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

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)

Status

Completed

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT03920995

Enrollment

1000

Registered

2019-04-19

Start date

2020-04-01

Completion date

2023-10-31

Last updated

2024-03-06

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Multiple Sclerosis

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.

Interventions

None listed

Study design

Observational model

CASE_ONLY

Time perspective

RETROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

18 Years to 85 Years

Healthy volunteers

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

Design outcomes

Primary

Measure	Time frame	Description
Multi-center registry of MRI scans	2 years	Measuring the ability of DeepGRAI to measure thalamus volume as a predictor of clinical outcomes for patients with multiple sclerosis

Countries

United States

Outcome results