjects
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04377217
|Contact: Luisa VILLA, Dr||492038729 ext +email@example.com|
|Hopital Pasteur 2||Recruiting|
|Nice, France, 06001|
|Contact: Luisa VILLA, Dr 492038729 ext +33 firstname.lastname@example.org|
|Principal Investigator:||Luisa VILLA, Dr||Centre Hospitalier Universitaire de Nice|