Condition or disease |
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Multiple Sclerosis |
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 |
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 |
Inclusion Criteria:
Access to raw MRI index scan images that meet all of the below criteria
Access to raw MRI post-index scan images that meet all of the below listed criteria
Exclusion Criteria:
United States, New York | |
University at Buffalo | |
Buffalo, New York, United States, 14203 |
Principal Investigator: | Robert Zivadinov | University at Buffalo |
Tracking Information | |||||
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First Submitted Date | March 12, 2019 | ||||
First Posted Date | April 19, 2019 | ||||
Last Update Posted Date | January 6, 2021 | ||||
Actual Study Start Date | May 13, 2019 | ||||
Estimated Primary Completion Date | September 30, 2021 (Final data collection date for primary outcome measure) | ||||
Current Primary Outcome Measures |
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
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Original Primary Outcome Measures |
Multi-center registry of MRI scans [ Time Frame: 2 years ] Measuring the ability of DeepGRAI's ability to measure thalamus volume can predict clinical outcomes for patients with multiple sclerosis
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Change History | |||||
Current Secondary Outcome Measures | Not Provided | ||||
Original Secondary Outcome Measures | Not Provided | ||||
Current Other Pre-specified Outcome Measures | Not Provided | ||||
Original Other Pre-specified Outcome Measures | Not Provided | ||||
Descriptive Information | |||||
Brief Title | Multi-center Database Registry to Study Thalamus Changes Using AI in MS | ||||
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) | ||||
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). | ||||
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. | ||||
Study Type | Observational | ||||
Study Design | Observational Model: Case-Only Time Perspective: Retrospective |
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Target Follow-Up Duration | Not Provided | ||||
Biospecimen | Not Provided | ||||
Sampling Method | Non-Probability Sample | ||||
Study Population | Individuals with Multiple sclerosis who have 2 MRI scans | ||||
Condition | Multiple Sclerosis | ||||
Intervention | Not Provided | ||||
Study Groups/Cohorts | Not Provided | ||||
Publications * | Not Provided | ||||
* Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline. |
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Recruitment Information | |||||
Recruitment Status | Active, not recruiting | ||||
Actual Enrollment |
1000 | ||||
Original Estimated Enrollment | Same as current | ||||
Estimated Study Completion Date | December 31, 2021 | ||||
Estimated Primary Completion Date | September 30, 2021 (Final data collection date for primary outcome measure) | ||||
Eligibility Criteria |
Inclusion Criteria:
Exclusion Criteria:
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Sex/Gender |
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Ages | 18 Years to 85 Years (Adult, Older Adult) | ||||
Accepts Healthy Volunteers | No | ||||
Contacts | Contact information is only displayed when the study is recruiting subjects | ||||
Listed Location Countries | United States | ||||
Removed Location Countries | |||||
Administrative Information | |||||
NCT Number | NCT03920995 | ||||
Other Study ID Numbers | N/A-NI-MS-PI-13632 | ||||
Has Data Monitoring Committee | No | ||||
U.S. FDA-regulated Product |
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IPD Sharing Statement |
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Responsible Party | Robert Zivadinov, MD, PhD, University at Buffalo | ||||
Study Sponsor | University at Buffalo | ||||
Collaborators | Celgene | ||||
Investigators |
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PRS Account | University at Buffalo | ||||
Verification Date | January 2021 |