Clinical Validation of DystoniaNet Deep Learning Platform for Diagnosis of

Status Recruiting

Clinical Trial Summary

This research involves retrospective and prospective studies for clinical validation of a DystoniaNet deep learning platform for the diagnosis of isolated dystonia.

Clinical Trial 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 onset, and the average diagnostic delay extends up to 10.1 years. This study will conduct retrospective and prospective studies to clinically validate the performance of DystoniaNet, a biomarker-based deep learning platform for the diagnosis of isolated dystonia. The retrospective studies will clinically validate the diagnostic performance of the DystoniaNet algorithm (1) in patients compared to healthy subjects (normative test), and (2) between patients with dystonia and other neurological and non-neurological conditions (differential test). The prospective randomized study will validate the performance of DystoniaNet algorithm for accurate, objective, and fast diagnosis of dystonia in the actual clinical setting. This research is expected to advance the DystoniaNet algorithm for dystonia diagnosis into its clinical use for increased accuracy of dystonia diagnosis. Early detection and diagnosis of dystonia will enable its early therapy and improved prognosis, having an overall positive impact on healthcare and patients' quality of life. ;

Study Design

Related Conditions & MeSH terms

Dyskinesias
Dysphonia
Dystonia
Dystonic Disorders
Essential Tremor
Myoclonus
Nerve Compression Syndromes
Parkinson Disease
Temporomandibular Joint Disorders
Temporomandibular Joint Dysfunction Syndrome
Tic Disorders
Torticollis
Ulnar Nerve Entrapment

Clinical Trial Details

NCT number	NCT05317390
Study type	Interventional
Source	Massachusetts Eye and Ear Infirmary
Contact	Kristina Simonyan, MD, PhD
Phone	617-573-6016
Email	simonyan_lab@meei.harvard.edu
Status	Recruiting
Phase	N/A
Start date	June 1, 2022
Completion date	April 30, 2027

View Details

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Clinical trials are conducted in a series of steps, called phases - each phase is designed to answer a separate research question.

Phase 1: Researchers test a new drug or treatment in a small group of people for the first time to evaluate its safety, determine a safe dosage range, and identify side effects.
Phase 2: The drug or treatment is given to a larger group of people to see if it is effective and to further evaluate its safety.
Phase 3: The drug or treatment is given to large groups of people to confirm its effectiveness, monitor side effects, compare it to commonly used treatments, and collect information that will allow the drug or treatment to be used safely.
Phase 4: Studies are done after the drug or treatment has been marketed to gather information on the drug's effect in various populations and any side effects associated with long-term use.

Clinical Validation of DystoniaNet Deep Learning Platform for Diagnosis of Isolated Dystonia

Clinical Trial Summary

Clinical Trial Description

Study Design

Related Conditions & MeSH terms