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

October 24, 2023 updated by: Kristina Simonyan, Massachusetts Eye and Ear Infirmary
This research involves retrospective and prospective studies for clinical validation of a DystoniaNet deep learning platform for the diagnosis of isolated dystonia.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Detailed 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 Type

Interventional

Enrollment (Estimated)

1000

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • United States
    • Massachusetts
      • Boston, Massachusetts, United States, 02114
        • Recruiting
        • Massachusetts Eye and Ear Infirmary
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Description

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.

Exclusion criteria:

  1. Patients who are incapable of giving informed consent;
  2. Patients who are unable to undergo brain MRI due to the presence of certain tattoos and ferromagnetic objects in their bodies (e.g., implanted stimulators, surgical clips, prosthesis, artificial heart valve) that cannot be removed or due to pregnancy or breastfeeding at the time of the study.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Double

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
No Intervention: Retrospective clinical validation of DystoniaNet
Retrospective studies will (1) clinically validate the diagnostic performance of DystoniaNet compared to a normal neurological state (normative test), and (2) develop and test DystoniaNet extensions in comparison with other neurological and non-neurological conditions (differential test).
Experimental: Prospective clinical validation of DystoniaNet
Prospective randomized studies will validate DystoniaNet performance for accurate, objective, and fast diagnosis of dystonia in the actual clinical setting.
Diagnostic test: DystoniaNet-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

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Correctness of clinical diagnosis of dystonia using the DystoniaNet algorithm
Time Frame: 4 years
Correctness of dystonia diagnosis (yes dystonia/no dystonia) will be established using the DystoniaNet machine-learning algorithm
4 years
Time of clinical diagnosis of dystonia using the DystoniaNet algorithm
Time Frame: 4 years
The length of time (in months) from symptom onset to clinical diagnosis will be established using the DystoniaNet machine-learning algorithm
4 years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Massachusetts Eye and Ear Infirmary

Investigators

  • Principal Investigator: Kristina Simonyan, MD, PhD, Massachusetts Eye and Ear

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

June 1, 2022

Primary Completion (Estimated)

April 30, 2027

Study Completion (Estimated)

April 30, 2027

Study Registration Dates

First Submitted

November 28, 2021

First Submitted That Met QC Criteria

March 30, 2022

First Posted (Actual)

April 7, 2022

Study Record Updates

Last Update Posted (Actual)

October 25, 2023

Last Update Submitted That Met QC Criteria

October 24, 2023

Last Verified

October 1, 2023

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 2020P004129

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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