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Abstract #3110

Semi-automatic cloud-based workflow for evaluating the central vein sign for MS diagnosis in a multicenter clinical setting

David Moreno-Dominguez1, Marc Ramos1, Daniel S Reich2, Daniel Ontaneda3, Paulo Rodrigues4, and Pascal Sati2

1Neuroimaging, QMENTA Inc., Barcelona, Spain, 2Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States, 3Mellen Center for Multiple Sclerosis Treatment and Research, Cleveland Clinic, Cleveland, OH, United States, 4QMENTA Inc., Barcelona, Spain

The central vein sign (CVS) is novel MRI marker for improving the accuracy and reducing the time to diagnose patients with multiple sclerosis (MS). Recent advancements have introduced the MRI FLAIR* contrast, allowing for CVS to be easily identified. In this work, we developed a semi-automatic cloud-based workflow for evaluating the clinical value of the CVS for MS diagnosis using FLAIR* in a multicenter setting. This novel workflow is a powerful tool that has the potential to significantly accelerate the clinical research imaging studies in MS.

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