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Multi-center Database Registry to Study Thalamus Changes Using AI in MS

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details. Identifier: NCT03920995
Recruitment Status : Active, not recruiting
First Posted : April 19, 2019
Last Update Posted : January 6, 2021
Information provided by (Responsible Party):
Robert Zivadinov, MD, PhD, University at Buffalo

Brief Summary:
In this study the Investigator's propose to validate a newly developed approach, DeepGRAI (Deep Gray Rating via Artificial Intelligence), to simplify the calculation of thalamic atrophy in a clinical routine and allow academic and community neurologists to plan, perform, and publish novel and influential clinical research using data from clinical routine, by employing deep machine learning (DML) pattern recognition (PR) information through use of artificial intelligence (AI).

Condition or disease
Multiple Sclerosis

Detailed Description:
This is a multicenter, observational, retrospective, cross-sectional and longitudinal population study of brain volume changes in MS patients. The retrospective electronic medical record (EMR) and brain MRI image data will be collected at participating MS centers and de-identified data will be integrated into a central research database. All the data to be integrated into the database has already been collected by physicians at the centers as part of their routine clinical practice and is thus non-interventional and retrospective in nature. This new approach will be compared to existing approaches of brain volume measurement that are currently widely available. This breakthrough approach would lead to potentially abandoning classis measurement of the specific brain volume structures and would be applicable in real-time in clinical routine.

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Study Type : Observational
Actual Enrollment : 1000 participants
Observational Model: Case-Only
Time Perspective: Retrospective
Official Title: Creation of a Multi-center Database Registry to Study Real World Thalamus Volume Changes by Use of Artificial Intelligence in Patients With Multiple Sclerosis (MS)
Actual Study Start Date : May 13, 2019
Estimated Primary Completion Date : September 30, 2021
Estimated Study Completion Date : December 31, 2021

Resource links provided by the National Library of Medicine

Primary Outcome Measures :
  1. Multi-center registry of MRI scans [ Time Frame: 2 years ]
    Measuring the ability of DeepGRAI to measure thalamus volume as a predictor of clinical outcomes for patients with multiple sclerosis

Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years to 85 Years   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population
Individuals with Multiple sclerosis who have 2 MRI scans

Inclusion Criteria:

  1. Patient diagnosed with relapsing-remitting (RR) MS
  2. Access to raw MRI index scan images that meet all of the below criteria

    1. MRI scan image acquired at index
    2. The scan was performed on 1.5T or 3T scanners
    3. The scan must have a T2-FLAIR sequence
  3. Access to raw MRI post-index scan images that meet all of the below listed criteria

    1. MRI scan image acquired at post-index
    2. The scan was performed on 1.5T or 3T scanners
    3. The scan must have a T2-FLAIR sequence
  4. Age 18-85 at index
  5. Fulfilling the MRI scan and clinical data requirements outlined in Table 2
  6. None of the exclusion criteria

Exclusion Criteria:

  1. Have received an investigational drug or experimental procedure during the study period
  2. Women who were pregnant, or lactating at index or during the post-index period
  3. Patients who had a relapse 30 days prior to the selected MRI scan date
  4. Patients who received steroid treatment 30 days prior to the selected MRI scan date
  5. Presence of other neurologic diseases affecting CNS

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its identifier (NCT number): NCT03920995

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United States, New York
University at Buffalo
Buffalo, New York, United States, 14203
Sponsors and Collaborators
University at Buffalo
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Principal Investigator: Robert Zivadinov University at Buffalo
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Responsible Party: Robert Zivadinov, MD, PhD, Director and Professor, University at Buffalo Identifier: NCT03920995    
Other Study ID Numbers: N/A-NI-MS-PI-13632
First Posted: April 19, 2019    Key Record Dates
Last Update Posted: January 6, 2021
Last Verified: January 2021
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Additional relevant MeSH terms:
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Multiple Sclerosis
Pathologic Processes
Demyelinating Autoimmune Diseases, CNS
Autoimmune Diseases of the Nervous System
Nervous System Diseases
Demyelinating Diseases
Autoimmune Diseases
Immune System Diseases