Massachusetts Eye and Ear Infirmary
Kristina Simonyan
This research involves retrospective and prospective studies for clinical validation of a DystoniaNet deep learning platform for the diagnosis of isolated dystonia.
Dystonia
Drug Induced Dystonia
Parkinson Disease
Essential Tremor
Dyskinesias
Myoclonus
Tic Disorders
Torticollis
Ulnar Nerve Entrapment
Temporomandibular Joint Disorders
Dysphonia
DystoniaNet-based diagnosis of isolated dystonia
NA
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 |
| Estimated Enrollment : | 1000 participants |
| Masking : | DOUBLE |
| Primary Purpose : | DIAGNOSTIC |
| Official Title : | Clinical Validation of DystoniaNet Deep Learning Platform for Diagnosis of Isolated Dystonia |
| Actual Study Start Date : | 2022-06-01 |
| Estimated Primary Completion Date : | 2028-04-30 |
| Estimated Study Completion Date : | 2028-04-30 |
Information not available for Arms and Intervention/treatment
| Ages Eligible for Study: | |
| Sexes Eligible for Study: | ALL |
| Accepts Healthy Volunteers: | 1 |
Want to participate in this study, select a site at your convenience, send yourself email to get contact details and prescreening steps.
RECRUITING
Massachusetts Eye and Ear Infirmary
Boston, Massachusetts, United States, 02114