Actively Recruiting
Clinical Validation of DystoniaNet Deep Learning Platform for Diagnosis of Isolated Dystonia
Led by Massachusetts Eye and Ear Infirmary · Updated on 2025-12-02
1000
Participants Needed
1
Research Sites
N/A
Total Duration
On this page
AI-Summary
What this Trial Is About
This research focuses on isolated dystonia, a movement disorder that causes involuntary muscle contractions leading to abnormal twisting movements and postures. Diagnosing dystonia is challenging because there is no biomarker or gold standard test, resulting in frequent misdiagnoses and delays averaging over 10 years. The study aims to clinically validate DystoniaNet, a deep learning platform designed to improve the accuracy and speed of dystonia diagnosis through retrospective and prospective studies. The study consists of two parts: retrospective studies will validate DystoniaNet's diagnostic ability by comparing patients with dystonia to healthy individuals and to patients with other neurological or non-neurological conditions that mimic dystonia symptoms. The prospective randomized study will test DystoniaNet's performance for fast, objective diagnosis in actual clinical settings. The intervention involves using DystoniaNet as a diagnostic test to distinguish dystonia from similar disorders. Participants will undergo clinical evaluations and brain imaging data will be analyzed by the DystoniaNet algorithm to measure the correctness and speed of dystonia diagnosis over four years. Researchers will monitor diagnostic accuracy, time to diagnosis, and compare results across patient groups. This study aims to advance dystonia diagnosis to clinical practice, enabling earlier treatment and better patient outcomes, with participation lasting throughout the study period ending in 2028.
CONDITIONS
Brief Title
Clinical Validation of DystoniaNet Deep Learning Platform for Diagnosis of Isolated Dystonia
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Males and females of diverse racial and ethnic backgrounds, with age across the lifespan
- Patients with at least one form of dystonia, including focal, segmental, or generalized dystonia
- Patients with other movement disorders or non-neurological conditions mimicking dystonia symptoms, such as Parkinson's disease, essential tremor, dyskinesia, myoclonus, tic disorders, torticollis, ulnar nerve entrapments, temporomandibular disorders, or dysphonia
You will not qualify if you...
- Patients unable to give informed consent
- Patients unable to undergo brain MRI due to tattoos, ferromagnetic implants, pregnancy, or breastfeeding
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Your Study Journey
Duration - 2 to 4 weeks
Participants are screened for eligibility to participate in the trial.
1 visit (in-person)
Duration - Up to 4 years
Participants undergo diagnostic procedures using the DystoniaNet deep learning platform to assess for isolated dystonia and differentiate it from other conditions.
Visits as needed during the diagnostic process
Duration - Up to 4 years
Participants are monitored over time to evaluate the accuracy and timeliness of dystonia diagnosis using the DystoniaNet algorithm in clinical settings.
Follow-up visits depending on clinical need
Trial Site Locations
Total: 1 location
1
Massachusetts Eye and Ear Infirmary
Boston, Massachusetts, United States, 02114
Actively Recruiting
Research Team
K
Kristina Simonyan, MD, PhD
How is the study designed?
Study Type
INTERVENTIONAL
Masking
DOUBLE
Allocation
RANDOMIZED
Model
PARALLEL
Primary Purpose
DIAGNOSTIC
Number of Arms
2
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