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

NCT03920995

CompletedN/A

Sponsor: University at Buffalo

Conditions: Multiple Sclerosis

Countries: United States

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).

Eligibility overview

Sex: ALL

Age: 18 Years to 85 Years

Healthy volunteers: No

Study type: OBSERVATIONAL

Eligibility criteria

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

Locations (1)

Buffalo, New York, United States