Clinical Validation of DystoniaNet Deep Learning Platform for Diagnosis of Isolated Dystonia
Massachusetts Eye and Ear Infirmary
Summary
This research involves retrospective and prospective studies for clinical validation of a DystoniaNet deep learning platform for the diagnosis of isolated dystonia.
Description
Isolated dystonia is a movement disorder of unknown pathophysiology, which causes involuntary muscle contractions leading to abnormal, typically patterned, twisting movements and postures. A significant challenge in the clinical management of dystonia is due to the absence of a biomarker and associated 'gold' standard diagnostic test. Currently, the diagnosis of dystonia is guided by clinical evaluations of its symptoms, which lead to a low agreement between clinicians and a high rate of diagnostic inaccuracies. It is estimated that only 5% of patients receive an accurate diagnosis at symptom…
Eligibility
- Age range
- Not specified
- Sex
- All
- Healthy volunteers
- Yes
Inclusion criteria: 1. Males and females of diverse racial and ethnic backgrounds, with age across the lifespan; 2. Patients will have at least one of the forms of dystonia, including focal dystonia (e.g., laryngeal, cervical, oromandibular, blepharospasm, focal hand, musicians), segmental dystonia, or generalized dystonia; 3. Patients will have other movement disorders (Parkinson's disease, essential tremor, dyskinesia, myoclonus) and other non-neurological conditions (tic disorders, torticollis, ulnar nerve entrapments, temporomandibular disorders, dysphonia) that mimic dystonic symptoms.…
Interventions
- Diagnostic TestDystoniaNet-based diagnosis of isolated dystonia
DystoniaNet will be used for the diagnosis of dystonia and its differential diagnosis from other neurological and non-neurological disorders mimicking symptoms of dystonia
Location
- Massachusetts Eye and Ear InfirmaryBoston, Massachusetts