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

Status Completed

Clinical Trial 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).

Clinical Trial 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 Design

Related Conditions & MeSH terms

Clinical Trial Details

NCT number	NCT03920995
Study type	Observational
Source	University at Buffalo
Contact
Status	Completed
Phase
Start date	April 1, 2020
Completion date	October 31, 2023

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